{ "data": { "a": { "slug": "memmachine", "name": "MemMachine", "vendor": "MemVerge, Inc.", "vendorUrl": "https://memmachine.ai", "kind": "http-api", "category": "agent-memory", "summary": "MemMachine is an open-source long-term memory layer for AI agents, incubated by MemVerge, with episodic, profile and working memory behind a self-hosted REST server, Python and TypeScript clients and an MCP server, plus a hosted platform.", "url": "https://www.anchorterminal.com/tools/memmachine", "markdownUrl": "https://www.anchorterminal.com/tools/memmachine.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/memmachine.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/memmachine.json", "dns": "memmachine.grade.anchorterminal.com", "repo": "https://github.com/MemMachine/MemMachine", "license": "Apache-2.0", "transports": [ "http", "stdio", "streamable-http" ], "packages": [ { "registry": "pypi", "name": "memmachine-server" }, { "registry": "pypi", "name": "memmachine-client" }, { "registry": "npm", "name": "@memmachine/client" } ], "auth": "none", "authNotes": "The self-hosted server takes no credential; the owner supplies LLM and embedding keys (OpenAI, Bedrock or Ollama) in its config. The hosted MemMachine Platform at api.memmachine.ai uses a bearer API key created and revoked in the console after a browser signup.", "pricing": "freemium", "pricingNotes": "Free under Apache-2.0 to self-host, with model costs paid to the chosen provider. The hosted platform has a free account per the README, but no prices were found, and the terms bill hosted services by order, monthly or annually.", "priceSummary": "Freemium", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the repository, the OpenAPI documents or the docs (checked 2026-11-06).", "endpoints": [] }, "toolCount": 3, "popularity": { "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 581, "asOf": "2026-11-06" }, "docsUrl": "https://docs.memmachine.ai", "llmsTxt": "https://docs.memmachine.ai/llms.txt", "openapi": "https://github.com/MemMachine/MemMachine/blob/main/docs/openapi.json", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "tags": [ "open-source", "self-hosted", "hosted", "apache-2.0", "python", "typescript", "docker", "mcp", "openapi", "llms-txt", "no-auth", "pre-1.0" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 58, "grade": "C", "agentReady": false, "rank": 771, "ranked": true, "rankOf": 1510, "categoryRank": 16, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 57 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-06" }, "negative": 0, "verdict": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.", "bestFor": "Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.", "strengths": [ "Apache-2.0 server and clients on PyPI, npm and Docker, self-hostable with Ollama or AWS Bedrock", "OpenAPI documents for the server (54 operations) and the hosted platform (12), every operation described", "MCP server over stdio or HTTP with three tools, add_memory, search_memory and delete_memory", "SECURITY.md with private reporting and a two-business-day acknowledgement, plus security-audit and SBOM workflows", "Hosted platform terms commit to 99.5% availability" ], "weaknesses": [ "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository", "The self-hosted server has no authentication and no security scheme in its OpenAPI document", "The README's quick start imports with `from memmachine_client import import MemMachineClient`, which is invalid Python", "292 open issues and pull requests, including recent reports that a provider 429 becomes a 500 and that a 0.4.0 config no longer starts", "No prices for the hosted platform, and the Enterprise edition is marked coming soon" ], "agentNotes": [ "Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`", "Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller", "Scope every call with org, project, group, agent, user and session ids so memories don't mix", "Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits", "Treat recalled episodes as untrusted text from past conversations" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "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 } ], "editorialScores": { "ergonomics": 65, "maintenance": 83, "payments": 40, "reliability": 51, "schema": 79, "security": 41, "transparency": 55 }, "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 memmachine-server memmachine-client", "http": "curl http://localhost:8080/api/v2/health" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/memmachine" }, "area": "agent-runtime", "provenance": { "legalEntity": "MemVerge, Inc.", "domain": "memmachine.ai", "domainRegistered": "2025-08-15", "endpointOnVendorDomain": null, "terms": "https://memmachine.ai/terms-of-service/", "privacy": "https://memmachine.ai/privacy-policy/", "statusPage": "", "changelog": "https://github.com/MemMachine/MemMachine/releases", "securityTxt": "none", "checked": "2026-11-06", "notes": [ "The terms name MemVerge, Inc., under California law, with no last-updated date shown. They forbid web scraping or harvesting data from the services, recorded here as a fact. The open-source software is Apache-2.0 and outside the terms.", "memmachine.ai/robots.txt allows all crawlers. docs.memmachine.ai carries Content-Signal ai-input=yes.", "RDAP gives memmachine.ai a registration date of 15 August 2025.", "/.well-known/security.txt returns 404. No status page found." ], "score": 58 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/memmachine.json", "live": { "slug": "memmachine", "versions": [ { "registry": "github", "name": "MemMachine/MemMachine", "version": "v0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:57.45502049Z" }, { "registry": "npm", "name": "@memmachine/client", "version": "0.3.9", "seenAt": "2026-11-06T23:43:56.945798416Z" }, { "registry": "pypi", "name": "memmachine-client", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:55.050118334Z" }, { "registry": "pypi", "name": "memmachine-server", "version": "0.4.0", "released": "2026-10-08", "seenAt": "2026-11-06T23:43:54.864236924Z" } ], "githubStars": 3085, "npmWeekly": 28, "pypiWeekly": 54, "securityTxt": { "url": "https://memmachine.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-11-07T16:00:09.818703565Z" }, "llmsTxt": { "url": "https://docs.memmachine.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:59.84146138Z" }, "pages": [ { "url": "https://memmachine.ai/privacy-policy/", "kind": "privacy", "status": 200, "checkedAt": "2026-11-07T14:14:11.012100581Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "19edc6281451" }, { "url": "https://memmachine.ai/terms-of-service/", "kind": "terms", "status": 200, "checkedAt": "2026-11-07T14:14:13.19202427Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "079364130152" } ], "updatedAt": "2026-11-07T16:00:09.818703565Z" } }, "answer": "MemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 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": 1231, "ranked": true, "rankOf": 1510, "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": "2026-11-07T19:22:19.067041408Z", "lastOk": true, "lastStatus": 401, "lastMs": 258, "lastNote": "asks for credentials", "authRequired": true, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 272, "p95ms24h": 361, "samples24h": 210, "samples30d": 210, "days": [ { "date": "2026-11-06", "probes": 13, "ok": 13 }, { "date": "2026-11-07", "probes": 197, "ok": 197 } ] }, "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": "2026-11-07T19:22:19.067041408Z" } }, "edges": [ { "by": 50, "category": "maintenance", "leads": "memmachine", "name": "Maintenance \u0026 community", "reasons": { "a": "v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.", "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": 83, "b": 33 } }, { "by": 23, "category": "reliability", "leads": "memmachine", "name": "Reliability", "reasons": { "a": "Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.", "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": 51, "b": 28 } }, { "by": 11, "category": "schema", "leads": "memmachine", "name": "Schema \u0026 documentation", "reasons": { "a": "OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79.", "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": 79, "b": 68 } }, { "by": 5, "category": "payments", "leads": "memori", "name": "Payments \u0026 pricing", "reasons": { "a": "Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI 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 } }, { "by": 5, "category": "transparency", "leads": "memmachine", "name": "Transparency \u0026 trust", "reasons": { "a": "Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.", "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": 57, "b": 52 } } ], "facts": [ { "a": "HTTP API", "b": "SDK + MCP", "name": "Kind" }, { "a": "MemVerge, Inc.", "b": "Memori Labs Inc.", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.memorilabs.ai/mcp/", "name": "Hosted endpoint" }, { "a": "HTTP, stdio, Streamable HTTP", "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": "3", "b": "7", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-08", "b": "2026-05-27", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-05-20", "b": "no date given", "name": "Privacy policy last updated" }, { "a": "not found in the text", "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": "not found in the text", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "3.1k stars, 28 npm/wk, 581 PyPI/wk", "b": "17k stars, 130 npm/wk, 3.8k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "MemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on payments \u0026 pricing.", "question": "Which is better for AI agents, MemMachine or Memori?" }, { "answer": "MemMachine 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 MemMachine and Memori without installing anything?" }, { "answer": "Yes. MemMachine is open source (Apache-2.0). Memori is open source (Apache-2.0).", "question": "Are MemMachine and Memori open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 51 against 28", "Schema \u0026 documentation, 79 against 68", "Maintenance \u0026 community, 83 against 33", "Transparency \u0026 trust, 57 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 agent frameworks that want episodic and profile memory with many integrations.", "slug": "memmachine", "watchFor": "Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository" }, { "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-memmachine.json", "title": "Amazon Bedrock AgentCore Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine" }, { "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-memmachine.json", "title": "Basic Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-memmachine" }, { "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-memmachine.json", "title": "claude-mem vs MemMachine", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-memmachine" }, { "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-memmachine.json", "title": "Cognee vs MemMachine", "url": "https://www.anchorterminal.com/compare/cognee-vs-memmachine" }, { "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-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/google-memory-bank-vs-memmachine.json", "title": "Agent Platform Memory Bank vs MemMachine", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine" }, { "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-memmachine.json", "title": "Graphiti vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphiti-vs-memmachine" }, { "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-memmachine.json", "title": "Hindsight vs MemMachine", "url": "https://www.anchorterminal.com/compare/hindsight-vs-memmachine" }, { "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-memmachine.json", "title": "Honcho vs MemMachine", "url": "https://www.anchorterminal.com/compare/honcho-vs-memmachine" }, { "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-memmachine.json", "title": "Hy Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-memmachine" }, { "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-memmachine.json", "title": "LangMem vs MemMachine", "url": "https://www.anchorterminal.com/compare/langmem-vs-memmachine" }, { "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-memmachine.json", "title": "LocalGhost vs MemMachine", "url": "https://www.anchorterminal.com/compare/localghost-vs-memmachine" }, { "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-memmachine.json", "title": "Mem0 Platform + MCP vs MemMachine", "url": "https://www.anchorterminal.com/compare/mem0-vs-memmachine" }, { "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-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/memmachine-vs-mempalace.json", "title": "MemMachine vs MemPalace", "url": "https://www.anchorterminal.com/compare/memmachine-vs-mempalace" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev.json", "title": "MemMachine vs past.dev", "url": "https://www.anchorterminal.com/compare/memmachine-vs-past-dev" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory.json", "title": "MemMachine vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/memmachine-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.json", "title": "MemMachine vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.json", "title": "MemMachine vs Tokenrip", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-zep.json", "title": "MemMachine vs Zep", "url": "https://www.anchorterminal.com/compare/memmachine-vs-zep" }, { "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-memmachine.json", "title": "AI Memory vs MemMachine", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-memmachine" }, { "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-memmachine.json", "title": "Context Mode Engine vs MemMachine", "url": "https://www.anchorterminal.com/compare/context-mode-vs-memmachine" }, { "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-memmachine.json", "title": "Graphicle vs MemMachine", "url": "https://www.anchorterminal.com/compare/graphicle-vs-memmachine" }, { "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": 23, "edge": "memmachine", "key": "reliability", "memmachine": 51, "memori": 28, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "edge": "memmachine", "key": "schema", "memmachine": 79, "memori": 68, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 0, "edge": "", "key": "ergonomics", "memmachine": 65, "memori": 65, "name": "Agent ergonomics", "weight": 13 }, { "by": 4, "edge": "memori", "key": "security", "memmachine": 41, "memori": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 5, "edge": "memori", "key": "payments", "memmachine": 40, "memori": 45, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 50, "edge": "memmachine", "key": "maintenance", "memmachine": 83, "memori": 33, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 5, "edge": "memmachine", "key": "transparency", "memmachine": 57, "memori": 52, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "MemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on payments \u0026 pricing. Both do agent memory.", "tasks": null, "tutorials": [], "verdicts": { "memmachine": "MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.", "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/memmachine-vs-memori", "json": "https://www.anchorterminal.com/compare/memmachine-vs-memori.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/memmachine-vs-memori.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/memmachine-vs-memori.min.md" }, "markdown": "MemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on payments \u0026 pricing. Both do agent memory.\n\n- MemMachine: grade C, 58/100, rank #771 of 1510. Markdown https://www.anchorterminal.com/tools/memmachine.md · JSON https://www.anchorterminal.com/api/v1/tools/memmachine.json\n- Memori: grade E, 44.2/100, rank #1231 of 1510. 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### MemMachine (C)\n\nGood for: Self-hosted memory for agent frameworks that want episodic and profile memory with many integrations.\n\nAhead on:\n- Reliability, 51 against 28\n- Schema \u0026 documentation, 79 against 68\n- Maintenance \u0026 community, 83 against 33\n- Transparency \u0026 trust, 57 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: Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository\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### Maintenance \u0026 community: MemMachine +50\n\n- MemMachine (83): v0.4.0 on PyPI on 8 October 2026, 29 days before the check (30). v0.3.9-post1, v0.4.0, v0.4.1-dev0 and v0.4.1-a1 in 90 days (20). Many open issues and recent reports with few replies (12 of 25). Python and TypeScript clients, both current (12 of 15). uv lock checks, security audit, SBOM and stale-issue workflows (9 of 10). Total 83.\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### Reliability: MemMachine +23\n\n- MemMachine (51): Local-software lines, as a server the owner runs. `memmachine-server` and `memmachine-client` on PyPI with Python versions stated, a Docker image and a compose script (20). pytest, integration and installation-test workflows exist, but GitHub's API answered with a rate limit, so run results were unread (15 of 25, unchecked). 292 open issues and pull requests; the newest bug reports, including a 429 from a provider surfacing as a 500 and a 0.4.0 configuration that no longer starts, have zero to two replies (10 of 25). No changelog file, release notes only on GitHub, which weren't read, and pre-1.0 tags (6 of 15). Version 0.4.0 (0). Total 51.\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### Schema \u0026 documentation: MemMachine +11\n\n- MemMachine (79): OpenAPI documents for the server (54 operations) and the hosted platform (12) (25). llms.txt on docs.memmachine.ai with Markdown pages (10). Every operation has a description, and the docs explain memory types and scoping (15 of 20). Typed request models generated from the server, with search options for limits and filters (12 of 15). Examples for each client and the MCP tools, but only 422 is documented on the server and the README's first example doesn't run (8 of 15). `/api/v2` paths and tagged releases, no changelog (9 of 15). Total 79.\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### Payments \u0026 pricing: Memori +5\n\n- MemMachine (40): Self-hosted rule, with the price lines read for the hosted platform. No x402, MPP or L402 (0 of 40). No hosted prices found on the site or docs (0). Free to self-host with no card (20). An agent can install it from PyPI 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### Transparency \u0026 trust: MemMachine +5\n\n- MemMachine (57): Apache-2.0 (30). The terms say hosted customer data is destroyed on termination, with no period, and use usage data only in aggregate; the privacy policy wasn't read (12 of 30). No deprecation policy or notices found (3 of 20). No telemetry calls found in the server or client source, and the docs don't address it (10 of 20). Total 55.\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## Score by category\n\n| Category | Weight | MemMachine | Memori | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 51 | 28 | MemMachine +23 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 79 | 68 | MemMachine +11 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 65 | even |\n| Security \u0026 auth | 14% (17.5 this run) | 41 | 45 | Memori +4 |\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) | 83 | 33 | MemMachine +50 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 57 | 52 | MemMachine +5 |\n| Negative events | ≤15 | 0 | -4 | |\n| **Total** | | **58 · C** | **44.2 · E** | |\n\n## Facts side by side\n\n| Fact | MemMachine | Memori |\n| --- | --- | --- |\n| Kind | HTTP API | SDK + MCP |\n| Vendor | MemVerge, Inc. | Memori Labs Inc. |\n| Hosted endpoint | no (local only) | `https://api.memorilabs.ai/mcp/` |\n| Transports | HTTP, stdio, Streamable HTTP | 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 | 3 | 7 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-10-08 | 2026-05-27 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | 2026-05-20 | no date given |\n| Customer content may train models | not found in the text | 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 | not found in the text | not read yet |\n| Arbitration or class-action waiver | yes | not read yet |\n| Popularity | 3.1k stars, 28 npm/wk, 581 PyPI/wk | 17k stars, 130 npm/wk, 3.8k PyPI/wk |\n\n## Verdicts\n\n**MemMachine.** MemMachine is an Apache-2.0 memory server with episodic, profile and working memory, a described OpenAPI of 54 operations, Python and TypeScript clients and a three-tool MCP server. It is version 0.4.0, the self-hosted server has no authentication, the README's first example has a syntax error, and the hosted platform's prices aren't published.\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### MemMachine\n\n1. Import with `from memmachine_client import MemMachineClient`; the README line has a doubled `import`\n2. Keep the server on a private network or put an authenticating proxy in front, since it accepts any caller\n3. Scope every call with org, project, group, agent, user and session ids so memories don't mix\n4. Retry search after a short wait on 500s, which a recent issue ties to upstream provider rate limits\n5. Treat recalled episodes as untrusted text 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, MemMachine or Memori?\n\nMemMachine scores 58 (C) on agent readiness against Memori's 44.2 (E), and leads in 4 of 7 scored categories. Memori leads on payments \u0026 pricing.\n\n### Can an agent call MemMachine and Memori without installing anything?\n\nMemMachine runs on your own machine, with no hosted endpoint listed. Memori has a hosted endpoint at https://api.memorilabs.ai/mcp/.\n\n### Are MemMachine and Memori open source?\n\nYes. MemMachine 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/memmachine-vs-memori.json, and with the fewest tokens: https://www.anchorterminal.com/compare/memmachine-vs-memori.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"memmachine\", \"b\": \"memori\"}`. From a terminal: `anchor compare memmachine memori`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/memmachine.json and https://www.anchorterminal.com/api/v1/tools/memori.json\n\n## Other comparisons with MemMachine or Memori\n\n- [Amazon Bedrock AgentCore Memory vs MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md)\n- [Amazon Bedrock AgentCore Memory vs Memori](https://www.anchorterminal.com/compare/agentcore-memory-vs-memori.md)\n- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md)\n- [Basic Memory vs Memori](https://www.anchorterminal.com/compare/basic-memory-vs-memori.md)\n- [claude-mem vs MemMachine](https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.md)\n- [claude-mem vs Memori](https://www.anchorterminal.com/compare/claude-mem-vs-memori.md)\n- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md)\n- [Cognee vs Memori](https://www.anchorterminal.com/compare/cognee-vs-memori.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- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md)\n- [Agent Platform Memory Bank vs Memori](https://www.anchorterminal.com/compare/google-memory-bank-vs-memori.md)\n- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md)\n- [Graphiti vs Memori](https://www.anchorterminal.com/compare/graphiti-vs-memori.md)\n- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md)\n- [Hindsight vs Memori](https://www.anchorterminal.com/compare/hindsight-vs-memori.md)\n- [Honcho vs MemMachine](https://www.anchorterminal.com/compare/honcho-vs-memmachine.md)\n- [Honcho vs Memori](https://www.anchorterminal.com/compare/honcho-vs-memori.md)\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)\n- [Hy Memory vs Memori](https://www.anchorterminal.com/compare/hy-memory-vs-memori.md)\n- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md)\n- [LangMem vs Memori](https://www.anchorterminal.com/compare/langmem-vs-memori.md)\n- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md)\n- [LocalGhost vs Memori](https://www.anchorterminal.com/compare/localghost-vs-memori.md)\n- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)\n- [Mem0 Platform + MCP vs Memori](https://www.anchorterminal.com/compare/mem0-vs-memori.md)\n- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md)\n- [MemMachine vs MemPalace](https://www.anchorterminal.com/compare/memmachine-vs-mempalace.md)\n- [MemMachine vs past.dev](https://www.anchorterminal.com/compare/memmachine-vs-past-dev.md)\n- [MemMachine vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memmachine-vs-supermemory.md)\n- [MemMachine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md)\n- [MemMachine vs Tokenrip](https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.md)\n- [MemMachine vs Zep](https://www.anchorterminal.com/compare/memmachine-vs-zep.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 MemMachine](https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.md)\n- [AI Memory vs Memori](https://www.anchorterminal.com/compare/ai-memory-vs-memori.md)\n- [Context Mode Engine vs MemMachine](https://www.anchorterminal.com/compare/context-mode-vs-memmachine.md)\n- [Context Mode Engine vs Memori](https://www.anchorterminal.com/compare/context-mode-vs-memori.md)\n- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.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": "MemMachine vs Memori", "url": "" } ], "description": "MemMachine scores 58 (C) to Memori's 44.2 (E) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "MemMachine C 58", "Memori E 44.2", "scores" ], "h1": "MemMachine vs Memori", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/memmachine-vs-memori", "published": "2026-10-01", "section": "tools", "title": "MemMachine vs Memori for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memori" }, "tokens": { "markdown": 4100, "slim": 1880 }, "version": 1 }