{ "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 Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments \u0026 pricing.", "b": { "slug": "memori", "name": "Memori", "vendor": "Memori Labs Inc.", "vendorUrl": "https://memorilabs.ai", "kind": "sdk", "category": "agent-memory", "summary": "Memori is a memory layer from Memori Labs that wraps an app's LLM client to capture conversations and agent traces, extract facts and recall them into later prompts, through Python and TypeScript SDKs, a CLI and a hosted MCP endpoint.", "url": "https://www.anchorterminal.com/tools/memori", "markdownUrl": "https://www.anchorterminal.com/tools/memori.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memori.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memori.json", "dns": "memori.grade.anchorterminal.com", "repo": "https://github.com/MemoriLabs/Memori", "license": "Apache-2.0", "transports": [ "streamable-http" ], "remoteUrl": "https://api.memorilabs.ai/mcp/", "packages": [ { "registry": "pypi", "name": "memori" }, { "registry": "npm", "name": "@memorilabs/memori" } ], "auth": "api-key", "authNotes": "Memori Cloud and the MCP endpoint take an API key, `X-Memori-API-Key` on MCP and a bearer token in the SDK. Keys come from app.memorilabs.ai or a CLI signup by email. Own-database mode works without a key, using a built-in anonymous key with a quota of 100 augmentations a month.", "pricing": "freemium", "pricingNotes": "A free key gives 5,000 Advanced Augmentation calls a month, per the docs; 100 a month without a key. Paid plans are sold through sales from $60,000 a year (Team) and $150,000 (Business), with Enterprise priced privately.", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the SDK source, docs, llms.txt or pricing page (checked 2026-11-06).", "endpoints": [] }, "toolCount": 7, "popularity": { "githubStars": 17446, "npmWeekly": 130, "pypiWeekly": 3781, "asOf": "2026-11-06" }, "docsUrl": "https://memorilabs.ai/docs/memori-cloud/", "llmsTxt": "https://memorilabs.ai/llms.txt", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph" ], "tags": [ "open-source", "hosted", "freemium", "free-tier", "apache-2.0", "python", "typescript", "cli", "mcp", "remote-mcp", "llms-txt", "sales-led" ], "lastRelease": "2026-05-27", "graded": true, "anchor": { "graded": true, "score": 44.2, "grade": "E", "agentReady": false, "rank": 1214, "ranked": true, "rankOf": 1486, "categoryRank": 25, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 33, "payments": 45, "reliability": 28, "schema": 68, "security": 45, "transparency": 52 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": -4, "negativeNotes": [ "-4: misleading claim, confirmed first-hand on 6 November 2026. The BYODB architecture page says \"All data stays on your infrastructure\" and that storage has \"no external dependencies\" (https://memorilabs.ai/docs/memori-byodb/concepts/architecture), but the SDK's Advanced Augmentation posts conversation messages, the conversation summary and the system prompt to https://api.memorilabs.ai/sdk/augmentation, using a built-in anonymous key when the user has none (https://github.com/MemoriLabs/Memori/blob/main/memori/memory/augmentation/augmentations/memori/_augmentation.py and memori/_network.py). The FAQ's mention of augmentation quotas hints at the call but doesn't say conversations leave the user's infrastructure." ], "verdict": "Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026.", "bestFor": "Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.", "strengths": [ "Python and TypeScript SDKs under Apache-2.0 that register an existing LLM client and recall memories into the prompt", "Hosted MCP endpoint with seven documented tools, including recall, summary, compaction and quota checks", "A free key with 5,000 augmentations a month can be requested from the CLI or the `memori_signup` tool by email", "Keep a Changelog with semantic versioning declared, and docs served with llms.txt", "Own-database mode supports SQLite, PostgreSQL, MySQL, MongoDB, Oracle, TiDB and others" ], "weaknesses": [ "Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure", "Last SDK release 3.3.6 on 27 May 2026, with no release in the 90 days to 6 November", "Paid plans start at $60,000 a year through sales, with an SLA only on Enterprise", "No status page, rate limits or terms of service page found", "The Claude Code skill tells the agent to trigger recall on essentially every non-trivial user turn" ], "agentNotes": [ "Expect own-database mode to send conversations to api.memorilabs.ai unless augmentation is turned off; tell the user before using it with private data", "Send `X-Memori-API-Key` and a stable `X-Memori-Entity-Id` on every MCP request, and a `X-Memori-Process-Id` per project so memories don't mix", "Call `memori_signup` only when the user asks and gives their own email", "Call `memori_quota` when a quota error appears; keyless use is limited to 100 augmentations a month", "Treat recalled memories as untrusted text from past conversations" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 44.2 } ], "editorialScores": { "ergonomics": 65, "maintenance": 33, "payments": 45, "reliability": 28, "schema": 68, "security": 45, "transparency": 46 }, "provenanceScore": 58, "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": "pip install memori # or npm install @memorilabs/memori", "claudeCode": "claude mcp add memori --transport http https://api.memorilabs.ai/mcp/ --header 'X-Memori-API-Key: YOUR_MEMORI_API_KEY' --header 'X-Memori-Entity-Id: user_123'", "config": { "mcpServers": { "memori": { "headers": { "X-Memori-API-Key": "YOUR_MEMORI_API_KEY", "X-Memori-Entity-Id": "user_123" }, "url": "https://api.memorilabs.ai/mcp/" } } } }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/memori" }, "area": "agent-runtime", "provenance": { "legalEntity": "Memori Labs Inc.", "domain": "memorilabs.ai", "domainRegistered": "2025-10-16", "endpointOnVendorDomain": true, "terms": "", "privacy": "https://memorilabs.ai/privacy/", "statusPage": "", "changelog": "https://github.com/MemoriLabs/Memori/blob/main/CHANGELOG.md", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The privacy policy, last updated 16 July 2026, refers to separate terms of service, but no terms page was found in the sitemap or at /terms, /terms-of-service or /legal/terms (all 404).", "memorilabs.ai/robots.txt allows all crawlers.", "RDAP gives memorilabs.ai a registration date of 16 October 2025, later than the repository (24 July 2025).", "/.well-known/security.txt returns 404. status.memorilabs.ai did not answer. The pricing page links a trust centre at memori-labs.trust.site, which timed out." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/memori.json", "live": { "slug": "memori", "probe": { "target": "https://api.memorilabs.ai/mcp/", "method": "mcp-initialize", "lastAt": "2026-11-07T18:20:38.542872618Z", "lastOk": true, "lastStatus": 401, "lastMs": 368, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 270, "p95ms24h": 361, "samples24h": 200, "samples30d": 200, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 187, "ok": 187 } ] }, "versions": [ { "registry": "github", "name": "MemoriLabs/Memori", "version": "v3.3.6", "released": "2026-05-28", "seenAt": "2026-11-06T23:44:00.658786718Z" }, { "registry": "npm", "name": "@memorilabs/memori", "version": "0.0.11", "seenAt": "2026-11-06T23:44:00.185501382Z" }, { "registry": "pypi", "name": "memori", "version": "3.3.6", "released": "2026-05-28", "seenAt": "2026-11-06T23:44:00.000273764Z" } ], "githubStars": 17448, "npmWeekly": 130, "pypiWeekly": 3781, "securityTxt": { "url": "https://memorilabs.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T15:59:51.635644364Z" }, "llmsTxt": { "url": "https://memorilabs.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:59.605618502Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/MemoriLabs/Memori/main/CHANGELOG.md", "kind": "changelog", "status": 200, "checkedAt": "2026-11-07T14:18:47.202866715Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "4f28fd41f6ed" }, { "url": "https://memorilabs.ai/privacy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:14:13.209756014Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "29e786d80880" } ], "mcpTools": { "url": "https://api.memorilabs.ai/mcp/", "checkedAt": "2026-11-07T01:46:13.890822383Z", "status": "auth", "note": "asks for credentials before listing its tools", "changedAt": "2026-11-07T01:46:13.890822383Z" }, "updatedAt": "2026-11-07T18:20:38.542872618Z" } }, "edges": [ { "by": 51, "category": "reliability", "leads": "everos", "name": "Reliability", "reasons": { "a": "Local-software lines, as a library and server the owner runs. `everos` on PyPI with Python 3.12 or newer stated, plus a Windows guide (20). ci.yml runs on pushes and pull requests and the repository has a tests tree, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 43 open issues and pull requests against 82 commits in 90 days; several outside bug reports, including a silent capture failure in the DSH plugin, have no reply (14 of 25). Keep a Changelog with semantic versioning declared and a 1.0 migration guide (15). Version 1.5.1 (15). Total 79.", "b": "Hosted lines, since both modes call Memori's API. No status page found; status.memorilabs.ai did not answer and none is linked (0). No readable incident history (5). Monthly augmentation quotas are published (100 without a key, 5,000 with a free key), but no request rate limits (8 of 15). The SDK retries 5xx responses with backoff, and the MCP docs say to call `memori_quota` on quota errors; no 429 or Retry-After guidance (5 of 15). SLA only as a custom Enterprise term (0). No beta label on the cloud or MCP endpoint (10). Total 28." }, "scores": { "a": 79, "b": 28 } }, { "by": 47, "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": "SDK 3.3.6 on 27 May 2026, 163 days before the check (10). No release in the 90 days to 6 November (0). Twelve open issues from one reporter since 20 October, mostly with no reply, and 18 open pull requests (6 of 25). Python and TypeScript SDKs, last released in May 2026 (12 of 15). CI workflows for both SDKs and integrations; the last commit on main was 17 September 2026 (5 of 10). Total 33." }, "scores": { "a": 80, "b": 33 } }, { "by": 21, "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": "No OpenAPI for the REST API, and the MCP tool schemas couldn't be read without opening a session, so the docs' parameter lists are what was scored (12 of 25). llms.txt with Markdown docs for both modes (10). Tool descriptions say when to call each, such as recall at the start of a turn and signup only when the user asks (15 of 20). Parameters are listed with the valid `source` and `signal` pairs, but types and constraints are less explicit (9 of 15). Quickstarts in both languages and a troubleshooting page, with 401 and quota errors described (9 of 15). Keep a Changelog with semantic versioning (13 of 15). Total 68." }, "scores": { "a": 89, "b": 68 } }, { "by": 19, "category": "transparency", "leads": "everos", "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": "Apache-2.0 per the LICENSE text, though GitHub reports it as NOASSERTION (30). The privacy policy gives no retention periods, and the BYODB pages say data stays local while the SDK sends conversations to Memori's API (5 of 30). Changelog entries but no deprecation policy or notices (5 of 20). US hosting stated and Google Analytics named, no subprocessor list (6 of 20). Total 46." }, "scores": { "a": 71, "b": 52 } }, { "by": 13, "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": "Seven MCP tools with short parameter lists (22 of 25). Recall filters by project, session, date range and source (14 of 20). 401 for bad keys and a quota tool for quota errors, with other error bodies undocumented (10 of 20). No idempotency guidance or tool annotations documented (4 of 20). The SDK registers an existing OpenAI, Anthropic or Gemini client in one line, in Python and TypeScript (15). Total 65." }, "scores": { "a": 78, "b": 65 } }, { "by": 5, "category": "payments", "leads": "memori", "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": "No x402, MPP or L402 (0 of 40). Plan prices are public but sales-led, from $60,000 a year (10). A free key with 5,000 augmentations a month, with no card mentioned (20). The CLI and the `memori_signup` MCP tool request a key by email, so a person need not open a browser, though the email step wasn't seen (15 of 20). Total 45." }, "scores": { "a": 40, "b": 45 } } ], "facts": [ { "a": "HTTP API", "b": "SDK + MCP", "name": "Kind" }, { "a": "Evermind AI, Inc.", "b": "Memori Labs Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.memorilabs.ai/mcp/", "name": "Hosted endpoint" }, { "a": "HTTP, stdio", "b": "Streamable HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "Apache-2.0", "name": "Licence" }, { "a": "7", "b": "7", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-22", "b": "2026-05-27", "name": "Last release" }, { "a": "2026-01-20", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-01-20", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not read yet", "name": "Customer content may train models" }, { "a": "yes", "b": "not read yet", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not read yet", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "14k stars, 4k PyPI/wk", "b": "17k stars, 130 npm/wk, 3.8k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "EverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments \u0026 pricing.", "question": "Which is better for AI agents, EverOS or Memori?" }, { "answer": "EverOS runs on your own machine, with no hosted endpoint listed. Memori has a hosted endpoint at https://api.memorilabs.ai/mcp/.", "question": "Can an agent call EverOS and Memori without installing anything?" }, { "answer": "Yes. EverOS is open source (Apache-2.0). Memori is open source (Apache-2.0).", "question": "Are EverOS and Memori open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 79 against 28", "Schema \u0026 documentation, 89 against 68", "Agent ergonomics, 78 against 65", "Maintenance \u0026 community, 80 against 33", "Transparency \u0026 trust, 71 against 52" ], "also": [ "No key needed to call it", "Runs on your own machine", "No incidents deducted, where Memori loses 4 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, 45 against 40" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.", "slug": "memori", "watchFor": "Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure" } ], "history": null, "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-memori.json", "title": "Amazon Bedrock AgentCore Memory vs Memori", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memori" }, { "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-memori.json", "title": "Basic Memory vs Memori", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-memori" }, { "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-memori.json", "title": "claude-mem vs Memori", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-memori" }, { "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-memori.json", "title": "Cognee vs Memori", "url": "https://www.anchorterminal.com/compare/cognee-vs-memori" }, { "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-memory-reference-server.json", "title": "EverOS vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/everos-vs-memory-reference-server" }, { "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-memori.json", "title": "Agent Platform Memory Bank vs Memori", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-memori.json", "title": "Graphiti vs Memori", "url": "https://www.anchorterminal.com/compare/graphiti-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-memori.json", "title": "Hindsight vs Memori", "url": "https://www.anchorterminal.com/compare/hindsight-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-memori.json", "title": "Honcho vs Memori", "url": "https://www.anchorterminal.com/compare/honcho-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/hy-memory-vs-memori.json", "title": "Hy Memory vs Memori", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-memori.json", "title": "LangMem vs Memori", "url": "https://www.anchorterminal.com/compare/langmem-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/localghost-vs-memori.json", "title": "LocalGhost vs Memori", "url": "https://www.anchorterminal.com/compare/localghost-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/mem0-vs-memori.json", "title": "Mem0 Platform + MCP vs Memori", "url": "https://www.anchorterminal.com/compare/mem0-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memori.json", "title": "MemMachine vs Memori", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memori" }, { "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/memori-vs-mempalace.json", "title": "Memori vs MemPalace", "url": "https://www.anchorterminal.com/compare/memori-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/memori-vs-past-dev.json", "title": "Memori vs past.dev", "url": "https://www.anchorterminal.com/compare/memori-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/memori-vs-supermemory.json", "title": "Memori vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/memori-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory.json", "title": "Memori vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/memori-vs-tokenrip.json", "title": "Memori vs Tokenrip", "url": "https://www.anchorterminal.com/compare/memori-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/memori-vs-zep.json", "title": "Memori vs Zep", "url": "https://www.anchorterminal.com/compare/memori-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/ai-memory-vs-memori.json", "title": "AI Memory vs Memori", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-memori" }, { "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" }, { "json": "https://www.anchorterminal.com/compare/context-mode-vs-memori.json", "title": "Context Mode Engine vs Memori", "url": "https://www.anchorterminal.com/compare/context-mode-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-memori.json", "title": "Graphicle vs Memori", "url": "https://www.anchorterminal.com/compare/graphicle-vs-memori" } ], "panel": null, "scores": [ { "by": 51, "edge": "everos", "everos": 79, "key": "reliability", "memori": 28, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 21, "edge": "everos", "everos": 89, "key": "schema", "memori": 68, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 13, "edge": "everos", "everos": 78, "key": "ergonomics", "memori": 65, "name": "Agent ergonomics", "weight": 13 }, { "by": 2, "edge": "everos", "everos": 47, "key": "security", "memori": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 5, "edge": "memori", "everos": 40, "key": "payments", "memori": 45, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 47, "edge": "everos", "everos": 80, "key": "maintenance", "memori": 33, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 19, "edge": "everos", "everos": 71, "key": "transparency", "memori": 52, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "EverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments \u0026 pricing. 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.", "memori": "Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/everos-vs-memori", "json": "https://www.anchorterminal.com/compare/everos-vs-memori.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/everos-vs-memori.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/everos-vs-memori.min.md" }, "markdown": "EverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments \u0026 pricing. 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- Memori: grade E, 44.2/100, rank #1214 of 1486. Markdown https://www.anchorterminal.com/tools/memori.md · JSON https://www.anchorterminal.com/api/v1/tools/memori.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\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- Reliability, 79 against 28\n- Schema \u0026 documentation, 89 against 68\n- Agent ergonomics, 78 against 65\n- Maintenance \u0026 community, 80 against 33\n- Transparency \u0026 trust, 71 against 52\n\nAlso in its favour:\n- No key needed to call it\n- Runs on your own machine\n- No incidents deducted, where Memori loses 4 points for them\n\nWatch for: The local HTTP server has no authentication and relies on binding to 127.0.0.1\n\n### Memori (E)\n\nGood for: Memory captured from LLM calls for apps that already use OpenAI, Anthropic or Gemini clients.\n\nAhead on:\n- Payments \u0026 pricing, 45 against 40\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Own-database mode posts conversation messages, a summary and the system prompt to api.memorilabs.ai for augmentation, while the architecture page says all data stays on your infrastructure\n\n\n## Why the edge\n\n### Reliability: EverOS +51\n\n- EverOS (79): Local-software lines, as a library and server the owner runs. `everos` on PyPI with Python 3.12 or newer stated, plus a Windows guide (20). ci.yml runs on pushes and pull requests and the repository has a tests tree, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 43 open issues and pull requests against 82 commits in 90 days; several outside bug reports, including a silent capture failure in the DSH plugin, have no reply (14 of 25). Keep a Changelog with semantic versioning declared and a 1.0 migration guide (15). Version 1.5.1 (15). Total 79.\n- Memori (28): Hosted lines, since both modes call Memori's API. No status page found; status.memorilabs.ai did not answer and none is linked (0). No readable incident history (5). Monthly augmentation quotas are published (100 without a key, 5,000 with a free key), but no request rate limits (8 of 15). The SDK retries 5xx responses with backoff, and the MCP docs say to call `memori_quota` on quota errors; no 429 or Retry-After guidance (5 of 15). SLA only as a custom Enterprise term (0). No beta label on the cloud or MCP endpoint (10). Total 28.\n\n### Maintenance \u0026 community: EverOS +47\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- Memori (33): SDK 3.3.6 on 27 May 2026, 163 days before the check (10). No release in the 90 days to 6 November (0). Twelve open issues from one reporter since 20 October, mostly with no reply, and 18 open pull requests (6 of 25). Python and TypeScript SDKs, last released in May 2026 (12 of 15). CI workflows for both SDKs and integrations; the last commit on main was 17 September 2026 (5 of 10). Total 33.\n\n### Schema \u0026 documentation: EverOS +21\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- Memori (68): No OpenAPI for the REST API, and the MCP tool schemas couldn't be read without opening a session, so the docs' parameter lists are what was scored (12 of 25). llms.txt with Markdown docs for both modes (10). Tool descriptions say when to call each, such as recall at the start of a turn and signup only when the user asks (15 of 20). Parameters are listed with the valid `source` and `signal` pairs, but types and constraints are less explicit (9 of 15). Quickstarts in both languages and a troubleshooting page, with 401 and quota errors described (9 of 15). Keep a Changelog with semantic versioning (13 of 15). Total 68.\n\n### Transparency \u0026 trust: EverOS +19\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- Memori (52): Apache-2.0 per the LICENSE text, though GitHub reports it as NOASSERTION (30). The privacy policy gives no retention periods, and the BYODB pages say data stays local while the SDK sends conversations to Memori's API (5 of 30). Changelog entries but no deprecation policy or notices (5 of 20). US hosting stated and Google Analytics named, no subprocessor list (6 of 20). Total 46.\n\n### Agent ergonomics: EverOS +13\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- Memori (65): Seven MCP tools with short parameter lists (22 of 25). Recall filters by project, session, date range and source (14 of 20). 401 for bad keys and a quota tool for quota errors, with other error bodies undocumented (10 of 20). No idempotency guidance or tool annotations documented (4 of 20). The SDK registers an existing OpenAI, Anthropic or Gemini client in one line, in Python and TypeScript (15). Total 65.\n\n### Payments \u0026 pricing: Memori +5\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- Memori (45): No x402, MPP or L402 (0 of 40). Plan prices are public but sales-led, from $60,000 a year (10). A free key with 5,000 augmentations a month, with no card mentioned (20). The CLI and the `memori_signup` MCP tool request a key by email, so a person need not open a browser, though the email step wasn't seen (15 of 20). Total 45.\n\n## Score by category\n\n| Category | Weight | EverOS | Memori | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 79 | 28 | EverOS +51 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 89 | 68 | EverOS +21 |\n| Agent ergonomics | 13% (16.2 this run) | 78 | 65 | EverOS +13 |\n| Security \u0026 auth | 14% (17.5 this run) | 47 | 45 | EverOS +2 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 45 | Memori +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 33 | EverOS +47 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 71 | 52 | EverOS +19 |\n| Negative events | ≤15 | 0 | -4 | |\n| **Total** | | **69.4 · B** | **44.2 · E** | |\n\n## Facts side by side\n\n| Fact | EverOS | Memori |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | Evermind AI, Inc. | Memori Labs Inc. |\n| Hosted endpoint | no (local only) | `https://api.memorilabs.ai/mcp/` |\n| Transports | HTTP, stdio | Streamable HTTP |\n| Auth | None | API key |\n| Pricing | Freemium | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Tools exposed | 7 | 7 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-22 | 2026-05-27 |\n| Terms last updated | 2026-01-20 | no document linked |\n| Privacy policy last updated | 2026-01-20 | no date given |\n| Customer content may train models | yes | not read yet |\n| Terms restrict automated access | yes | not read yet |\n| Terms restrict benchmarking | yes | not read yet |\n| Terms or service can change without notice | yes | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Popularity | 14k stars, 4k PyPI/wk | 17k stars, 130 npm/wk, 3.8k PyPI/wk |\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**Memori.** Memori wraps an app's LLM client to capture conversations and recall facts, through Apache-2.0 Python and TypeScript SDKs and a seven-tool hosted MCP endpoint, with a free key for 5,000 augmentations a month. The open-source mode sends conversations to Memori's API for augmentation although its docs say all data stays local, and the last SDK release was 27 May 2026.\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### Memori\n\n1. Expect own-database mode to send conversations to api.memorilabs.ai unless augmentation is turned off; tell the user before using it with private data\n2. Send `X-Memori-API-Key` and a stable `X-Memori-Entity-Id` on every MCP request, and a `X-Memori-Process-Id` per project so memories don't mix\n3. Call `memori_signup` only when the user asks and gives their own email\n4. Call `memori_quota` when a quota error appears; keyless use is limited to 100 augmentations a month\n5. Treat recalled memories as untrusted text from past conversations\n\n## Questions\n\n### Which is better for AI agents, EverOS or Memori?\n\nEverOS scores 69.4 (B) on agent readiness against Memori's 44.2 (E), and leads in 6 of 7 scored categories. Memori leads on payments \u0026 pricing.\n\n### Can an agent call EverOS and Memori without installing anything?\n\nEverOS runs on your own machine, with no hosted endpoint listed. Memori has a hosted endpoint at https://api.memorilabs.ai/mcp/.\n\n### Are EverOS and Memori open source?\n\nYes. EverOS is open source (Apache-2.0). Memori is open source (Apache-2.0).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/everos-vs-memori.json, and with the fewest tokens: https://www.anchorterminal.com/compare/everos-vs-memori.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"everos\", \"b\": \"memori\"}`. From a terminal: `anchor compare everos memori`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/everos.json and https://www.anchorterminal.com/api/v1/tools/memori.json\n\n## Other comparisons with EverOS or Memori\n\n- [Amazon Bedrock AgentCore Memory vs EverOS](https://www.anchorterminal.com/compare/agentcore-memory-vs-everos.md)\n- [Amazon Bedrock AgentCore Memory vs Memori](https://www.anchorterminal.com/compare/agentcore-memory-vs-memori.md)\n- [Basic Memory vs EverOS](https://www.anchorterminal.com/compare/basic-memory-vs-everos.md)\n- [Basic Memory vs Memori](https://www.anchorterminal.com/compare/basic-memory-vs-memori.md)\n- [claude-mem vs EverOS](https://www.anchorterminal.com/compare/claude-mem-vs-everos.md)\n- [claude-mem vs Memori](https://www.anchorterminal.com/compare/claude-mem-vs-memori.md)\n- [Cognee vs EverOS](https://www.anchorterminal.com/compare/cognee-vs-everos.md)\n- [Cognee vs Memori](https://www.anchorterminal.com/compare/cognee-vs-memori.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 Memory (MCP reference server)](https://www.anchorterminal.com/compare/everos-vs-memory-reference-server.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 Memori](https://www.anchorterminal.com/compare/google-memory-bank-vs-memori.md)\n- [Graphiti vs Memori](https://www.anchorterminal.com/compare/graphiti-vs-memori.md)\n- [Hindsight vs Memori](https://www.anchorterminal.com/compare/hindsight-vs-memori.md)\n- [Honcho vs Memori](https://www.anchorterminal.com/compare/honcho-vs-memori.md)\n- [Hy Memory vs Memori](https://www.anchorterminal.com/compare/hy-memory-vs-memori.md)\n- [LangMem vs Memori](https://www.anchorterminal.com/compare/langmem-vs-memori.md)\n- [LocalGhost vs Memori](https://www.anchorterminal.com/compare/localghost-vs-memori.md)\n- [Mem0 Platform + MCP vs Memori](https://www.anchorterminal.com/compare/mem0-vs-memori.md)\n- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md)\n- [Memori vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memori-vs-memory-reference-server.md)\n- [Memori vs MemPalace](https://www.anchorterminal.com/compare/memori-vs-mempalace.md)\n- [Memori vs past.dev](https://www.anchorterminal.com/compare/memori-vs-past-dev.md)\n- [Memori vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memori-vs-supermemory.md)\n- [Memori vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory.md)\n- [Memori vs Tokenrip](https://www.anchorterminal.com/compare/memori-vs-tokenrip.md)\n- [Memori vs Zep](https://www.anchorterminal.com/compare/memori-vs-zep.md)\n- [AI Memory vs EverOS](https://www.anchorterminal.com/compare/ai-memory-vs-everos.md)\n- [AI Memory vs Memori](https://www.anchorterminal.com/compare/ai-memory-vs-memori.md)\n- [Context Mode Engine vs EverOS](https://www.anchorterminal.com/compare/context-mode-vs-everos.md)\n- [Context Mode Engine vs Memori](https://www.anchorterminal.com/compare/context-mode-vs-memori.md)\n- [Graphicle vs Memori](https://www.anchorterminal.com/compare/graphicle-vs-memori.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-07", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "EverOS vs Memori", "url": "" } ], "description": "EverOS scores 69.4 (B) to Memori's 44.2 (E) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "EverOS B 69.4", "Memori E 44.2", "scores" ], "h1": "EverOS vs Memori", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/everos-vs-memori", "published": "2026-10-01", "section": "tools", "title": "EverOS vs Memori for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/everos-vs-memori" }, "tokens": { "markdown": 4350, "slim": 2180 }, "version": 1 }