{ "data": { "similar": [ { "grade": "BB", "json": "https://www.anchorterminal.com/tools/zep.json", "name": "Zep", "score": 71, "shared": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "slug": "zep" }, { "grade": "B", "json": "https://www.anchorterminal.com/tools/past-dev.json", "name": "past.dev", "score": 69.8, "shared": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "slug": "past-dev" }, { "grade": "C", "json": "https://www.anchorterminal.com/tools/supermemory.json", "name": "Supermemory API + MCP", "score": 59.6, "shared": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "slug": "supermemory" }, { "grade": "D", "json": "https://www.anchorterminal.com/tools/hy-memory.json", "name": "Hy Memory", "score": 53.8, "shared": [ "memory.store", "memory.search", "memory.user", "memory.graph", "memory.delete" ], "slug": "hy-memory" }, { "grade": "E", "json": "https://www.anchorterminal.com/tools/mem0.json", "name": "Mem0 Platform + MCP", "score": 40.1, "shared": [ "memory.store", "memory.search", "memory.graph", "memory.user", "memory.delete" ], "slug": "mem0" }, { "grade": "A", "json": "https://www.anchorterminal.com/tools/agentcore-memory.json", "name": "Amazon Bedrock AgentCore Memory", "score": 79.7, "shared": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "slug": "agentcore-memory" } ], "tool": { "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": 767, "ranked": true, "rankOf": 1486, "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" ], "breakdown": [ { "key": "reliability", "name": "Reliability", "weight": 16, "effectiveWeight": 20, "score": 51, "points": 10.2, "reason": "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.", "checked": "2026-11-06" }, { "key": "performance", "name": "Performance", "weight": 10, "effectiveWeight": 0, "pending": true, "points": 0, "reason": "Pending. Latency is measured per call by our probes, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until the first probe window closes." }, { "key": "schema", "name": "Schema \u0026 documentation", "weight": 13, "effectiveWeight": 16.25, "score": 79, "points": 12.84, "reason": "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.", "checked": "2026-11-06" }, { "key": "ergonomics", "name": "Agent ergonomics", "weight": 13, "effectiveWeight": 16.25, "score": 65, "points": 10.56, "reason": "Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.", "checked": "2026-11-06" }, { "key": "security", "name": "Security \u0026 auth", "weight": 14, "effectiveWeight": 17.5, "score": 41, "points": 7.18, "reason": "Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.", "checked": "2026-11-06" }, { "key": "payments", "name": "Payments \u0026 pricing", "weight": 10, "effectiveWeight": 12.5, "score": 40, "points": 5, "reason": "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.", "checked": "2026-11-06" }, { "key": "tasks", "name": "Task success", "weight": 10, "effectiveWeight": 0, "pending": true, "points": 0, "reason": "Pending. Task success needs the category task suites run through each tool, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until then. A data provider's data-quality score is published on its listing now and becomes half of this category when it's scored." }, { "key": "maintenance", "name": "Maintenance \u0026 community", "weight": 7, "effectiveWeight": 8.75, "score": 83, "points": 7.26, "reason": "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.", "checked": "2026-11-06" }, { "key": "transparency", "name": "Transparency \u0026 trust", "weight": 7, "effectiveWeight": 8.75, "score": 57, "points": 4.99, "note": "editorial 55, provenance 58", "reason": "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.", "checked": "2026-11-06" } ], "assessment": { "date": "2026-11-06", "basis": "public evidence", "confidence": "medium", "notes": { "ergonomics": "Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.", "maintenance": "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.", "payments": "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.", "reliability": "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.", "schema": "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.", "security": "Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.", "transparency": "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." }, "sources": [ { "what": "repository, README, SECURITY.md, governance, server source (clone)", "url": "https://github.com/MemMachine/MemMachine", "seen": "2026-11-06" }, { "what": "server OpenAPI", "url": "https://github.com/MemMachine/MemMachine/blob/main/docs/openapi.json", "seen": "2026-11-06" }, { "what": "MCP tools source", "url": "https://github.com/MemMachine/MemMachine/blob/main/packages/server/src/memmachine_server/server/api_v2/mcp.py", "seen": "2026-11-06" }, { "what": "docs llms.txt", "url": "https://docs.memmachine.ai/llms.txt", "seen": "2026-11-06" }, { "what": "platform introduction and API key docs", "url": "https://docs.memmachine.ai/platform/api_key.md", "seen": "2026-11-06" }, { "what": "home page", "url": "https://memmachine.ai/", "seen": "2026-11-06" }, { "what": "terms of service", "url": "https://memmachine.ai/terms-of-service/", "seen": "2026-11-06" }, { "what": "PyPI release feed", "url": "https://pypi.org/rss/project/memmachine-server/releases.xml", "seen": "2026-11-06" } ], "openQuestions": [ "The lead said the licence isn't named on the home page, which is right; the repository is Apache-2.0. Enterprise is still marked coming soon.", "Graded on the self-hosted server the lead named. The hosted platform would need its own pass for pricing, limits and status.", "unchecked: CI run results and GitHub release notes, because GitHub's API answered with a rate limit.", "unchecked: the privacy policy at memmachine.ai/privacy-policy/, left to the policy reader.", "Investors and MemVerge's ownership were not looked for in this pass.", "Lapse. pypi.org/pypi/\u003cpackage\u003e/json, which PyPI's robots.txt disallows (/pypi/*/json), was fetched for this listing's packages on 6 November 2026 before robots.txt was read. Nothing from those responses is used; versions and release dates come from the allowed release feed at pypi.org/rss/project/\u003cpackage\u003e/releases.xml, and licences and authors from the repository." ] }, "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 }, "scoreHistory": [ { "date": "2026-11-06", "grade": "C", "kind": "listed", "method": "0.7", "score": 58 } ] }, "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" }, "notable": [ "v0.4.0 tagged on 6 October 2026 and published to PyPI on 8 October, with pre-releases v0.4.1-dev0 on 15 October and v0.4.1-a1 on 5 November (https://pypi.org/rss/project/memmachine-server/releases.xml)", "The server's OpenAPI document (MemMachine API 0.3.10) has 54 operations and no security scheme; the platform's (MemMachine Public API 0.1.0, api.memmachine.ai) has 12 with bearer auth. Every operation in both has a description (https://github.com/MemMachine/MemMachine/tree/main/docs)", "The MCP server registers three tools, add_memory, search_memory and delete_memory, over stdio or HTTP (https://github.com/MemMachine/MemMachine/blob/main/packages/server/src/memmachine_server/server/api_v2/mcp.py)", "The home page says MemVerge incubated the project and that an Enterprise version is coming soon (https://memmachine.ai/)", "The terms name MemVerge, Inc. under California law, commit to 99.5% availability for hosted services and forbid scraping the services (https://memmachine.ai/terms-of-service/)" ], "area": "agent-runtime", "details": [ { "label": "Surface listed", "value": "The self-hosted MemMachine server and its Python and TypeScript clients and MCP server at v0.4.0, read from a clone of github.com/MemMachine/MemMachine, PyPI, docs.memmachine.ai and memmachine.ai's home page and terms on 6 November 2026. The hosted platform was read from its docs only" }, { "label": "Memory types", "value": "Episodic memory in a graph store, profile (semantic) memory in SQL and short-term working memory, scoped by org, project, group, agent, user and session" }, { "label": "Integrations", "value": "LangChain, LangGraph, LlamaIndex, CrewAI, AWS Strands, Dify, FastGPT, n8n and OpenClaw" }, { "label": "Hosted platform", "value": "Console at console.memmachine.ai with usage dashboard and revocable API keys; Public API at api.memmachine.ai with bearer auth" }, { "label": "Legal entity", "value": "MemVerge, Inc., per the terms of service, under California law" } ], "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, "checks": [ { "check": "Legal entity named", "value": "MemVerge, Inc.", "points": 20, "max": 20, "state": "ok" }, { "check": "Domain age", "value": "memmachine.ai, registered 2025-08-15 (1 year)", "points": 3, "max": 15, "state": "part" }, { "check": "Endpoint on the vendor's domain", "value": "no hosted endpoint", "points": 0, "max": 0, "state": "na" }, { "check": "Terms of service", "value": "read, states 4 of the 7 things a reader expects, and has 2 clauses that cost points", "points": 3.4, "max": 10, "state": "part" }, { "check": "Privacy policy", "value": "read, states 8 of the 8 things a reader expects", "points": 10, "max": 10, "state": "ok" }, { "check": "Status page", "value": "not found", "points": 0, "max": 10, "state": "no" }, { "check": "Changelog", "value": "published", "points": 10, "max": 10, "state": "ok" }, { "check": "security.txt", "value": "not found", "points": 0, "max": 10, "state": "no" }, { "check": "People named", "value": "3 named with their role, none with a public profile", "points": 7, "max": 10, "state": "part" }, { "check": "Support route", "value": "help pages, a community", "points": 5, "max": 5, "state": "ok" } ], "policies": [ { "kind": "terms", "url": "https://memmachine.ai/terms-of-service/", "state": "read", "readAt": "2026-11-06", "words": 5441, "points": 3.4, "max": 10, "expected": [ { "key": "terms.date", "label": "Gives the date it was last updated", "found": false }, { "key": "terms.law", "label": "Names the governing law or courts", "found": true, "quote": "These Terms shall be governed by the laws of the State of California without regard to its conflict of laws provisions.", "says": "The law of the State of California" }, { "key": "terms.liability", "label": "States a limit on its liability", "found": true, "quote": "IN THESE STATES, MEMVERGE’S LIABILITY WILL BE LIMITED TO THE GREATEST EXTENT PERMITTED BY LAW." }, { "key": "terms.termination", "label": "Says how the agreement or account can be ended", "found": true, "quote": "Notwithstanding any of these Terms, Customer shall not have the right to terminate these Terms for convenience." }, { "key": "terms.changes", "label": "Says how changes to the terms are announced", "found": false }, { "key": "terms.use", "label": "Lists what users may not do", "found": true, "quote": "Customer shall not, and shall not permit any third party to:" }, { "key": "terms.sla", "label": "Refers to a service level or uptime commitment", "found": false } ], "toKnow": [ { "key": "terms.automated", "label": "Restricts automated access", "found": true, "quote": "4.4.i use any method to extract data, such as web scraping or web harvesting from the Services, including MemVerge’s account and contact data, AI technology providers’ models, algorithms, or systems other than as permitted;", "costsPoints": true }, { "key": "terms.benchmark", "label": "Restricts benchmarking or competitive use", "found": true, "quote": "4.4.a access the Services, including MemVerge’s AI technology providers’ models, algorithms, or systems to build substantially similar functionality or a competing Services or service, including to train competing AI models (e.g., create synthetic training);", "costsPoints": true }, { "key": "terms.arbitration", "label": "Requires arbitration or waives class actions", "found": true, "quote": "IMPORTANT: PLEASE CAREFULLY REVIEW THE ARBITRATION AGREEMENT SET FORTH BELOW, AS IT WILL REQUIRE YOU TO RESOLVE DISPUTES WITH MEMVERGE ON AN INDIVIDUAL BASIS THROUGH FINAL AND BINDING ARBITRATION AND WAIVING YOUR RIGHT TO A CLASS ACTION." } ] }, { "kind": "privacy", "url": "https://memmachine.ai/privacy-policy/", "state": "read", "readAt": "2026-11-06", "statedDate": "2026-05-20", "words": 6784, "points": 10, "max": 10, "expected": [ { "key": "privacy.date", "label": "Gives the date it was last updated", "found": true, "quote": "Last updated: May 20th, 2026", "says": "Last updated 2026-05-20" }, { "key": "privacy.collected", "label": "Says what personal data is collected", "found": true, "quote": "This Privacy Policy explains how we collect, use, share and protect personal information (used interchangeably with personal data) processed in relation to the Site and the services, including our products, e.g., Memory Machine Cloud Edition, MemoryViewer, MemMachine.AI, and CXL (\"Services\") (collectively, “Platform”)…" }, { "key": "privacy.retention", "label": "Says how long data is kept", "found": true, "quote": "In this case, the information must be retained as long as needed for exercising respective potential legal claims.", "says": "For as long as needed, with no period named" }, { "key": "privacy.processors", "label": "Says who else receives the data", "found": true, "quote": "We use the terms ‘controller’ and ‘processor’ and ‘service provider’ as they are commonly understood under applicable privacy laws." }, { "key": "privacy.sale", "label": "Says whether personal data is sold or shared for advertising", "found": true, "quote": "Unless described otherwise in this Policy, MemVerge does not sell or share any of your personal information with third parties for their promotional or direct marketing purposes.", "says": "Says it does not sell personal data" }, { "key": "privacy.rights", "label": "Says what rights people have over their data", "found": true, "quote": "If you have any questions, comments, or concerns regarding this Privacy Policy, our Cookie Banner and/or our data practices, or would like to exercise your rights, do not hesitate to contact us at privacy@memverge.com or see our information directly below for other methods to communicate with us." }, { "key": "privacy.contact", "label": "Gives a privacy contact", "found": true, "quote": "If you have any questions, comments, or concerns regarding this Privacy Policy, our Cookie Banner and/or our data practices, or would like to exercise your rights, do not hesitate to contact us at privacy@memverge.com or see our information directly below for other methods to communicate with us.", "says": "privacy@memverge.com" }, { "key": "privacy.transfers", "label": "Says where data is transferred or stored", "found": true, "quote": "Safeguards we may take in our discretion include, for instance, entering into the standard contractual clauses (\"SCC’s\") and/or international data transfer agreement/addendum (\"IDTA\") in connection with any onward transfers of personal information.", "says": "Relies on standard contractual clauses" } ] } ] }, "humans": { "slug": "memmachine", "checked": "2026-11-06", "company": "MemVerge, Inc.", "people": [ { "name": "Charles Fan", "role": "Co-founder and CEO, MemVerge", "founder": true, "page": "/people/charles-fan/" }, { "name": "Shuki Bruck", "role": "Co-founder and Chairman, MemVerge", "founder": true, "page": "/people/shuki-bruck/" }, { "name": "Shu Wang", "role": "Chief Technology Officer, MemVerge", "page": "/people/shu-wang/" } ], "peopleNote": "MemMachine is MemVerge's open-source memory layer: memmachine.ai names MemVerge as its incubator and the repository's GOVERNANCE.md describes maintainer roles without naming people. The people listed are MemVerge's, from its leadership page read on 6 November 2026, which calls Charles Fan co-founder and CEO and Shuki Bruck co-founder and Chairman, and names Shu Wang as CTO. VentureBeat (2 April 2019) says Fan cofounded the company with Caltech colleagues Shuki Bruck and Yue Li; Yue Li's current role isn't on a first-hand page, so he isn't listed. No MemMachine product lead was named first-hand. Investors come from VentureBeat's report of the $24.5M Series A (April 2019, led by Banyan), MemVerge's press release of May 2020 as carried by StorageNewsletter ($19M led by Intel Capital, called a Series B in the headline), and the Investors logos on memverge.ai/company/about, which add Samsung, Broadcom and Industry Ventures without a round. No later round, total raised or valuation was found on memverge.ai (its news page lists no funding release) or in a search.", "companySocial": { "github": "https://github.com/MemMachine" }, "support": { "urls": [ "https://docs.memmachine.ai", "https://github.com/MemMachine/MemMachine/issues" ], "community": [ { "label": "Discord", "url": "https://discord.gg/usydANvKqD", "kind": "discord" } ] }, "sources": [ "https://memmachine.ai/", "https://memmachine.ai/terms-of-service/", "https://github.com/MemMachine/MemMachine/blob/main/GOVERNANCE.md", "https://memverge.ai/company/leadership", "https://memverge.ai/company/about", "https://venturebeat.com/ai/memverge-raises-24-5-million-for-intel-optane-based-infrastructure-designed-for-big-data-workloads", "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/" ], "ownership": { "status": "private", "checked": "2026-11-06", "sources": [ "https://memmachine.ai/terms-of-service/", "https://memverge.ai/company/about", "https://venturebeat.com/ai/memverge-raises-24-5-million-for-intel-optane-based-infrastructure-designed-for-big-data-workloads", "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/" ] }, "investors": [ { "name": "Banyan", "kind": "vc", "rounds": [ "Series A, April 2019" ], "lead": true, "source": "https://venturebeat.com/ai/memverge-raises-24-5-million-for-intel-optane-based-infrastructure-designed-for-big-data-workloads", "quote": "in series A funding led by Banyan", "page": "/investors/banyan/" }, { "name": "Gaorong Capital", "kind": "vc", "rounds": [ "Series A, April 2019", "Series B, May 2020" ], "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/gaorong-capital/" }, { "name": "Jerusalem Venture Partners", "kind": "vc", "rounds": [ "Series A, April 2019", "Series B, May 2020" ], "url": "https://www.jvpvc.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/jerusalem-venture-partners/" }, { "name": "LDV Partners", "kind": "vc", "rounds": [ "Series A, April 2019", "Series B, May 2020" ], "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/ldv-partners/" }, { "name": "Lightspeed Venture Partners", "kind": "vc", "rounds": [ "Series A, April 2019", "Series B, May 2020" ], "url": "https://lsvp.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/lightspeed-venture-partners/" }, { "name": "Northern Light Venture Capital", "kind": "vc", "rounds": [ "Series A, April 2019", "Series B, May 2020" ], "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/northern-light-venture-capital/" }, { "name": "Glory Ventures", "kind": "vc", "rounds": [ "Series B, May 2020" ], "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/glory-ventures/" }, { "name": "Intel Capital", "firm": "Intel", "kind": "corporate", "rounds": [ "Series B, May 2020" ], "lead": true, "url": "https://www.intelcapital.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/intel/" }, { "name": "Cisco Investments", "kind": "corporate", "rounds": [ "Series B, May 2020" ], "url": "https://www.ciscoinvestments.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/cisco-investments/" }, { "name": "NetApp", "kind": "corporate", "rounds": [ "Series B, May 2020" ], "url": "https://www.netapp.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/netapp/" }, { "name": "SK hynix", "kind": "corporate", "rounds": [ "Series B, May 2020" ], "url": "https://www.skhynix.com", "source": "https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/", "page": "/investors/sk-hynix/" }, { "name": "Samsung", "kind": "corporate", "url": "https://www.samsung.com", "source": "https://memverge.ai/company/about", "quote": "Investors (Samsung logo)", "page": "/investors/samsung/" }, { "name": "Broadcom", "kind": "corporate", "url": "https://www.broadcom.com", "source": "https://memverge.ai/company/about", "quote": "Investors (Broadcom logo)", "page": "/investors/broadcom/" }, { "name": "Industry Ventures", "kind": "vc", "url": "https://www.industryventures.com", "source": "https://memverge.ai/company/about", "quote": "Investors (Industry Ventures logo)", "page": "/investors/industry-ventures/" } ] }, "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" } }, "verify": { "accepts": "a page on memmachine.ai or one of its subdomains, or the README at the root of github.com/MemMachine/MemMachine", "badgeUrl": "https://www.anchorterminal.com/badges/memmachine.svg", "body": { "slug": "memmachine", "url": "the page with the badge or the link" }, "docs": "https://www.anchorterminal.com/builders/#verify", "effect": "none, it never changes a grade, rank or review", "endpoint": "https://www.anchorterminal.com/api/v1/verify", "listingUrl": "https://www.anchorterminal.com/tools/memmachine", "mcpTool": "verify_listing", "recheck": "weekly; two failed checks in a row and it lapses, a later pass restores it", "snippets": { "html": "\u003ca href=\"https://www.anchorterminal.com/tools/memmachine\"\u003e\u003cimg src=\"https://www.anchorterminal.com/badges/memmachine.svg\" alt=\"MemMachine on Anchor Terminal\" height=\"20\"\u003e\u003c/a\u003e", "markdown": "[![MemMachine on Anchor Terminal](https://www.anchorterminal.com/badges/memmachine.svg)](https://www.anchorterminal.com/tools/memmachine)", "link": "\u003ca href=\"https://www.anchorterminal.com/tools/memmachine\"\u003eMemMachine on Anchor Terminal\u003c/a\u003e" } } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/tools/memmachine", "json": "https://www.anchorterminal.com/tools/memmachine.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/tools/memmachine.md", "mcp": "https://www.anchorterminal.com/mcp", "pricing": "https://www.anchorterminal.com/tools/memmachine#pricing", "reviews": "https://www.anchorterminal.com/tools/memmachine#reviews", "slim": "https://www.anchorterminal.com/tools/memmachine.min.md" }, "markdown": "## Overview\n\n**Grade C · 58/100 · rank #767 of 1486 · #16 in Agent memory · not agent-ready · confidence medium**\n\n\n## Assessment\n\nMemMachine 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## Facts\n\n| Field | Value |\n| --- | --- |\n| Vendor | MemVerge, Inc. (https://memmachine.ai) |\n| Kind | HTTP API |\n| Category | Agent memory (https://www.anchorterminal.com/categories/agent-memory) |\n| Transport | HTTP, stdio, Streamable HTTP |\n| Auth | None · 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. |\n| Pricing | Freemium (Freemium) · 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. |\n| x402 | No · No x402, MPP or L402 in the repository, the OpenAPI documents or the docs (checked 2026-11-06). |\n| Licence | Apache-2.0 |\n| Tools exposed | 3 |\n| Packages | pypi: `memmachine-server`; pypi: `memmachine-client`; npm: `@memmachine/client` |\n| Source | https://github.com/MemMachine/MemMachine |\n| Docs | https://docs.memmachine.ai |\n| llms.txt | https://docs.memmachine.ai/llms.txt |\n| Last release | 2026-10-08 |\n| GitHub stars | 3,085 (as of 2026-11-06) |\n| npm downloads / week | 28 |\n| PyPI downloads / week | 581 |\n| Surface listed | The self-hosted MemMachine server and its Python and TypeScript clients and MCP server at v0.4.0, read from a clone of github.com/MemMachine/MemMachine, PyPI, docs.memmachine.ai and memmachine.ai's home page and terms on 6 November 2026. The hosted platform was read from its docs only |\n| Memory types | Episodic memory in a graph store, profile (semantic) memory in SQL and short-term working memory, scoped by org, project, group, agent, user and session |\n| Integrations | LangChain, LangGraph, LlamaIndex, CrewAI, AWS Strands, Dify, FastGPT, n8n and OpenClaw |\n| Hosted platform | Console at console.memmachine.ai with usage dashboard and revocable API keys; Public API at api.memmachine.ai with bearer auth |\n| Legal entity | MemVerge, Inc., per the terms of service, under California law |\n| Capabilities | memory.store, memory.search, memory.user, memory.graph, memory.delete |\n| Tags | open-source, self-hosted, hosted, apache-2.0, python, typescript, docker, mcp, openapi, llms-txt, no-auth, pre-1.0 |\n| JSON | https://www.anchorterminal.com/api/v1/tools/memmachine.json |\n\n## Score breakdown (methodology v0.7, October 2026 research run)\n\nAssessed 2026-11-06 from public evidence against the published checklist (https://www.anchorterminal.com/benchmark/#checklist). Confidence: medium. Performance and Task success pending (no score, not in the total); the total is Σ(score × weight) ÷ 80 over the 7 assessed categories. \"This run\" is each category's share of the 100 points.\n\n| Category | Weight | This run | Score (0–100) | Points |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% | 20 | 51 | 10.2 |\n| Performance | 10% | pending | pending | n/a |\n| Schema \u0026 documentation | 13% | 16.2 | 79 | 12.8 |\n| Agent ergonomics | 13% | 16.2 | 65 | 10.6 |\n| Security \u0026 auth | 14% | 17.5 | 41 | 7.2 |\n| Payments \u0026 pricing | 10% | 12.5 | 40 | 5.0 |\n| Task success | 10% | pending | pending | n/a |\n| Maintenance \u0026 community | 7% | 8.8 | 83 | 7.3 |\n| Transparency \u0026 trust (editorial 55, provenance 58) | 7% | 8.8 | 57 | 5.0 |\n| Negative events | up to −15 | up to −15 | none recorded | 0 |\n| **Total** | | | | **58 → C** |\n\n### Why each score\n\n- Reliability 51 (checked 2026-11-06): 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- Performance: Pending. Latency is measured per call by our probes, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until the first probe window closes.\n- Schema \u0026 documentation 79 (checked 2026-11-06): 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- Agent ergonomics 65 (checked 2026-11-06): Searches take limit and filter options for episodic and semantic results (20 of 25). Memories can be listed and filtered by scope (15 of 20). Validation errors are typed; other failures are less clear, as the 429-to-500 issue shows (10 of 20). No idempotency keys or safe-retry guidance found (5 of 20). Python and TypeScript clients and a five-line quick start, once the import is fixed (15). Total 65.\n- Security \u0026 auth 41 (checked 2026-11-06): Framework reading for software the owner runs. The server has no authentication and no security scheme in its OpenAPI document (15 of 30). No read-only mode or confirmation for deletes (5 of 20). No guidance on recalled memories as untrusted text (4 of 15). No audit log on the self-hosted server; the hosted console shows usage (5 of 15). SECURITY.md with GitHub private reporting and a two-business-day acknowledgement, with security-audit and SBOM workflows; no security.txt or certification (12 of 20). Total 41.\n- Payments \u0026 pricing 40 (checked 2026-11-06): 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- Task success: Pending. Task success needs the category task suites run through each tool, which haven't run yet, so this run doesn't score it. Its weight is shared across the assessed categories until then. A data provider's data-quality score is published on its listing now and becomes half of this category when it's scored.\n- Maintenance \u0026 community 83 (checked 2026-11-06): 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- Transparency \u0026 trust 57 (checked 2026-11-06): 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\nFix list, everything this grade says the listing lacks, the biggest gain first (18 items). What it covers is at https://www.anchorterminal.com/fixes/memmachine.md (JSON https://www.anchorterminal.com/fixes/memmachine.json). The whole list for a coding agent comes from `POST https://www.anchorterminal.com/api/v1/fix-list` with `{\"listing\": \"memmachine\", \"plan\": \"read\"}`, free while the beta runs\n\n### What we couldn't check\n\n- The lead said the licence isn't named on the home page, which is right; the repository is Apache-2.0. Enterprise is still marked coming soon.\n- Graded on the self-hosted server the lead named. The hosted platform would need its own pass for pricing, limits and status.\n- unchecked: CI run results and GitHub release notes, because GitHub's API answered with a rate limit.\n- unchecked: the privacy policy at memmachine.ai/privacy-policy/, left to the policy reader.\n- Investors and MemVerge's ownership were not looked for in this pass.\n- Lapse. pypi.org/pypi/\u003cpackage\u003e/json, which PyPI's robots.txt disallows (/pypi/*/json), was fetched for this listing's packages on 6 November 2026 before robots.txt was read. Nothing from those responses is used; versions and release dates come from the allowed release feed at pypi.org/rss/project/\u003cpackage\u003e/releases.xml, and licences and authors from the repository.\n\n### Sources\n\n- repository, README, SECURITY.md, governance, server source (clone): \u003chttps://github.com/MemMachine/MemMachine\u003e (seen 2026-11-06)\n- server OpenAPI: \u003chttps://github.com/MemMachine/MemMachine/blob/main/docs/openapi.json\u003e (seen 2026-11-06)\n- MCP tools source: \u003chttps://github.com/MemMachine/MemMachine/blob/main/packages/server/src/memmachine_server/server/api_v2/mcp.py\u003e (seen 2026-11-06)\n- docs llms.txt: \u003chttps://docs.memmachine.ai/llms.txt\u003e (seen 2026-11-06)\n- platform introduction and API key docs: \u003chttps://docs.memmachine.ai/platform/api_key.md\u003e (seen 2026-11-06)\n- home page: \u003chttps://memmachine.ai/\u003e (seen 2026-11-06)\n- terms of service: \u003chttps://memmachine.ai/terms-of-service/\u003e (seen 2026-11-06)\n- PyPI release feed: \u003chttps://pypi.org/rss/project/memmachine-server/releases.xml\u003e (seen 2026-11-06)\n\n## Score history\n\nEvery move of a score since the listing was graded, newest first, with its cause. A score can't move without an entry here. JSON: https://www.anchorterminal.com/api/v1/tools/memmachine/history.json\n\n- 2026-11-06: graded 58 C (methodology 0.7)\n\n## Who's behind it (provenance 58/100, checked 2026-11-06)\n\n| Check | Finding | Points |\n| --- | --- | --- |\n| Legal entity named | MemVerge, Inc. | 20/20 |\n| Domain age | memmachine.ai, registered 2025-08-15 (1 year) | 3/15 |\n| Endpoint on the vendor's domain | no hosted endpoint | n/a |\n| Terms of service | read, states 4 of the 7 things a reader expects, and has 2 clauses that cost points | 3.4/10 |\n| Privacy policy | read, states 8 of the 8 things a reader expects | 10/10 |\n| Status page | not found | 0/10 |\n| Changelog | published | 10/10 |\n| security.txt | not found | 0/10 |\n| People named | 3 named with their role, none with a public profile | 7/10 |\n| Support route | help pages, a community | 5/5 |\n\nThe 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.\n\nmemmachine.ai/robots.txt allows all crawlers. docs.memmachine.ai carries Content-Signal ai-input=yes.\n\nRDAP gives memmachine.ai a registration date of 15 August 2025.\n\n/.well-known/security.txt returns 404. No status page found.\n\n### Terms and privacy, as read\n\nA reading by a fixed set of rules, each answered with the vendor's own sentence. Not legal advice.\n\n**Terms of service** (https://memmachine.ai/terms-of-service/), read 2026-11-06, gives no date, states 4 of the 7 things a reader expects.\n\n- To know. Restricts automated access (costs points). \"4.4.i use any method to extract data, such as web scraping or web harvesting from the Services, including MemVerge’s account and contact data, AI technology providers’ models, algorithms, or systems other than as permitted;\"\n- To know. Restricts benchmarking or competitive use (costs points). \"4.4.a access the Services, including MemVerge’s AI technology providers’ models, algorithms, or systems to build substantially similar functionality or a competing Services or service, including to train competing AI models (e.g., create synthetic training);\"\n- To know. Requires arbitration or waives class actions. \"IMPORTANT: PLEASE CAREFULLY REVIEW THE ARBITRATION AGREEMENT SET FORTH BELOW, AS IT WILL REQUIRE YOU TO RESOLVE DISPUTES WITH MEMVERGE ON AN INDIVIDUAL BASIS THROUGH FINAL AND BINDING ARBITRATION AND WAIVING YOUR RIGHT TO A CLASS ACTION.\"\n- Not found in the text. Gives the date it was last updated.\n- Names the governing law or courts. The law of the State of California.\n- Not found in the text. Says how changes to the terms are announced.\n- Not found in the text. Refers to a service level or uptime commitment.\n\n**Privacy policy** (https://memmachine.ai/privacy-policy/), read 2026-11-06, dated 2026-05-20, states 8 of the 8 things a reader expects.\n\n- Gives the date it was last updated. Last updated 2026-05-20.\n- Says how long data is kept. For as long as needed, with no period named.\n- Says whether personal data is sold or shared for advertising. Says it does not sell personal data.\n- Gives a privacy contact. privacy@memverge.com.\n- Says where data is transferred or stored. Relies on standard contractual clauses.\n\n## Humans behind the project (researched 2026-11-06 from public pages, not part of the grade)\n\n### Key people\n\n- Charles Fan, Co-founder and CEO, MemVerge\n- Shuki Bruck, Co-founder and Chairman, MemVerge\n- Shu Wang, Chief Technology Officer, MemVerge\n- Note: MemMachine is MemVerge's open-source memory layer: memmachine.ai names MemVerge as its incubator and the repository's GOVERNANCE.md describes maintainer roles without naming people. The people listed are MemVerge's, from its leadership page read on 6 November 2026, which calls Charles Fan co-founder and CEO and Shuki Bruck co-founder and Chairman, and names Shu Wang as CTO. VentureBeat (2 April 2019) says Fan cofounded the company with Caltech colleagues Shuki Bruck and Yue Li; Yue Li's current role isn't on a first-hand page, so he isn't listed. No MemMachine product lead was named first-hand. Investors come from VentureBeat's report of the $24.5M Series A (April 2019, led by Banyan), MemVerge's press release of May 2020 as carried by StorageNewsletter ($19M led by Intel Capital, called a Series B in the headline), and the Investors logos on memverge.ai/company/about, which add Samsung, Broadcom and Industry Ventures without a round. No later round, total raised or valuation was found on memverge.ai (its news page lists no funding release) or in a search.\n- MemVerge, Inc.: GitHub https://github.com/MemMachine\n\n### Ownership and investors\n\n- Backed by: Banyan, Gaorong Capital, Jerusalem Venture Partners, LDV Partners, Lightspeed Venture Partners, Northern Light Venture Capital, Glory Ventures, Intel, Cisco Investments, NetApp, SK hynix, Samsung, Broadcom, Industry Ventures\n\n### Getting support\n\n- Discord: https://discord.gg/usydANvKqD\n- Help: https://docs.memmachine.ai\n- Help: https://github.com/MemMachine/MemMachine/issues\n- Sources: https://memmachine.ai/, https://memmachine.ai/terms-of-service/, https://github.com/MemMachine/MemMachine/blob/main/GOVERNANCE.md, https://memverge.ai/company/leadership, https://memverge.ai/company/about, https://venturebeat.com/ai/memverge-raises-24-5-million-for-intel-optane-based-infrastructure-designed-for-big-data-workloads, https://www.storagenewsletter.com/2020/05/13/memverge-raised-19-million-in-series-b-from-new-investors-including-intel-capital-cisco-investments-netapp-and-sk-hynix/\n\n## Live (updated 2026-11-07 16:00 UTC)\n\n- github `MemMachine/MemMachine` v0.4.0, released 2026-10-08\n- npm `@memmachine/client` 0.3.9\n- pypi `memmachine-client` 0.4.0, released 2026-10-08\n- pypi `memmachine-server` 0.4.0, released 2026-10-08\n- security.txt: none\n- Watching privacy \u003chttps://memmachine.ai/privacy-policy/\u003e\n- Watching terms \u003chttps://memmachine.ai/terms-of-service/\u003e\n- Always current: https://www.anchorterminal.com/api/v1/live/memmachine.json\n\n## Probe metrics\n\nNot measured yet. Our benchmark probes haven't run, so there's no availability, latency or error rate from a run and Performance is pending. Live uptime, where we poll the endpoint, is under Live and doesn't change the score.\n\n## Strengths\n\n- Apache-2.0 server and clients on PyPI, npm and Docker, self-hostable with Ollama or AWS Bedrock\n- OpenAPI documents for the server (54 operations) and the hosted platform (12), every operation described\n- MCP server over stdio or HTTP with three tools, add_memory, search_memory and delete_memory\n- SECURITY.md with private reporting and a two-business-day acknowledgement, plus security-audit and SBOM workflows\n- Hosted platform terms commit to 99.5% availability\n\n## Weaknesses\n\n- Version 0.4.0 of 6 October 2026, pre-1.0, with no changelog file in the repository\n- The self-hosted server has no authentication and no security scheme in its OpenAPI document\n- The README's quick start imports with `from memmachine_client import import MemMachineClient`, which is invalid Python\n- 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\n- No prices for the hosted platform, and the Enterprise edition is marked coming soon\n\n\n\n## Before you call it (notes for agents)\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## Connect\n\nInstall:\n\n```bash\npip install memmachine-server memmachine-client\n```\n\nFirst request:\n\n```bash\ncurl http://localhost:8080/api/v2/health\n```\n\nThrough letme: https://letme.dev/memmachine. letme answers with the pick and how to call it direct. How it works: https://www.anchorterminal.com/letme/index.md\n\n## Similar tools\n\nRanked by shared capabilities, then score. Same-category tools with no shared capability key are listed last.\n\n| Tool | Grade | Score | Rank | Shared capabilities | x402 | Markdown |\n| --- | --- | --- | --- | --- | --- | --- |\n| Zep | BB | 71 | 175 | memory.store, memory.search, memory.graph, memory.user, memory.delete | no | https://www.anchorterminal.com/tools/zep.md |\n| past.dev | B | 69.8 | 223 | memory.store, memory.search, memory.user, memory.graph, memory.delete | no | https://www.anchorterminal.com/tools/past-dev.md |\n| Supermemory API + MCP | C | 59.6 | 692 | memory.store, memory.search, memory.graph, memory.user, memory.delete | no | https://www.anchorterminal.com/tools/supermemory.md |\n| Hy Memory | D | 53.8 | 931 | memory.store, memory.search, memory.user, memory.graph, memory.delete | no | https://www.anchorterminal.com/tools/hy-memory.md |\n| Mem0 Platform + MCP | E | 40.1 | 1310 | memory.store, memory.search, memory.graph, memory.user, memory.delete | no | https://www.anchorterminal.com/tools/mem0.md |\n| Amazon Bedrock AgentCore Memory | A | 79.7 | 17 | memory.store, memory.search, memory.user, memory.delete | no | https://www.anchorterminal.com/tools/agentcore-memory.md |\n\n## Panel reviews (0)\n\nReviewed by the Anchor panel (https://www.anchorterminal.com/reviewers/index.md): .\n\nDesk reviews, written from public documentation, pricing, terms, source and status history on 1 October 2026. No calls made. For a desk review, the outcome says whether the reviewer's questions could be answered from public material: success, partial or failure. How reviews work: https://www.anchorterminal.com/reviews/how-it-works.md\n\n## Notable\n\n- v0.4.0 tagged on 6 October 2026 and published to PyPI on 8 October, with pre-releases v0.4.1-dev0 on 15 October and v0.4.1-a1 on 5 November (source: \u003chttps://pypi.org/rss/project/memmachine-server/releases.xml\u003e)\n- The server's OpenAPI document (MemMachine API 0.3.10) has 54 operations and no security scheme; the platform's (MemMachine Public API 0.1.0, api.memmachine.ai) has 12 with bearer auth. Every operation in both has a description (source: \u003chttps://github.com/MemMachine/MemMachine/tree/main/docs\u003e)\n- The MCP server registers three tools, add_memory, search_memory and delete_memory, over stdio or HTTP (source: \u003chttps://github.com/MemMachine/MemMachine/blob/main/packages/server/src/memmachine_server/server/api_v2/mcp.py\u003e)\n- The home page says MemVerge incubated the project and that an Enterprise version is coming soon (source: \u003chttps://memmachine.ai/\u003e)\n- The terms name MemVerge, Inc. under California law, commit to 99.5% availability for hosted services and forbid scraping the services (source: \u003chttps://memmachine.ai/terms-of-service/\u003e)\n\n- #16 of 26 in 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## Compare\n\n- [Amazon Bedrock AgentCore Memory vs MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md): A 79.7 vs C 58\n- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md): BB 76.9 vs C 58\n- [claude-mem vs MemMachine](https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.md): C 54.6 vs C 58\n- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md): D 47.7 vs C 58\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md): B 69.4 vs C 58\n- [Agent Platform Memory Bank vs MemMachine](https://www.anchorterminal.com/compare/google-memory-bank-vs-memmachine.md): B 65.6 vs C 58\n- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md): D 50.1 vs C 58\n- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md): D 47.8 vs C 58\n- [Honcho vs MemMachine](https://www.anchorterminal.com/compare/honcho-vs-memmachine.md): C 61.6 vs C 58\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md): D 53.8 vs C 58\n- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md): D 47.7 vs C 58\n- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md): C 55.7 vs C 58\n- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md): E 40.1 vs C 58\n- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-vs-memori.md): C 58 vs E 44.2\n- [MemMachine vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/memmachine-vs-memory-reference-server.md): C 58 vs C 58.8\n- [MemMachine vs MemPalace](https://www.anchorterminal.com/compare/memmachine-vs-mempalace.md): C 58 vs C 60.7\n- [MemMachine vs past.dev](https://www.anchorterminal.com/compare/memmachine-vs-past-dev.md): C 58 vs B 69.8\n- [MemMachine vs Supermemory API + MCP](https://www.anchorterminal.com/compare/memmachine-vs-supermemory.md): C 58 vs C 59.6\n- [MemMachine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md): C 58 vs D 50.9\n- [MemMachine vs Tokenrip](https://www.anchorterminal.com/compare/memmachine-vs-tokenrip.md): C 58 vs C 60.3\n- [MemMachine vs Zep](https://www.anchorterminal.com/compare/memmachine-vs-zep.md): C 58 vs BB 71\n- [AI Memory vs MemMachine](https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.md): B 65 vs C 58\n- [Context Mode Engine vs MemMachine](https://www.anchorterminal.com/compare/context-mode-vs-memmachine.md): C 54.6 vs C 58\n- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.md): BB 70.6 vs C 58\n\n## Verify this listing\n\nFor the vendor. The badge or a plain link to this page verifies the listing, from a page on memmachine.ai or one of its subdomains, or the README at the root of github.com/MemMachine/MemMachine. It shows the listing is the vendor's and that the vendor knows it's here, and it never changes a grade, rank or review. The vendor sends the page's address to `POST https://www.anchorterminal.com/api/v1/verify` as `{\"slug\": \"memmachine\", \"url\": \"…\"}`, or calls the `verify_listing` tool at https://www.anchorterminal.com/mcp. We fetch the page once, then again every week; two failed checks in a row and the verification lapses, and a later pass restores it. What we check: https://www.anchorterminal.com/builders/index.md#verify\n\nHTML badge:\n\n```html\n\u003ca href=\"https://www.anchorterminal.com/tools/memmachine\"\u003e\u003cimg src=\"https://www.anchorterminal.com/badges/memmachine.svg\" alt=\"MemMachine on Anchor Terminal\" height=\"20\"\u003e\u003c/a\u003e\n```\n\nMarkdown badge, for a README:\n\n```markdown\n[![MemMachine on Anchor Terminal](https://www.anchorterminal.com/badges/memmachine.svg)](https://www.anchorterminal.com/tools/memmachine)\n```\n\nPlain link:\n\n```html\n\u003ca href=\"https://www.anchorterminal.com/tools/memmachine\"\u003eMemMachine on Anchor Terminal\u003c/a\u003e\n```\n\n## Share this listing\n\nFor the vendor. Sharing assets for social media, two PNGs of 1200 × 630 that say MemMachine is listed on Anchor Terminal, with the vendor's logo and this page's address and no grade or score.\n\n- Dark: https://www.anchorterminal.com/assets/share/memmachine-dark.png\n- Light: https://www.anchorterminal.com/assets/share/memmachine-light.png\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": "Terminal", "url": "https://www.anchorterminal.com/tools/" }, { "name": "Agent memory", "url": "https://www.anchorterminal.com/categories/agent-memory" }, { "name": "MemMachine", "url": "" } ], "description": "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.", "facts": [ "rank #767 of 1486", "None auth", "0 desk reviews" ], "h1": "MemMachine", "image": "https://www.anchorterminal.com/assets/og/tools-memmachine.png", "path": "/tools/memmachine", "published": "2026-10-01", "section": "tools", "title": "MemMachine review (2026): pricing, alternatives and grade C", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/tools/memmachine" }, "tokens": { "markdown": 6600, "slim": 1330 }, "version": 1 }