{
  "data": {
    "a": {
      "slug": "everos",
      "name": "EverOS",
      "vendor": "Evermind AI, Inc.",
      "vendorUrl": "https://evermind.ai",
      "kind": "http-api",
      "category": "agent-memory",
      "summary": "EverOS, formerly EverMemOS, is EverMind's open-source memory runtime for agents. It stores conversations, files and agent trajectories as Markdown with SQLite and LanceDB indexes, behind a local HTTP API and MCP server, with a managed EverOS Cloud.",
      "url": "https://www.anchorterminal.com/tools/everos",
      "markdownUrl": "https://www.anchorterminal.com/tools/everos.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/everos.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/everos.json",
      "dns": "everos.grade.anchorterminal.com",
      "repo": "https://github.com/EverMind-AI/EverOS",
      "license": "Apache-2.0",
      "transports": [
        "http",
        "stdio"
      ],
      "packages": [
        {
          "registry": "pypi",
          "name": "everos"
        },
        {
          "registry": "pypi",
          "name": "everos-mcp"
        }
      ],
      "auth": "none",
      "authNotes": "The self-hosted server has no authentication and binds to 127.0.0.1:8000 by default. The owner supplies LLM and embedding provider keys in ~/.everos/everos.toml. EverOS Cloud uses a bearer API key from the console at everos.evermind.ai, and its hosted MCP connector signs in with an EverOS account.",
      "pricing": "freemium",
      "pricingNotes": "Free under Apache-2.0 to run locally, with LLM and embedding costs paid to the chosen provider. EverOS Cloud has a console and API keys, but no plan or price was found on evermind.ai or docs.evermind.ai.",
      "priceSummary": "Freemium",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "No x402, MPP or L402 in the repository, the OpenAPI document, llms.txt or the docs (checked 2026-11-06).",
        "endpoints": []
      },
      "toolCount": 7,
      "popularity": {
        "githubStars": 13839,
        "npmWeekly": null,
        "pypiWeekly": 4033,
        "asOf": "2026-11-06"
      },
      "docsUrl": "https://docs.evermind.ai",
      "llmsTxt": "https://docs.evermind.ai/llms.txt",
      "openapi": "https://github.com/EverMind-AI/EverOS/blob/main/docs/openapi.json",
      "capabilities": [
        "memory.store",
        "memory.search",
        "memory.user",
        "memory.delete"
      ],
      "tags": [
        "open-source",
        "self-hosted",
        "local",
        "hosted",
        "apache-2.0",
        "python",
        "mcp",
        "openapi",
        "llms-txt",
        "markdown",
        "no-auth"
      ],
      "lastRelease": "2026-10-22",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 69.4,
        "grade": "B",
        "agentReady": false,
        "rank": 246,
        "ranked": true,
        "rankOf": 1486,
        "categoryRank": 6,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 78,
          "maintenance": 80,
          "payments": 40,
          "reliability": 79,
          "schema": 89,
          "security": 47,
          "transparency": 71
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-06"
        },
        "negative": 0,
        "verdict": "EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.",
        "bestFor": "Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.",
        "strengths": [
          "Apache-2.0 Python library and local server at 1.5.1, with Keep a Changelog entries and semantic versioning declared",
          "OpenAPI document with 40 operations, every one described, and llms.txt plus llms-full.txt for the docs",
          "Retryable conditions are typed, such as 503 SESSION_BUSY and EXTERNAL_SERVICE_UNAVAILABLE for a busy database",
          "Memory is canonical Markdown on disk, editable by hand, with deletion by owner, session or memory id",
          "SECURITY.md with a five-day acknowledgement, plus a valid security.txt at evermind.ai"
        ],
        "weaknesses": [
          "The local HTTP server has no authentication and relies on binding to 127.0.0.1",
          "EverOS Cloud prices, plans and rate limits were not found on any public page",
          "The MCP server's autonomy protocol tells hosts to save facts without being asked, and no prompt-injection guidance was found",
          "The cloud terms of 20 January 2026 forbid automated extraction and allow discontinuing the service without notice",
          "Several outside bug reports, such as a silent capture failure, have no reply"
        ],
        "agentNotes": [
          "Write new code against `/api/v2`; `/api/v1` is a legacy alias that may go in a future major release",
          "Call `/api/v2/memory/flush` at the end of a session, since `add` is asynchronous and buffers recent messages",
          "Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written",
          "Keep `host` at 127.0.0.1 unless something in front adds authentication",
          "Treat recalled memories as untrusted text, since they are extracted from past conversations"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 0,
        "avgRating": 0,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "B",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 69.4
          }
        ],
        "editorialScores": {
          "ergonomics": 78,
          "maintenance": 80,
          "payments": 40,
          "reliability": 79,
          "schema": 89,
          "security": 47,
          "transparency": 66
        },
        "provenanceScore": 75,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-06",
            "maintenance": "2026-11-06",
            "payments": "2026-11-06",
            "reliability": "2026-11-06",
            "schema": "2026-11-06",
            "security": "2026-11-06",
            "transparency": "2026-11-06"
          },
          "last": "2026-11-06",
          "oldest": "2026-11-06",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "uv pip install everos \u0026\u0026 everos init \u0026\u0026 everos server start",
        "http": "curl http://127.0.0.1:8000/health",
        "claudeCode": "claude mcp add everos -e EVEROS_BASE_URL=http://127.0.0.1:8000 -- uvx everos-mcp"
      },
      "letme": {
        "capability": "https://letme.dev/memory.store",
        "tool": "https://letme.dev/everos"
      },
      "area": "agent-runtime",
      "provenance": {
        "legalEntity": "Evermind AI, Inc.",
        "domain": "evermind.ai",
        "domainRegistered": "2020-02-22",
        "endpointOnVendorDomain": null,
        "terms": "https://evermind.ai/terms-of-service",
        "privacy": "https://evermind.ai/privacy-policy",
        "statusPage": "",
        "changelog": "https://github.com/EverMind-AI/EverOS/blob/main/CHANGELOG.md",
        "securityTxt": "valid",
        "checked": "2026-11-06",
        "notes": [
          "Terms and privacy policy both say last updated 20 January 2026 and name Evermind AI, Inc. The terms choose Singapore law and forbid extracting data by bots, scripts, crawlers or data-mining tools, recorded here as a fact.",
          "evermind.ai/robots.txt allows all crawlers and names Claude-Web and anthropic-ai as allowed. docs.evermind.ai carries Content-Signal ai-input=yes.",
          "RDAP gives evermind.ai a registration date of 22 February 2020.",
          "security.txt at evermind.ai/.well-known/ gives contact@evermind.ai and a policy URL, expiring 28 February 2027.",
          "The about page is drawn by script and returned no readable text."
        ],
        "score": 75
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/everos.json",
      "live": {
        "slug": "everos",
        "versions": [
          {
            "registry": "github",
            "name": "EverMind-AI/EverOS",
            "version": "v1.5.1",
            "released": "2026-10-22",
            "seenAt": "2026-11-06T23:24:44.540703115Z"
          },
          {
            "registry": "pypi",
            "name": "everos",
            "version": "1.5.1",
            "released": "2026-10-22",
            "seenAt": "2026-11-06T23:24:41.488069905Z"
          },
          {
            "registry": "pypi",
            "name": "everos-mcp",
            "version": "0.1.1",
            "released": "2026-10-15",
            "seenAt": "2026-11-06T23:24:42.65503941Z"
          }
        ],
        "githubStars": 13840,
        "pypiWeekly": 4033,
        "securityTxt": {
          "url": "https://evermind.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2027-02-28T00:00:00Z",
          "checkedAt": "2026-11-07T16:01:32.419431813Z"
        },
        "llmsTxt": {
          "url": "https://docs.evermind.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-11-07T15:32:26.933711899Z"
        },
        "pages": [
          {
            "url": "https://raw.githubusercontent.com/EverMind-AI/EverOS/main/CHANGELOG.md",
            "kind": "changelog",
            "status": 200,
            "checkedAt": "2026-11-07T14:18:19.185692468Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "40ab92cf4d99"
          },
          {
            "url": "https://evermind.ai/privacy-policy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-11-07T14:09:24.819286526Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "dcd843ca72fe"
          },
          {
            "url": "https://evermind.ai/terms-of-service",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-11-07T14:09:28.72898661Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "009377ab61a3"
          }
        ],
        "updatedAt": "2026-11-07T16:01:32.419431813Z"
      }
    },
    "answer": "EverOS scores 69.4 (B) on agent readiness against Memory (MCP reference server)'s 58.8 (C), and leads in 5 of 7 scored categories. Memory (MCP reference server) leads on payments \u0026 pricing and transparency \u0026 trust.",
    "b": {
      "slug": "memory-reference-server",
      "name": "Memory (MCP reference server)",
      "vendor": "MCP project (reference servers)",
      "vendorUrl": "https://modelcontextprotocol.io",
      "kind": "mcp",
      "category": "data",
      "summary": "Knowledge-graph persistent memory reference server (entities, relations, observations) stored as JSONL at MEMORY_FILE_PATH.",
      "url": "https://www.anchorterminal.com/tools/memory-reference-server",
      "markdownUrl": "https://www.anchorterminal.com/tools/memory-reference-server.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memory-reference-server.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json",
      "dns": "memory-reference-server.grade.anchorterminal.com",
      "repo": "https://github.com/modelcontextprotocol/servers",
      "license": "MIT and Apache-2.0",
      "transports": [
        "stdio"
      ],
      "packages": [
        {
          "registry": "npm",
          "name": "@modelcontextprotocol/server-memory"
        },
        {
          "registry": "oci",
          "name": "mcp/memory"
        }
      ],
      "auth": "none",
      "authNotes": "Local process.",
      "pricing": "free",
      "pricingNotes": "Open source.",
      "priceSummary": "Free · OSS",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Local reference server, no payments.",
        "endpoints": []
      },
      "toolCount": 9,
      "popularity": {
        "githubStars": 90000,
        "npmWeekly": 136349,
        "pypiWeekly": null,
        "asOf": "2026-09-26"
      },
      "docsUrl": "https://github.com/modelcontextprotocol/servers/blob/main/src/memory/README.md",
      "capabilities": [
        "memory.graph"
      ],
      "tags": [
        "reference",
        "local",
        "open-source"
      ],
      "lastRelease": "2026-10-28",
      "graded": true,
      "disclosure": "MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.",
      "anchor": {
        "graded": true,
        "score": 58.8,
        "grade": "C",
        "agentReady": false,
        "rank": 724,
        "ranked": true,
        "rankOf": 1486,
        "categoryRank": 11,
        "methodology": "0.7",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 67,
          "maintenance": 75,
          "payments": 60,
          "reliability": 75,
          "schema": 70,
          "security": 39,
          "transparency": 76
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-11-04"
        },
        "negative": -6,
        "negativeNotes": [
          "-3, a released fix of the server's own described flaw with no advisory. 1.0.0 (tag v1.0.0, 10 October 2026) fixed #4827, where the atomic save added in 2026.8.31 replaced a memory file 'the operator narrowed with chmod 600' with one at 0644, and the temporary file was 'briefly readable at 0644' (1b01ea6d, 819ae904, 463c402f). The changelog calls it keeping the file's permission bits and no GHSA id is cited. https://github.com/modelcontextprotocol/servers/blob/main/src/memory/CHANGELOG.md",
          "-3, published behaviour changed for existing clients with word only on release day. 1.0.0 (10 October 2026) makes a write to a read-only memory file fail with EACCES where 2026.8.31 replaced the file, and fails a write that can't take the new lock file within 60 seconds; 2.0.1 (tag v2.2.0, 28 October 2026) stops startup when the memory.json migration fails, where earlier versions started on an empty graph. Each was described only in that release's changelog. One folded term. https://github.com/modelcontextprotocol/servers/blob/main/src/memory/CHANGELOG.md"
        ],
        "verdict": "Nine tools with typed schemas and accurate read, destructive and idempotent annotations, and since 1.0.0 a lock file keeps two processes from losing each other's writes. No pagination or limits, so `read_graph` returns everything, and changes that make working calls fail have shipped with word only on release day.",
        "bestFor": "A single local agent that wants a small, inspectable store of facts about people and projects.",
        "disclosure": "MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.",
        "strengths": [
          "Nine tools with typed schemas and accurate read, destructive and idempotent annotations",
          "Plain JSONL storage at a path you choose, easy to back up, diff and edit by hand",
          "Atomic writes, a per-process write queue and a cross-process lock file since 1.0.0",
          "Semver releases with a per-package changelog since 1.0.0, four releases since 6 August",
          "The graph is also exposed as an MCP resource with change notifications"
        ],
        "weaknesses": [
          "No pagination or limits. `read_graph` returns everything and `search_nodes` every match",
          "Search is case-insensitive substring matching, with no ranking or semantics",
          "The default file location is inside the package directory, where a reinstall or cache clean can remove it",
          "No read-only mode, and stored text returns verbatim in later sessions with no guidance on untrusted content",
          "1.0.0 and 2.0.1 changed behaviour that made working calls fail, told only in the release's changelog"
        ],
        "agentNotes": [
          "Set `MEMORY_FILE_PATH` to an absolute path in a writable directory. The default sits inside the npx cache, and the lock file needs the directory",
          "Use `search_nodes` or `open_nodes` instead of `read_graph` once the graph holds a few hundred entities or more",
          "Read `skipped` in the `create_entities` result and use `add_observations` for names that already exist",
          "Create both entities before `create_relations`. A missing endpoint fails the whole batch",
          "Run on Node 24 or later since 2.0.0, and keep observations short and factual. They come back verbatim in every later read"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 2.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.7",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 58.8
          }
        ],
        "editorialScores": {
          "ergonomics": 67,
          "maintenance": 75,
          "payments": 60,
          "reliability": 75,
          "schema": 70,
          "security": 39,
          "transparency": 78
        },
        "provenanceScore": 74,
        "checked": {
          "categories": {
            "ergonomics": "2026-11-04",
            "maintenance": "2026-11-04",
            "payments": "2026-11-04",
            "reliability": "2026-11-04",
            "schema": "2026-11-04",
            "security": "2026-11-04",
            "transparency": "2026-11-04"
          },
          "last": "2026-11-04",
          "lastMoved": "2026-11-04",
          "oldest": "2026-11-04",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "claudeCode": "claude mcp add memory -- npx -y @modelcontextprotocol/server-memory",
        "config": {
          "mcpServers": {
            "memory": {
              "args": [
                "-y",
                "@modelcontextprotocol/server-memory"
              ],
              "command": "npx",
              "env": {
                "MEMORY_FILE_PATH": "/data/memory.jsonl"
              }
            }
          }
        }
      },
      "letme": {
        "capability": "https://letme.dev/memory.graph",
        "tool": "https://letme.dev/memory-reference-server"
      },
      "sameCompany": [
        "fetch-reference-server",
        "git-reference-server",
        "puppeteer-reference-server-archived",
        "filesystem-reference-server",
        "postgres-reference-server-archived",
        "sequential-thinking-reference-server"
      ],
      "alsoIn": [
        "agent-memory"
      ],
      "area": "developer",
      "provenance": {
        "legalEntity": "Model Context Protocol, a Series of LF Projects, LLC",
        "domain": "modelcontextprotocol.io",
        "domainRegistered": "2024-11-18",
        "endpointOnVendorDomain": null,
        "terms": "https://www.lfprojects.org/policies/terms-of-use/",
        "privacy": "https://www.lfprojects.org/policies/privacy-policy/",
        "statusPage": "",
        "changelog": "https://github.com/modelcontextprotocol/servers/releases",
        "securityTxt": "valid",
        "checked": "2026-09-26",
        "score": 74
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/memory-reference-server.json",
      "live": {
        "slug": "memory-reference-server",
        "versions": [
          {
            "registry": "github",
            "name": "modelcontextprotocol/servers",
            "version": "v2.3.0",
            "released": "2026-11-04",
            "seenAt": "2026-11-06T23:44:03.926181669Z"
          },
          {
            "registry": "npm",
            "name": "@modelcontextprotocol/server-memory",
            "version": "2.1.0",
            "seenAt": "2026-11-06T23:44:03.713410969Z"
          }
        ],
        "githubStars": 91839,
        "npmWeekly": 297358,
        "securityTxt": {
          "url": "https://modelcontextprotocol.io/.well-known/security.txt",
          "state": "valid",
          "checkedAt": "2026-11-07T16:01:43.564896778Z"
        },
        "domain": {
          "domain": "modelcontextprotocol.io",
          "checkedAt": "2026-11-01T14:07:30.038395054Z"
        },
        "pages": [
          {
            "url": "https://raw.githubusercontent.com/modelcontextprotocol/servers/main/src/memory/CHANGELOG.md",
            "kind": "deprecations",
            "status": 304,
            "checkedAt": "2026-11-07T14:21:57.904273443Z",
            "changedAt": "2026-11-05T13:06:00.440607386Z",
            "fingerprint": "7e1bf59fb9b7"
          }
        ],
        "github": {
          "repo": "modelcontextprotocol/servers",
          "checkedAt": "2026-11-02T09:08:15.395430974Z",
          "stars": 91747,
          "archived": false,
          "issuesEnabled": true,
          "pushedAt": "2026-10-29T05:27:40Z",
          "openIssues": 30,
          "openPRs": 8,
          "issuesOpened90d": 289,
          "issuesClosed90d": 487,
          "prsMerged90d": 276,
          "ci": {
            "branch": "main",
            "runs": 50,
            "success": 44,
            "failure": 0,
            "other": 6,
            "latest": "success",
            "latestAt": "2026-10-28T20:46:50Z"
          },
          "advisories": [
            {
              "ghsa": "GHSA-w766-5x43-whvw",
              "severity": "medium",
              "published": "2026-10-28T21:13:40Z"
            },
            {
              "ghsa": "GHSA-mvf5-2qqv-rg3c",
              "severity": "medium",
              "published": "2026-10-25T00:19:52Z"
            },
            {
              "ghsa": "GHSA-hhwq-wxfx-cj7g",
              "severity": "low",
              "published": "2026-10-25T00:19:37Z"
            },
            {
              "ghsa": "GHSA-53mr-w429-c597",
              "severity": "low",
              "published": "2026-10-25T00:19:21Z"
            },
            {
              "ghsa": "GHSA-v38p-wf49-hx2j",
              "severity": "medium",
              "published": "2026-10-25T00:19:06Z"
            },
            {
              "ghsa": "GHSA-66qx-2266-pmj6",
              "severity": "low",
              "published": "2026-10-25T00:18:52Z"
            },
            {
              "ghsa": "GHSA-7rgq-gccq-qphx",
              "severity": "medium",
              "published": "2026-10-25T00:18:38Z"
            },
            {
              "ghsa": "GHSA-4gxg-m5jx-9j57",
              "severity": "medium",
              "published": "2026-10-25T00:18:21Z"
            },
            {
              "ghsa": "GHSA-3jqg-r5pp-rmp2",
              "severity": "low",
              "published": "2026-10-25T00:15:37Z"
            },
            {
              "ghsa": "GHSA-vjqx-cfc4-9h6v",
              "cve": "CVE-2026-27735",
              "severity": "medium",
              "published": "2026-02-25T23:21:57Z"
            },
            {
              "ghsa": "GHSA-j22h-9j4x-23w5",
              "cve": "CVE-2025-68145",
              "severity": "medium",
              "published": "2025-12-17T16:04:43Z"
            },
            {
              "ghsa": "GHSA-9xwc-hfwc-8w59",
              "cve": "CVE-2025-68144",
              "severity": "medium",
              "published": "2025-12-17T16:01:56Z"
            },
            {
              "ghsa": "GHSA-5cgr-j3jf-jw3v",
              "cve": "CVE-2025-68143",
              "severity": "medium",
              "published": "2025-12-17T15:55:26Z"
            },
            {
              "ghsa": "GHSA-hc55-p739-j48w",
              "cve": "CVE-2025-53110",
              "severity": "high",
              "published": "2025-07-01T18:39:04Z"
            },
            {
              "ghsa": "GHSA-q66q-fx2p-7w4m",
              "cve": "CVE-2025-53109",
              "severity": "high",
              "published": "2025-07-01T18:38:24Z"
            }
          ],
          "replies": {
            "sampled": 25,
            "unanswered": 8,
            "medianDays": 0.5
          }
        },
        "updatedAt": "2026-11-07T16:01:43.564896778Z"
      }
    },
    "edges": [
      {
        "by": 20,
        "category": "payments",
        "leads": "memory-reference-server",
        "name": "Payments \u0026 pricing",
        "reasons": {
          "a": "Self-hosted rule, with the price lines read for EverOS Cloud. No x402, MPP or L402 (0 of 40). No cloud price or plan found on evermind.ai, its FAQ, terms or docs (0). The open-source runtime is free with no card (20). An agent can install it from PyPI and run it with no account (20). Total 40.",
          "b": "Free, self-hosted, nothing to buy, so 20 + 20 + 20. No payment protocol (0)."
        },
        "scores": {
          "a": 40,
          "b": 60
        }
      },
      {
        "by": 19,
        "category": "schema",
        "leads": "everos",
        "name": "Schema \u0026 documentation",
        "reasons": {
          "a": "OpenAPI document in the repository with 40 operations, every one with a description (25). llms.txt and llms-full.txt on docs.evermind.ai (10). Operation descriptions state purpose; when-not-to-use guidance appears in the docs, such as flush after add, rather than per operation (15 of 20). Typed request models with filter operators eq, ne, gt, gte, lt, lte and in, and 422 on malformed ids (12 of 15). curl examples for add, flush and search, and typed error codes such as SESSION_BUSY and EXTERNAL_SERVICE_UNAVAILABLE (12 of 15). `/api/v2` with `/api/v1` kept as a legacy alias, a changelog and release notes (15). Total 89.",
          "b": "All nine tools take typed zod input schemas and declare output schemas, stated as JSON Schema 2020-12 since 2.0.0 (25). No llms.txt. The README is Markdown on GitHub with JSON examples (5). Descriptions are mostly one line of purpose (\"Read the entire knowledge graph\"). Since 1.0.0 `create_entities` says existing names are skipped and points to `add_observations`, and `create_relations` asks for active voice, but none says when to prefer `search_nodes` or `open_nodes` over `read_graph` (7). Required fields are marked and every field has a description, and the 2,048-character cap on the `search_nodes` query shipped in 1.0.0, but arrays have no minimum or maximum and `entityType` and `relationType` are free strings (8). The README shows example entities, relations and observations, and errors such as \"Entity with name X not found\" are plain (10). A per-package CHANGELOG.md with Major, Minor and Patch sections from 1.0.0, and dated release tags (15). 25+5+7+8+10+15 = 70."
        },
        "scores": {
          "a": 89,
          "b": 70
        }
      },
      {
        "by": 11,
        "category": "ergonomics",
        "leads": "everos",
        "name": "Agent ergonomics",
        "reasons": {
          "a": "Read for the API, with seven MCP tools on top. Searches take `top_k` and a method, and responses can be scoped by five ids (20 of 25). Filters nest with AND and OR, and `/get` pages results (18 of 20). Errors carry typed codes and say which are retryable (16 of 20). `add` is queued and returns 202, a busy session refuses deletion with nothing deleted, and the cloud purge needs a nonce confirmed within five minutes (12 of 20). A demo runs with no key and the minimal setup needs one OpenRouter key, with a Python library and the MCP server, one language (12 of 15). Total 78.",
          "b": "Nine tools with short descriptions, but the entity and relation schemas repeat in every output schema, so tools/list runs to about 10,700 characters or roughly 2,700 tokens by the 1 October count, with a `$schema` line on each schema since 2.0.0 (22). No pagination, limit or field selection anywhere. `read_graph` returns the whole graph and `search_nodes` returns every substring match (5). Since 1.0.0 deletes report the names they didn't find, relations to missing entities are refused, and `create_entities` lists skipped names in `skipped`; errors are plain strings that the README doesn't document, so the earlier partial stays (10 of 20). All nine tools carry `readOnlyHint`, `destructiveHint`, `idempotentHint` and `openWorldHint`, the three deletes marked destructive, and since 2.0.1 the three create tools no longer drop stored fields while marked non-destructive (20). At most one required parameter per tool. Node only, plus Docker (10). 22+5+10+20+10 = 67."
        },
        "scores": {
          "a": 78,
          "b": 67
        }
      },
      {
        "by": 8,
        "category": "security",
        "leads": "everos",
        "name": "Security \u0026 auth",
        "reasons": {
          "a": "Framework reading for software the owner runs. The local server has no authentication and no security scheme in the OpenAPI document, relying on a 127.0.0.1 bind by default (15 of 30). No read-only mode; the cloud purge is two-step (8 of 20). Memories are extracted from conversations and returned into prompts, and everos-mcp tells hosts to save facts unprompted, with no injection guidance found (4 of 15). Structured logs and lock metrics, no audit log (6 of 15). SECURITY.md with a reporting address, five-day acknowledgement, supported versions and a published-advisories section, plus a valid security.txt (14 of 20). Total 47.",
          "b": "No credentials, nothing to scope, so the middle band (20). No read-only mode. The three delete tools run without confirmation and annotations are the only signal a host gets. The file path is whatever `MEMORY_FILE_PATH` says (5). Everything stored comes back verbatim in later sessions, so an instruction an agent copied from a web page or document persists as memory. The README still has no guidance on this (2). No log of who changed what. Resource notifications say only that the graph changed (0). SECURITY.md was rewritten on 29 September 2026 and is on main since 1.0.0. It names this server in scope, takes private reports through GitHub, says fixes ship in the next release and publishes accepted advisories once a fixed release is out. modelcontextprotocol.io serves a security.txt with a contact and no Expires line. No bounty or certification. Graded as the sequential-thinking and filesystem servers and nanobot (12 of 20). OSV lists no advisory for the package on 4 November, and none of the GHSA-named branches merged in October touches this server. 20+5+2+0+12 = 39."
        },
        "scores": {
          "a": 47,
          "b": 39
        }
      },
      {
        "by": 5,
        "category": "maintenance",
        "leads": "everos",
        "name": "Maintenance \u0026 community",
        "reasons": {
          "a": "v1.5.1 on 22 October 2026 (30). Five tagged releases in 90 days and 12 PyPI uploads (20). Maintainer replies on some issues, others from outside users unanswered for weeks (12 of 25). Python library and the everos-mcp package, not in the official MCP registry (10 of 15). uv.lock, CI, docs and release workflows (8 of 10). Total 80.",
          "b": "Memory 2.0.1, released with the monorepo's v2.2.0 tag on 28 October 2026, 7 days before this check (30). Four releases of this package in the 90 days from 6 August, 2026.8.31 (31 August), 1.0.0 (tag v1.0.0, 10 October), 2.0.0 (tag v2.0.0, 19 October) and 2.0.1 (tag v2.2.0, 28 October), each with code changes; v2.1.0 (24 October) left it at 2.0.0 (package.json read at each tag). Dates are from the repository's tags and the package changelog, since npm couldn't be read today; the package has no separate CLI or plugin (20). Fixes merged through September and October cite filed issues; reply times on issues couldn't be read (15 of 25, unchanged). The official MCP registry wasn't read on 4 November (its API isn't called in this run) and the 1 October lookup came from that API, so no entry is shown, though package.json carries the mcpName io.github.modelcontextprotocol/server-memory (0). Current SDK (`@modelcontextprotocol/server` ^2.3.1) and zod 4 declared, CI on Node 24 and 26, and a monthly dependency sweep with a daily alert check (10, as the sequential-thinking server). 30+20+15+0+10 = 75."
        },
        "scores": {
          "a": 80,
          "b": 75
        }
      },
      {
        "by": 5,
        "category": "transparency",
        "leads": "memory-reference-server",
        "name": "Transparency \u0026 trust",
        "reasons": {
          "a": "Apache-2.0 with a NOTICE file (30). Local data stays in the owner's Markdown and indexes. For the cloud, the privacy policy gives no retention periods, the terms and privacy policy word the training exceptions differently, and the privacy contact link points to a miromind.ai address (12 of 30). The README marks `/api/v1` as a legacy alias that may be removed in a future major release, and a 1.0 migration guide exists, with no notice period (14 of 20). No outbound telemetry was found in the source, and the docs don't address it (10 of 20). Total 66.",
          "b": "MIT for older contributions and Apache-2.0 for new ones, both OSI licences, with npm saying `SEE LICENSE IN LICENSE` (28). Local software with no network calls. The README says where the graph is stored, and since 1.0.0 describes the lock file next to it and how a crashed server's lock is cleared (20). RELEASING.md's semver policy says what makes a major, and 1.0.0's changelog said on 10 October that it was the last release on the 1.x SDK. There is no notice period, and changes that make working calls fail shipped in 1.0.0 and 2.0.1 with word only on release day (10 of 20). No telemetry in the code (20). 28+20+10+20 = 78."
        },
        "scores": {
          "a": 71,
          "b": 76
        }
      }
    ],
    "facts": [
      {
        "a": "HTTP API",
        "b": "MCP server",
        "name": "Kind"
      },
      {
        "a": "Evermind AI, Inc.",
        "b": "MCP project (reference servers)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "HTTP, stdio",
        "b": "stdio",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Freemium",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "MIT and Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "7",
        "b": "9",
        "name": "Tools exposed"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "yes",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-10-22",
        "b": "2026-10-28",
        "name": "Last release"
      },
      {
        "a": "2026-01-20",
        "b": "2021-09-08",
        "name": "Terms last updated"
      },
      {
        "a": "2026-01-20",
        "b": "2023-03-15",
        "name": "Privacy policy last updated"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Customer content may train models"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict automated access"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "yes",
        "b": "not found in the text",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "not found in the text",
        "b": "not found in the text",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "14k stars, 4k PyPI/wk",
        "b": "90k stars, 136k npm/wk",
        "name": "Popularity"
      },
      {
        "a": "none",
        "b": "2.5/5 (2)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "EverOS scores 69.4 (B) on agent readiness against Memory (MCP reference server)'s 58.8 (C), and leads in 5 of 7 scored categories. Memory (MCP reference server) leads on payments \u0026 pricing and transparency \u0026 trust.",
        "question": "Which is better for AI agents, EverOS or Memory (MCP reference server)?"
      },
      {
        "answer": "Neither needs a key.",
        "question": "Do EverOS and Memory (MCP reference server) need an API key?"
      },
      {
        "answer": "EverOS runs on your own machine, with no hosted endpoint listed. Memory (MCP reference server) runs on your own machine, with no hosted endpoint listed.",
        "question": "Can an agent call EverOS and Memory (MCP reference server) without installing anything?"
      },
      {
        "answer": "Yes. EverOS is open source (Apache-2.0). Memory (MCP reference server) is open source (MIT and Apache-2.0).",
        "question": "Are EverOS and Memory (MCP reference server) open source?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Schema \u0026 documentation, 89 against 70",
          "Agent ergonomics, 78 against 67",
          "Security \u0026 auth, 47 against 39",
          "Maintenance \u0026 community, 80 against 75"
        ],
        "also": [
          "No incidents deducted, where Memory (MCP reference server) loses 6 points for them"
        ],
        "goodFor": "Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.",
        "slug": "everos",
        "watchFor": "The local HTTP server has no authentication and relies on binding to 127.0.0.1"
      },
      {
        "aheadOn": [
          "Payments \u0026 pricing, 60 against 40",
          "Transparency \u0026 trust, 76 against 71"
        ],
        "also": null,
        "goodFor": "A single local agent that wants a small, inspectable store of facts about people and projects.",
        "slug": "memory-reference-server",
        "watchFor": "No pagination or limits. `read_graph` returns everything and `search_nodes` every match"
      }
    ],
    "history": {
      "everos": null,
      "memory-reference-server": [
        {
          "causes": [
            "security",
            "product",
            "event"
          ],
          "date": "2026-11-04",
          "delta": 4.4,
          "from": 54.4,
          "fromGrade": "C",
          "to": 58.8,
          "toGrade": "C"
        },
        {
          "causes": [
            "evidence"
          ],
          "date": "2026-10-28",
          "delta": 0.1,
          "from": 54.3,
          "fromGrade": "C",
          "to": 54.4,
          "toGrade": "C"
        },
        {
          "causes": [
            "method"
          ],
          "date": "2026-10-27",
          "delta": 0.1,
          "from": 54.2,
          "fromGrade": "C",
          "to": 54.3,
          "toGrade": "C"
        }
      ]
    },
    "job": {
      "capability": "memory.store",
      "name": "Agent memory"
    },
    "others": [
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.json",
        "title": "Amazon Bedrock AgentCore Memory vs EverOS",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-everos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.json",
        "title": "Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/basic-memory-vs-everos.json",
        "title": "Basic Memory vs EverOS",
        "url": "https://www.anchorterminal.com/compare/basic-memory-vs-everos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/basic-memory-vs-memory-reference-server.json",
        "title": "Basic Memory vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/basic-memory-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/claude-mem-vs-everos.json",
        "title": "claude-mem vs EverOS",
        "url": "https://www.anchorterminal.com/compare/claude-mem-vs-everos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/claude-mem-vs-memory-reference-server.json",
        "title": "claude-mem vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/claude-mem-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-everos.json",
        "title": "Cognee vs EverOS",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-everos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/cognee-vs-memory-reference-server.json",
        "title": "Cognee vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/cognee-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.json",
        "title": "EverOS vs Agent Platform Memory Bank",
        "url": "https://www.anchorterminal.com/compare/everos-vs-google-memory-bank"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-graphicle.json",
        "title": "EverOS vs Graphicle",
        "url": "https://www.anchorterminal.com/compare/everos-vs-graphicle"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-graphiti.json",
        "title": "EverOS vs Graphiti",
        "url": "https://www.anchorterminal.com/compare/everos-vs-graphiti"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-hindsight.json",
        "title": "EverOS vs Hindsight",
        "url": "https://www.anchorterminal.com/compare/everos-vs-hindsight"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-honcho.json",
        "title": "EverOS vs Honcho",
        "url": "https://www.anchorterminal.com/compare/everos-vs-honcho"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-hy-memory.json",
        "title": "EverOS vs Hy Memory",
        "url": "https://www.anchorterminal.com/compare/everos-vs-hy-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-langmem.json",
        "title": "EverOS vs LangMem",
        "url": "https://www.anchorterminal.com/compare/everos-vs-langmem"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-localghost.json",
        "title": "EverOS vs LocalGhost",
        "url": "https://www.anchorterminal.com/compare/everos-vs-localghost"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-mem0.json",
        "title": "EverOS vs Mem0 Platform + MCP",
        "url": "https://www.anchorterminal.com/compare/everos-vs-mem0"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-memmachine.json",
        "title": "EverOS vs MemMachine",
        "url": "https://www.anchorterminal.com/compare/everos-vs-memmachine"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-memori.json",
        "title": "EverOS vs Memori",
        "url": "https://www.anchorterminal.com/compare/everos-vs-memori"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-mempalace.json",
        "title": "EverOS vs MemPalace",
        "url": "https://www.anchorterminal.com/compare/everos-vs-mempalace"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-past-dev.json",
        "title": "EverOS vs past.dev",
        "url": "https://www.anchorterminal.com/compare/everos-vs-past-dev"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-supermemory.json",
        "title": "EverOS vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/everos-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.json",
        "title": "EverOS vs TencentDB Agent Memory",
        "url": "https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-tokenrip.json",
        "title": "EverOS vs Tokenrip",
        "url": "https://www.anchorterminal.com/compare/everos-vs-tokenrip"
      },
      {
        "json": "https://www.anchorterminal.com/compare/everos-vs-zep.json",
        "title": "EverOS vs Zep",
        "url": "https://www.anchorterminal.com/compare/everos-vs-zep"
      },
      {
        "json": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server.json",
        "title": "Agent Platform Memory Bank vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.json",
        "title": "Graphiti vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hindsight-vs-memory-reference-server.json",
        "title": "Hindsight vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/hindsight-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.json",
        "title": "Honcho vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.json",
        "title": "Hy Memory vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.json",
        "title": "LangMem vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server.json",
        "title": "LocalGhost vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.json",
        "title": "Mem0 Platform + MCP vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.json",
        "title": "MemMachine vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memori-vs-memory-reference-server.json",
        "title": "Memori vs Memory (MCP reference server)",
        "url": "https://www.anchorterminal.com/compare/memori-vs-memory-reference-server"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-mempalace.json",
        "title": "Memory (MCP reference server) vs MemPalace",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-mempalace"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-past-dev.json",
        "title": "Memory (MCP reference server) vs past.dev",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-past-dev"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory.json",
        "title": "Memory (MCP reference server) vs Supermemory API + MCP",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-tencentdb-agent-memory.json",
        "title": "Memory (MCP reference server) vs TencentDB Agent Memory",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-tencentdb-agent-memory"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-tokenrip.json",
        "title": "Memory (MCP reference server) vs Tokenrip",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-tokenrip"
      },
      {
        "json": "https://www.anchorterminal.com/compare/memory-reference-server-vs-zep.json",
        "title": "Memory (MCP reference server) vs Zep",
        "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-zep"
      },
      {
        "json": "https://www.anchorterminal.com/compare/ai-memory-vs-everos.json",
        "title": "AI Memory vs EverOS",
        "url": "https://www.anchorterminal.com/compare/ai-memory-vs-everos"
      },
      {
        "json": "https://www.anchorterminal.com/compare/context-mode-vs-everos.json",
        "title": "Context Mode Engine vs EverOS",
        "url": "https://www.anchorterminal.com/compare/context-mode-vs-everos"
      }
    ],
    "panel": null,
    "scores": [
      {
        "by": 4,
        "edge": "everos",
        "everos": 79,
        "key": "reliability",
        "memory-reference-server": 75,
        "name": "Reliability",
        "weight": 16
      },
      {
        "key": "performance",
        "name": "Performance",
        "pending": true,
        "weight": 10
      },
      {
        "by": 19,
        "edge": "everos",
        "everos": 89,
        "key": "schema",
        "memory-reference-server": 70,
        "name": "Schema \u0026 documentation",
        "weight": 13
      },
      {
        "by": 11,
        "edge": "everos",
        "everos": 78,
        "key": "ergonomics",
        "memory-reference-server": 67,
        "name": "Agent ergonomics",
        "weight": 13
      },
      {
        "by": 8,
        "edge": "everos",
        "everos": 47,
        "key": "security",
        "memory-reference-server": 39,
        "name": "Security \u0026 auth",
        "weight": 14
      },
      {
        "by": 20,
        "edge": "memory-reference-server",
        "everos": 40,
        "key": "payments",
        "memory-reference-server": 60,
        "name": "Payments \u0026 pricing",
        "weight": 10
      },
      {
        "key": "tasks",
        "name": "Task success",
        "pending": true,
        "weight": 10
      },
      {
        "by": 5,
        "edge": "everos",
        "everos": 80,
        "key": "maintenance",
        "memory-reference-server": 75,
        "name": "Maintenance \u0026 community",
        "weight": 7
      },
      {
        "by": 5,
        "edge": "memory-reference-server",
        "everos": 71,
        "key": "transparency",
        "memory-reference-server": 76,
        "name": "Transparency \u0026 trust",
        "weight": 7
      }
    ],
    "summary": "EverOS scores 69.4 (B) on agent readiness against Memory (MCP reference server)'s 58.8 (C), and leads in 5 of 7 scored categories. Memory (MCP reference server) leads on payments \u0026 pricing and transparency \u0026 trust. Both do agent memory.",
    "tasks": null,
    "tutorials": [],
    "verdicts": {
      "everos": "EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.",
      "memory-reference-server": "Nine tools with typed schemas and accurate read, destructive and idempotent annotations, and since 1.0.0 a lock file keeps two processes from losing each other's writes. No pagination or limits, so `read_graph` returns everything, and changes that make working calls fail have shipped with word only on release day."
    }
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  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server",
    "json": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.md",
    "mcp": "https://www.anchorterminal.com/mcp",
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  "markdown": "EverOS scores 69.4 (B) on agent readiness against Memory (MCP reference server)'s 58.8 (C), and leads in 5 of 7 scored categories. Memory (MCP reference server) leads on payments \u0026 pricing and transparency \u0026 trust. Both do agent memory.\n\n- EverOS: grade B, 69.4/100, rank #246 of 1486. Markdown https://www.anchorterminal.com/tools/everos.md · JSON https://www.anchorterminal.com/api/v1/tools/everos.json\n- Memory (MCP reference server): grade C, 58.8/100, rank #724 of 1486. Markdown https://www.anchorterminal.com/tools/memory-reference-server.md · JSON https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 353 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n- Best database, file and memory tools for AI agents: https://www.anchorterminal.com/best/data/index.md\n- All 97 databases comparisons: https://www.anchorterminal.com/compare/data/index.md\n\n## Which one, for what\n\n### EverOS (B)\n\nGood for: Self-hosted memory for agents and apps that want Markdown as the source of truth and separate user and agent tracks.\n\nAhead on:\n- Schema \u0026 documentation, 89 against 70\n- Agent ergonomics, 78 against 67\n- Security \u0026 auth, 47 against 39\n- Maintenance \u0026 community, 80 against 75\n\nAlso in its favour:\n- No incidents deducted, where Memory (MCP reference server) loses 6 points for them\n\nWatch for: The local HTTP server has no authentication and relies on binding to 127.0.0.1\n\n### Memory (MCP reference server) (C)\n\nGood for: A single local agent that wants a small, inspectable store of facts about people and projects.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 40\n- Transparency \u0026 trust, 76 against 71\n\nWatch for: No pagination or limits. `read_graph` returns everything and `search_nodes` every match\n\n\n## Why the edge\n\n### Payments \u0026 pricing: Memory (MCP reference server) +20\n\n- EverOS (40): Self-hosted rule, with the price lines read for EverOS Cloud. No x402, MPP or L402 (0 of 40). No cloud price or plan found on evermind.ai, its FAQ, terms or docs (0). The open-source runtime is free with no card (20). An agent can install it from PyPI and run it with no account (20). Total 40.\n- Memory (MCP reference server) (60): Free, self-hosted, nothing to buy, so 20 + 20 + 20. No payment protocol (0).\n\n### Schema \u0026 documentation: EverOS +19\n\n- EverOS (89): OpenAPI document in the repository with 40 operations, every one with a description (25). llms.txt and llms-full.txt on docs.evermind.ai (10). Operation descriptions state purpose; when-not-to-use guidance appears in the docs, such as flush after add, rather than per operation (15 of 20). Typed request models with filter operators eq, ne, gt, gte, lt, lte and in, and 422 on malformed ids (12 of 15). curl examples for add, flush and search, and typed error codes such as SESSION_BUSY and EXTERNAL_SERVICE_UNAVAILABLE (12 of 15). `/api/v2` with `/api/v1` kept as a legacy alias, a changelog and release notes (15). Total 89.\n- Memory (MCP reference server) (70): All nine tools take typed zod input schemas and declare output schemas, stated as JSON Schema 2020-12 since 2.0.0 (25). No llms.txt. The README is Markdown on GitHub with JSON examples (5). Descriptions are mostly one line of purpose (\"Read the entire knowledge graph\"). Since 1.0.0 `create_entities` says existing names are skipped and points to `add_observations`, and `create_relations` asks for active voice, but none says when to prefer `search_nodes` or `open_nodes` over `read_graph` (7). Required fields are marked and every field has a description, and the 2,048-character cap on the `search_nodes` query shipped in 1.0.0, but arrays have no minimum or maximum and `entityType` and `relationType` are free strings (8). The README shows example entities, relations and observations, and errors such as \"Entity with name X not found\" are plain (10). A per-package CHANGELOG.md with Major, Minor and Patch sections from 1.0.0, and dated release tags (15). 25+5+7+8+10+15 = 70.\n\n### Agent ergonomics: EverOS +11\n\n- EverOS (78): Read for the API, with seven MCP tools on top. Searches take `top_k` and a method, and responses can be scoped by five ids (20 of 25). Filters nest with AND and OR, and `/get` pages results (18 of 20). Errors carry typed codes and say which are retryable (16 of 20). `add` is queued and returns 202, a busy session refuses deletion with nothing deleted, and the cloud purge needs a nonce confirmed within five minutes (12 of 20). A demo runs with no key and the minimal setup needs one OpenRouter key, with a Python library and the MCP server, one language (12 of 15). Total 78.\n- Memory (MCP reference server) (67): Nine tools with short descriptions, but the entity and relation schemas repeat in every output schema, so tools/list runs to about 10,700 characters or roughly 2,700 tokens by the 1 October count, with a `$schema` line on each schema since 2.0.0 (22). No pagination, limit or field selection anywhere. `read_graph` returns the whole graph and `search_nodes` returns every substring match (5). Since 1.0.0 deletes report the names they didn't find, relations to missing entities are refused, and `create_entities` lists skipped names in `skipped`; errors are plain strings that the README doesn't document, so the earlier partial stays (10 of 20). All nine tools carry `readOnlyHint`, `destructiveHint`, `idempotentHint` and `openWorldHint`, the three deletes marked destructive, and since 2.0.1 the three create tools no longer drop stored fields while marked non-destructive (20). At most one required parameter per tool. Node only, plus Docker (10). 22+5+10+20+10 = 67.\n\n### Security \u0026 auth: EverOS +8\n\n- EverOS (47): Framework reading for software the owner runs. The local server has no authentication and no security scheme in the OpenAPI document, relying on a 127.0.0.1 bind by default (15 of 30). No read-only mode; the cloud purge is two-step (8 of 20). Memories are extracted from conversations and returned into prompts, and everos-mcp tells hosts to save facts unprompted, with no injection guidance found (4 of 15). Structured logs and lock metrics, no audit log (6 of 15). SECURITY.md with a reporting address, five-day acknowledgement, supported versions and a published-advisories section, plus a valid security.txt (14 of 20). Total 47.\n- Memory (MCP reference server) (39): No credentials, nothing to scope, so the middle band (20). No read-only mode. The three delete tools run without confirmation and annotations are the only signal a host gets. The file path is whatever `MEMORY_FILE_PATH` says (5). Everything stored comes back verbatim in later sessions, so an instruction an agent copied from a web page or document persists as memory. The README still has no guidance on this (2). No log of who changed what. Resource notifications say only that the graph changed (0). SECURITY.md was rewritten on 29 September 2026 and is on main since 1.0.0. It names this server in scope, takes private reports through GitHub, says fixes ship in the next release and publishes accepted advisories once a fixed release is out. modelcontextprotocol.io serves a security.txt with a contact and no Expires line. No bounty or certification. Graded as the sequential-thinking and filesystem servers and nanobot (12 of 20). OSV lists no advisory for the package on 4 November, and none of the GHSA-named branches merged in October touches this server. 20+5+2+0+12 = 39.\n\n### Maintenance \u0026 community: EverOS +5\n\n- EverOS (80): v1.5.1 on 22 October 2026 (30). Five tagged releases in 90 days and 12 PyPI uploads (20). Maintainer replies on some issues, others from outside users unanswered for weeks (12 of 25). Python library and the everos-mcp package, not in the official MCP registry (10 of 15). uv.lock, CI, docs and release workflows (8 of 10). Total 80.\n- Memory (MCP reference server) (75): Memory 2.0.1, released with the monorepo's v2.2.0 tag on 28 October 2026, 7 days before this check (30). Four releases of this package in the 90 days from 6 August, 2026.8.31 (31 August), 1.0.0 (tag v1.0.0, 10 October), 2.0.0 (tag v2.0.0, 19 October) and 2.0.1 (tag v2.2.0, 28 October), each with code changes; v2.1.0 (24 October) left it at 2.0.0 (package.json read at each tag). Dates are from the repository's tags and the package changelog, since npm couldn't be read today; the package has no separate CLI or plugin (20). Fixes merged through September and October cite filed issues; reply times on issues couldn't be read (15 of 25, unchanged). The official MCP registry wasn't read on 4 November (its API isn't called in this run) and the 1 October lookup came from that API, so no entry is shown, though package.json carries the mcpName io.github.modelcontextprotocol/server-memory (0). Current SDK (`@modelcontextprotocol/server` ^2.3.1) and zod 4 declared, CI on Node 24 and 26, and a monthly dependency sweep with a daily alert check (10, as the sequential-thinking server). 30+20+15+0+10 = 75.\n\n### Transparency \u0026 trust: Memory (MCP reference server) +5\n\n- EverOS (71): Apache-2.0 with a NOTICE file (30). Local data stays in the owner's Markdown and indexes. For the cloud, the privacy policy gives no retention periods, the terms and privacy policy word the training exceptions differently, and the privacy contact link points to a miromind.ai address (12 of 30). The README marks `/api/v1` as a legacy alias that may be removed in a future major release, and a 1.0 migration guide exists, with no notice period (14 of 20). No outbound telemetry was found in the source, and the docs don't address it (10 of 20). Total 66.\n- Memory (MCP reference server) (76): MIT for older contributions and Apache-2.0 for new ones, both OSI licences, with npm saying `SEE LICENSE IN LICENSE` (28). Local software with no network calls. The README says where the graph is stored, and since 1.0.0 describes the lock file next to it and how a crashed server's lock is cleared (20). RELEASING.md's semver policy says what makes a major, and 1.0.0's changelog said on 10 October that it was the last release on the 1.x SDK. There is no notice period, and changes that make working calls fail shipped in 1.0.0 and 2.0.1 with word only on release day (10 of 20). No telemetry in the code (20). 28+20+10+20 = 78.\n\n## Score by category\n\n| Category | Weight | EverOS | Memory (MCP reference server) | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 79 | 75 | EverOS +4 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 89 | 70 | EverOS +19 |\n| Agent ergonomics | 13% (16.2 this run) | 78 | 67 | EverOS +11 |\n| Security \u0026 auth | 14% (17.5 this run) | 47 | 39 | EverOS +8 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 60 | Memory (MCP reference server) +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 75 | EverOS +5 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 76 | Memory (MCP reference server) +5 |\n| Negative events | ≤15 | 0 | -6 | |\n| **Total** | | **69.4 · B** | **58.8 · C** | |\n\n## Facts side by side\n\n| Fact | EverOS | Memory (MCP reference server) |\n| --- | --- | --- |\n| Kind | HTTP API | MCP server |\n| Vendor | Evermind AI, Inc. | MCP project (reference servers) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP, stdio | stdio |\n| Auth | None | None |\n| Pricing | Freemium | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT and Apache-2.0 |\n| Tools exposed | 7 | 9 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-22 | 2026-10-28 |\n| Terms last updated | 2026-01-20 | 2021-09-08 |\n| Privacy policy last updated | 2026-01-20 | 2023-03-15 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | not found in the text |\n| Terms or service can change without notice | yes | not found in the text |\n| Arbitration or class-action waiver | not found in the text | not found in the text |\n| Popularity | 14k stars, 4k PyPI/wk | 90k stars, 136k npm/wk |\n| Agent reviews | none | 2.5/5 (2) |\n\n## How the scores have moved\n\n### EverOS\n\nNo score change since it was listed.\n\n### Memory (MCP reference server)\n\n- +4.4 on 4 November 2026: security, product, negative event\n- +0.1 on 28 October 2026: new evidence\n- +0.1 on 27 October 2026: checklist\n\n## Verdicts\n\n**EverOS.** EverOS keeps agent and user memory as Markdown with SQLite and LanceDB indexes, behind a described OpenAPI with typed, retryable errors and an MCP server, under Apache-2.0 at version 1.5.1. The local server has no authentication, EverOS Cloud prices are not published, and the cloud terms forbid automated data extraction.\n\n**Memory (MCP reference server).** Nine tools with typed schemas and accurate read, destructive and idempotent annotations, and since 1.0.0 a lock file keeps two processes from losing each other's writes. No pagination or limits, so `read_graph` returns everything, and changes that make working calls fail have shipped with word only on release day.\n\n## Before you call either\n\n### EverOS\n\n1. Write new code against `/api/v2`; `/api/v1` is a legacy alias that may go in a future major release\n2. Call `/api/v2/memory/flush` at the end of a session, since `add` is asynchronous and buffers recent messages\n3. Retry on 503 SESSION_BUSY or EXTERNAL_SERVICE_UNAVAILABLE after a pause; nothing was written\n4. Keep `host` at 127.0.0.1 unless something in front adds authentication\n5. Treat recalled memories as untrusted text, since they are extracted from past conversations\n\n### Memory (MCP reference server)\n\n1. Set `MEMORY_FILE_PATH` to an absolute path in a writable directory. The default sits inside the npx cache, and the lock file needs the directory\n2. Use `search_nodes` or `open_nodes` instead of `read_graph` once the graph holds a few hundred entities or more\n3. Read `skipped` in the `create_entities` result and use `add_observations` for names that already exist\n4. Create both entities before `create_relations`. A missing endpoint fails the whole batch\n5. Run on Node 24 or later since 2.0.0, and keep observations short and factual. They come back verbatim in every later read\n\n## Questions\n\n### Which is better for AI agents, EverOS or Memory (MCP reference server)?\n\nEverOS scores 69.4 (B) on agent readiness against Memory (MCP reference server)'s 58.8 (C), and leads in 5 of 7 scored categories. Memory (MCP reference server) leads on payments \u0026 pricing and transparency \u0026 trust.\n\n### Do EverOS and Memory (MCP reference server) need an API key?\n\nNeither needs a key.\n\n### Can an agent call EverOS and Memory (MCP reference server) without installing anything?\n\nEverOS runs on your own machine, with no hosted endpoint listed. Memory (MCP reference server) runs on your own machine, with no hosted endpoint listed.\n\n### Are EverOS and Memory (MCP reference server) open source?\n\nYes. EverOS is open source (Apache-2.0). Memory (MCP reference server) is open source (MIT and Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.json, and with the fewest tokens: https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"everos\", \"b\": \"memory-reference-server\"}`. From a terminal: `anchor compare everos memory-reference-server`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/everos.json and https://www.anchorterminal.com/api/v1/tools/memory-reference-server.json\n\n## Other comparisons with EverOS or Memory (MCP reference server)\n\n- [Amazon Bedrock AgentCore Memory vs EverOS](https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.md)\n- [Amazon Bedrock AgentCore Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/agentcore-memory-vs-memory-reference-server.md)\n- [Basic Memory vs EverOS](https://www.anchorterminal.com/compare/basic-memory-vs-everos.md)\n- [Basic Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/basic-memory-vs-memory-reference-server.md)\n- [claude-mem vs EverOS](https://www.anchorterminal.com/compare/claude-mem-vs-everos.md)\n- [claude-mem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/claude-mem-vs-memory-reference-server.md)\n- [Cognee vs EverOS](https://www.anchorterminal.com/compare/cognee-vs-everos.md)\n- [Cognee vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/cognee-vs-memory-reference-server.md)\n- [EverOS vs Agent Platform Memory Bank](https://www.anchorterminal.com/compare/everos-vs-google-memory-bank.md)\n- [EverOS vs Graphicle](https://www.anchorterminal.com/compare/everos-vs-graphicle.md)\n- [EverOS vs Graphiti](https://www.anchorterminal.com/compare/everos-vs-graphiti.md)\n- [EverOS vs Hindsight](https://www.anchorterminal.com/compare/everos-vs-hindsight.md)\n- [EverOS vs Honcho](https://www.anchorterminal.com/compare/everos-vs-honcho.md)\n- [EverOS vs Hy Memory](https://www.anchorterminal.com/compare/everos-vs-hy-memory.md)\n- [EverOS vs LangMem](https://www.anchorterminal.com/compare/everos-vs-langmem.md)\n- [EverOS vs LocalGhost](https://www.anchorterminal.com/compare/everos-vs-localghost.md)\n- [EverOS vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/everos-vs-mem0.md)\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)\n- [EverOS vs Memori](https://www.anchorterminal.com/compare/everos-vs-memori.md)\n- [EverOS vs MemPalace](https://www.anchorterminal.com/compare/everos-vs-mempalace.md)\n- [EverOS vs past.dev](https://www.anchorterminal.com/compare/everos-vs-past-dev.md)\n- [EverOS vs Supermemory API + MCP](https://www.anchorterminal.com/compare/everos-vs-supermemory.md)\n- [EverOS vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.md)\n- [EverOS vs Tokenrip](https://www.anchorterminal.com/compare/everos-vs-tokenrip.md)\n- [EverOS vs Zep](https://www.anchorterminal.com/compare/everos-vs-zep.md)\n- [Agent Platform Memory Bank vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/google-memory-bank-vs-memory-reference-server.md)\n- [Graphiti vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/graphiti-vs-memory-reference-server.md)\n- [Hindsight vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/hindsight-vs-memory-reference-server.md)\n- [Honcho vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/honcho-vs-memory-reference-server.md)\n- [Hy Memory vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/hy-memory-vs-memory-reference-server.md)\n- [LangMem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.md)\n- [LocalGhost vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/localghost-vs-memory-reference-server.md)\n- [Mem0 Platform + MCP vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/mem0-vs-memory-reference-server.md)\n- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md)\n- [Memori vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memori-vs-memory-reference-server.md)\n- [Memory (MCP reference server) vs MemPalace](https://www.anchorterminal.com/compare/memory-reference-server-vs-mempalace.md)\n- [Memory (MCP reference server) vs past.dev](https://www.anchorterminal.com/compare/memory-reference-server-vs-past-dev.md)\n- [Memory (MCP reference server) vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memory-reference-server-vs-supermemory.md)\n- [Memory (MCP reference server) vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memory-reference-server-vs-tencentdb-agent-memory.md)\n- [Memory (MCP reference server) vs Tokenrip](https://www.anchorterminal.com/compare/memory-reference-server-vs-tokenrip.md)\n- [Memory (MCP reference server) vs Zep](https://www.anchorterminal.com/compare/memory-reference-server-vs-zep.md)\n- [AI Memory vs EverOS](https://www.anchorterminal.com/compare/ai-memory-vs-everos.md)\n- [Context Mode Engine vs EverOS](https://www.anchorterminal.com/compare/context-mode-vs-everos.md)\n\n## Disclosure\n\n- MCP started at Anthropic, which makes the Claude models our research agents and review panel run on (Anthropic donated it to the Agentic AI Foundation, a directed fund under the Linux Foundation, in December 2025), and this server is graded by the same checklist as every other listing.\n",
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