{ "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": 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" ], "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 TencentDB Agent Memory's 50.9 (D), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on payments \u0026 pricing and transparency \u0026 trust.", "b": { "slug": "tencentdb-agent-memory", "name": "TencentDB Agent Memory", "vendor": "Tencent Cloud", "vendorUrl": "https://github.com/TencentCloud/TencentDB-Agent-Memory", "kind": "http-api", "category": "agent-memory", "summary": "TencentDB Agent Memory is Tencent Cloud's MIT-licensed, self-hosted memory stack for coding agents. A proxy injects layered conversation memory, skills, wiki pages and code graphs into each request, with a team panel and HTTP API over SQLite.", "url": "https://www.anchorterminal.com/tools/tencentdb-agent-memory", "markdownUrl": "https://www.anchorterminal.com/tools/tencentdb-agent-memory.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/tencentdb-agent-memory.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/tencentdb-agent-memory.json", "dns": "tencentdb-agent-memory.grade.anchorterminal.com", "repo": "https://github.com/TencentCloud/TencentDB-Agent-Memory", "license": "MIT", "transports": [ "http" ], "packages": [ { "registry": "oci", "name": "agentmemory/memory-core" }, { "registry": "oci", "name": "agentmemory/memory-hub" }, { "registry": "oci", "name": "agentmemory/memory-proxy" }, { "registry": "npm", "name": "@tencentdb-agent-memory/memory-tencentdb" }, { "registry": "npm", "name": "@tencentdb-agent-memory/memory-sdk-ts-v2" } ], "auth": "api-key", "authNotes": "Self-hosted, with no Tencent account. Agents reach memory through the proxy with a per-user key (`sk-mem-...`) sent as the Anthropic or OpenAI auth token, which the proxy checks against Memory Core. Users can hold several revocable keys, and the panel can log in through an OAuth2 identity provider. Memory Core's own bearer gate (`MEMORY_CORE_GATEWAY_API_KEY`) is empty by default, data-plane routes need only the `x-tdai-service-id` header, and the proxy's admin routes have no authentication (https://github.com/TencentCloud/TencentDB-Agent-Memory/blob/master/MemoryCore/v3-api-memorycore-doc.md).", "pricing": "free", "pricingNotes": "Free under MIT, with nothing to buy and no signup. The owner pays for the LLM calls that extract L1 to L3 memory, build wiki pages and code graphs and answer through the proxy, at whichever OpenAI-compatible or Anthropic-compatible provider is configured (https://github.com/TencentCloud/TencentDB-Agent-Memory/blob/feat/server_team/INSTALL.md).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the README, install guide, API references or changelog read on 30 October 2026. Self-hosted open-source software with no paid endpoint.", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 2218, "pypiWeekly": null, "asOf": "2026-10-30" }, "docsUrl": "https://github.com/TencentCloud/TencentDB-Agent-Memory/blob/feat/server_team/INSTALL.md", "openapi": "https://github.com/TencentCloud/TencentDB-Agent-Memory/blob/feat/server_team/MemoryKnowledge/openapi.yaml", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete", "knowledge.search" ], "tags": [ "self-hosted", "open-source", "local", "docker", "typescript", "python", "free", "no-card", "mit", "openai-compatible", "skills", "beta" ], "lastRelease": "2026-10-26", "graded": true, "anchor": { "graded": true, "score": 50.9, "grade": "D", "agentReady": false, "rank": 1040, "ranked": true, "rankOf": 1486, "categoryRank": 20, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 68, "maintenance": 70, "payments": 60, "reliability": 51, "schema": 61, "security": 35, "transparency": 68 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": -6, "negativeNotes": [ "-3, a released fix of the project's own described flaw with no advisory. Memory Core's asset/get and asset/list ran with an unrestricted admin view, so any team member holding a valid user key could list and read other members' private assets, which the commit calls horizontal privilege escalation. Fixed on 21 September 2026 and released in 2.0.2 on 9 October 2026, with no advisory or changelog line found (https://github.com/TencentCloud/TencentDB-Agent-Memory/commit/5017e2bb927c65bd8302af2d984b04db46303f1b).", "-3, a security fix in no release. A commit of 28 October 2026 on the default branch scopes Agent and Task get and list reads to the caller, with regression tests for outsiders reading private Agents. The latest release, 2.0.3 of 26 October 2026, doesn't carry it on 4 November (https://github.com/TencentCloud/TencentDB-Agent-Memory/commit/afadb9aade42e524a350fcb38a2092f56b77c7c1)." ], "verdict": "A self-hosted team memory stack with layered recall, per-asset visibility and ACLs, documented HTTP APIs and frequent releases, 2.0.1 to 2.0.3 since August. The default deployment publishes its ports on all interfaces with the core's bearer gate off, the proxy's admin routes have no authentication, and two 2026 access-control fixes came without advisories.", "bestFor": "Small teams that run several coding agents on a host they control and want shared, permissioned memory, skills and code context injected through a proxy.", "strengths": [ "MIT licence in the repository and on every npm package, with three multi-architecture Docker images on Docker Hub's agentmemory account", "Layered recall from L3 persona and L2 scenarios down to L1 atoms and raw L0 conversation, with hybrid BM25 and vector search", "Assets are private by default, with team, restricted (user, role and agent ACLs) and agent visibility, and per-user revocable keys", "Coding agents join through the proxy by changing a base URL, for Claude Code, Codex, CodeBuddy, OpenCode, DeepSeek Harness and others", "Six releases from 2.0.1-beta.1 on 13 August to 2.0.3 on 26 October 2026, each in a dated Keep a Changelog file" ], "weaknesses": [ "The core's bearer gate is off by default, and the deploy notes say enabling it breaks the proxy's auth and session setup", "Data-plane deletes and chat-memory clears make no user-level check, trusting the bearer gate and `x-tdai-service-id`, per the API reference", "The proxy's rate-limit routes (GET, PUT, DELETE) and session admin routes have no authentication, per its own API reference", "Asset reads were scoped to the caller only in 2.0.2, with no advisory, and Agent and Task reads only in an unreleased commit of 28 October 2026", "The npm OpenClaw plugin's postinstall rewrites the installed OpenClaw's files with sed, output silenced, unless skipped" ], "agentNotes": [ "Set `MEMORY_CORE_GATEWAY_API_KEY`, `KNOWLEDGE_SERVICE_KEY` and a non-default admin key before exposing ports 8420, 8424, 8096 or 8125 beyond the host", "In headless runs send `x-team-id`, `x-agent-id` and `x-task-id` headers to the proxy. Without all three it falls back to an interactive picker and skips memory", "Expect every proxied turn to be stored. The proxy records upstream messages and model replies to Memory Core, and injected memory lands in your system prompt", "Check `data.valid` on `/v3/meta/auth/verify` and `data.isError` on `/v3/tools/call`. Both can fail inside a success envelope", "Retry `/v3/session/add` only on 500, 503 or a network error. The API reference says it isn't idempotent and writes a new object each call", "Build from the default branch past 2.0.3, or wait for the next release, before giving several users one Memory Core. Agent and Task reads were unscoped until 28 October" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 50.9 } ], "editorialScores": { "ergonomics": 68, "maintenance": 70, "payments": 60, "reliability": 51, "schema": 61, "security": 35, "transparency": 61 }, "provenanceScore": 75, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "git clone https://github.com/TencentCloud/TencentDB-Agent-Memory.git\ncd TencentDB-Agent-Memory/deploy/global-images\ncp .env.example .env\n./start-all.sh", "http": "export ANTHROPIC_BASE_URL=http://127.0.0.1:8096/claude-code/default\nexport ANTHROPIC_AUTH_TOKEN='\u003csk-mem- user key\u003e'\nclaude --model \u003cPROXY_UPSTREAM_MODEL\u003e" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/tencentdb-agent-memory" }, "sameCompany": [ "hy-memory", "hy3" ], "area": "agent-runtime", "provenance": { "legalEntity": "Tencent", "domain": "tencent.com", "domainRegistered": "1998-09-14", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "https://github.com/TencentCloud/TencentDB-Agent-Memory/blob/feat/server_team/CHANGELOG.md", "securityTxt": "none", "checked": "2026-11-04", "notes": [ "LICENSE reads 'Copyright (C) 2026 Tencent. All rights reserved.' above the MIT text, and the README footer reads '© TencentDB Agent Memory Team'. No fuller legal name was found.", "The repository is in GitHub's TencentCloud organisation. The 2.0.0 changelog and main-branch links still use github.com/Tencent/TencentDB-Agent-Memory, and raw files answer at both paths. The project has no website of its own. RDAP at Verisign gives tencent.com a registration date of 14 September 1998.", "No terms or privacy policy applies beyond the MIT licence. Self-hosted, so no status page.", "security.txt returns 404 on www.tencent.com. www.tencentcloud.com answers robots.txt with a bot check, so that host is treated as blocked. No branch has SECURITY.md; CONTRIBUTING.md names agentmemory@tencent.com for vulnerability reports.", "github.com pages and api.github.com weren't read (closed by the session's proxy). The repository was read from a clone on 4 November 2026. Its default branch is now feat/server_team, and the master branch the 30 October check read no longer exists.", "cloud.tencent.com allows general crawling in robots.txt, but its service agreement answered with a bot check on 4 November 2026, so Tencent Cloud's terms weren't read and nothing else on that host was requested." ], "score": 75 }, "requirements": { "setupChecked": true, "complianceChecked": true, "card": "no", "freeTier": true, "minutes": 30, "credential": "api-key", "hosting": [ "self-hosted" ], "euResidency": "unknown", "trainsOnData": "no", "zeroRetention": "unknown", "selfHost": "yes" }, "pageJsonUrl": "https://www.anchorterminal.com/tools/tencentdb-agent-memory.json", "live": { "slug": "tencentdb-agent-memory", "versions": [ { "registry": "github", "name": "TencentCloud/TencentDB-Agent-Memory", "version": "v2.0.3", "released": "2026-10-26", "seenAt": "2026-11-07T00:11:03.066814774Z" }, { "registry": "npm", "name": "@tencentdb-agent-memory/memory-sdk-ts-v2", "version": "1.0.0-beta.1", "seenAt": "2026-11-07T00:11:01.36963606Z" }, { "registry": "npm", "name": "@tencentdb-agent-memory/memory-tencentdb", "version": "1.0.3", "seenAt": "2026-11-07T00:11:00.859500824Z" } ], "githubStars": 30577, "npmWeekly": 2589, "securityTxt": { "url": "https://tencent.com/.well-known/security.txt", "state": "unknown", "checkedAt": "2026-11-07T16:01:57.23927149Z" }, "domain": { "domain": "tencent.com", "registered": "1998-09-14", "source": "https://rdap.verisign.com/com/v1/domain/tencent.com", "checkedAt": "2026-11-01T14:16:02.443593707Z" }, "pages": [ { "url": "https://raw.githubusercontent.com/TencentCloud/TencentDB-Agent-Memory/feat/server_team/CHANGELOG.md", "kind": "changelog", "status": 304, "checkedAt": "2026-11-07T14:19:35.679034443Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e213f9445c48" }, { "url": "https://raw.githubusercontent.com/TencentCloud/TencentDB-Agent-Memory/master/CHANGELOG.md", "kind": "changelog", "status": 304, "checkedAt": "2026-11-04T08:32:32.15651231Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e213f9445c48" } ], "github": { "repo": "tencentcloud/tencentdb-agent-memory", "checkedAt": "2026-11-02T08:23:41.922514512Z", "stars": 30347, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-28T14:33:21Z", "openIssues": 312, "openPRs": 578, "issuesOpened90d": 347, "issuesClosed90d": 99, "prsMerged90d": 77, "replies": { "sampled": 25, "unanswered": 25 } }, "updatedAt": "2026-11-07T16:01:57.23927149Z" } }, "edges": [ { "by": 20, "category": "payments", "leads": "tencentdb-agent-memory", "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": "Read with the self-hosted rule. MIT software with nothing to buy from Tencent, so 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 (0). Memory extraction, wiki and code-graph building and the proxied model are paid to whichever LLM provider the owner configures." }, "scores": { "a": 40, "b": 60 } }, { "by": 18, "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": "API reading for a self-hosted HTTP service. The Knowledge service has an OpenAPI 3.0.3 file of 28 paths with no security scheme. Memory Core's 109 endpoints and the proxy's routes are described only in Markdown references, and the proxy's main LLM paths are outside them (10 of 25). No website and no llms.txt. The docs are Markdown in the repository and readable raw (5 of 10). Each Core endpoint states what it does, its limits and caveats, such as which deletes skip user checks, and Knowledge's tool list marks its tools read-only. The API references and the changelog are in Chinese; the README and install guide are in English (11 of 20). Zod-checked inputs with bounds (1 to 100 messages, 8,192 characters per message, `limit` up to 100) and enums for atom types, but the reference records that `version` comes back as a string from `atomic/update` and a number from `query` (10 of 15). Worked request and response examples per endpoint and error tables per module, with the three different error-message formats set out (12 of 15). `/v3` paths with v1 and v2 routes listed as deprecated, and a dated public changelog for every release since 0.1.0 (13 of 15)." }, "scores": { "a": 79, "b": 61 } }, { "by": 13, "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": "Release 2.0.3 on 26 October 2026 by the changelog and its tag, 9 days before this check (30). Six changelog releases in the 90 days from 6 August, 2.0.1-beta.1 (13 August), 2.0.1 (25 August), 2.0.2-beta.1 (7 September), 2.0.2 (9 October), 2.0.3-beta.1 (13 October) and 2.0.3, with image tags v1.0.2 (8 September) and v1.0.3 (22 September) between. The three stable releases 2.0.1, 2.0.2 and 2.0.3 meet the line without the pre-releases, which this run doesn't count (20). GitHub issues and pull requests weren't readable, so reply times weren't judged. The plugin changelog credits fixes to numbered issues and outside pull requests, and the README says issues get a reply within 24 hours, which we couldn't check. A workflow added on 28 October posts an automatic acknowledgement on new external pull requests, which isn't a maintainer reply (10 of 25). Official TypeScript and Python SDKs exist but only as betas, the TypeScript one last published on 14 August 2026, and the Python package name differs between the changelog and its pyproject. No MCP server, so the registry line doesn't apply (6 of 15). npm packages carry registry signatures but no provenance attestations, the deploy pulls `:latest` images, the one CI workflow skips the tests and doesn't run on the default branch, and 2.0.3 fixed a Knowledge service broken by OpenTelemetry dependency drift (4 of 10)." }, "scores": { "a": 83, "b": 70 } }, { "by": 11, "category": "transparency", "leads": "tencentdb-agent-memory", "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": "MIT on both branches and in npm metadata, with the codegraph and Hermes Agent code it reuses credited in the README (30 of 30). The README says new chat memory and skills are private by default and sets out what each visibility means. No privacy statement says what each layer keeps or for how long. The proxy records every turn's upstream messages and model replies, the plugin's L0 and L1 retention defaults to never, `chat-memory/clear` empties L0, L1 and profile content while keeping the asset, and switching storage backends leaves data behind (12 of 30). v1 and v2 routes are marked deprecated with removal 'planned' and no date, and known limitations promise fixes 'in the next version' without dates (6 of 20). The plugin's metrics reporting is off by default and writes to local logs only, and ClickHouse analytics are off by default and documented. Core depends on OpenTelemetry exporters, and we didn't audit whether anything exports by default. The Hermes Docker image's default model endpoint is Tencent Cloud LKE, which the README states (13 of 20)." }, "scores": { "a": 57, "b": 68 } }, { "by": 6, "category": "security", "leads": "memmachine", "name": "Security \u0026 auth", "reasons": { "a": "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.", "b": "Read as self-hosted software with a network API. Per-user `sk-mem-` keys, several per user and revocable, and OAuth2 for panel login. Against that, Memory Core's bearer gate is off by default and the .env template says setting it breaks the proxy's auth and session setup, the data plane takes team, agent and user IDs from the caller and needs only `x-tdai-service-id`, the proxy's rate-limit and session admin routes have no authentication, `/v3/instance/destroy` rests on the same unset bearer, the deploy README's defaults include an `admin` key, and the start scripts publish every port on all interfaces (8 of 30). Private-by-default assets with team, restricted and agent visibility, ACLs by user, role and agent, and read-only Knowledge tools. Data-plane deletes and `chat-memory/clear` make no user-level check and nothing asks for confirmation. Asset reads were scoped to the caller only in 2.0.2, and Agent and Task reads only in an unreleased commit of 28 October (8 of 20). The proxy injects stored memory, skills, imported documents and code into the system prompt, and we found no guidance on prompt injection or memory poisoning. Personal skills are private until shared after review (3 of 15). Participation logs, memory-generation logs and the raw L0 record let the operator trace what was written, and per-call analytics to ClickHouse is available but off by default (9 of 15). CONTRIBUTING.md asks for vulnerability reports by email to agentmemory@tencent.com rather than public issues, with no acknowledgement time, so a disclosure route without a stated time (7). No SECURITY.md on any branch, no security.txt on www.tencent.com, and no bounty or audit named. The npm plugin's postinstall runs a bash script that rewrites OpenClaw's installed files, with output sent to /dev/null. Two access-control fixes in 2026 are under the negative events." }, "scores": { "a": 41, "b": 35 } } ], "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "MemVerge, Inc.", "b": "Tencent Cloud", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "HTTP, stdio, Streamable HTTP", "b": "HTTP", "name": "Transports" }, { "a": "None", "b": "API key", "name": "Auth" }, { "a": "Freemium", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "MIT", "name": "Licence" }, { "a": "3", "b": "none", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "no", "name": "llms.txt" }, { "a": "2026-10-08", "b": "2026-10-26", "name": "Last release" }, { "a": "no date given", "b": "no document linked", "name": "Terms last updated" }, { "a": "2026-05-20", "b": "no document linked", "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": "2.2k npm/wk", "name": "Popularity" } ], "faq": [ { "answer": "MemMachine scores 58 (C) on agent readiness against TencentDB Agent Memory's 50.9 (D), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on payments \u0026 pricing and transparency \u0026 trust.", "question": "Which is better for AI agents, MemMachine or TencentDB Agent Memory?" }, { "answer": "MemMachine needs no key. TencentDB Agent Memory needs an API key.", "question": "Do MemMachine and TencentDB Agent Memory need an API key?" }, { "answer": "MemMachine runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for TencentDB Agent Memory.", "question": "Can an agent call MemMachine and TencentDB Agent Memory without installing anything?" }, { "answer": "Yes. MemMachine is open source (Apache-2.0). TencentDB Agent Memory is open source (MIT).", "question": "Are MemMachine and TencentDB Agent Memory open source?" } ], "goodFor": [ { "aheadOn": [ "Schema \u0026 documentation, 79 against 61", "Security \u0026 auth, 41 against 35", "Maintenance \u0026 community, 83 against 70" ], "also": [ "No key needed to call it", "Runs on your own machine", "No incidents deducted, where TencentDB Agent Memory loses 6 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, 60 against 40", "Transparency \u0026 trust, 68 against 57" ], "also": [ "Free to start without a card" ], "goodFor": "Small teams that run several coding agents on a host they control and want shared, permissioned memory, skills and code context injected through a proxy.", "slug": "tencentdb-agent-memory", "watchFor": "The core's bearer gate is off by default, and the deploy notes say enabling it breaks the proxy's auth and session setup" } ], "history": { "memmachine": null, "tencentdb-agent-memory": [ { "causes": [ "security", "correction" ], "date": "2026-11-04", "delta": -5.1, "from": 56, "fromGrade": "C", "to": 50.9, "toGrade": "D" } ] }, "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-tencentdb-agent-memory.json", "title": "Amazon Bedrock AgentCore Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Basic Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/basic-memory-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "claude-mem vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/claude-mem-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Cognee vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/cognee-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "EverOS vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/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-tencentdb-agent-memory.json", "title": "Agent Platform Memory Bank vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/google-memory-bank-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Graphiti vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/graphiti-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Hindsight vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/hindsight-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Honcho vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/honcho-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Hy Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/hy-memory-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "LangMem vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/langmem-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "LocalGhost vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/localghost-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Mem0 Platform + MCP vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/mem0-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/memmachine-vs-memori.json", "title": "MemMachine vs Memori", "url": "https://www.anchorterminal.com/compare/memmachine-vs-memori" }, { "json": "https://www.anchorterminal.com/compare/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-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-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/memory-reference-server-vs-tencentdb-agent-memory.json", "title": "Memory (MCP reference server) vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/memory-reference-server-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/mempalace-vs-tencentdb-agent-memory.json", "title": "MemPalace vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/mempalace-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/past-dev-vs-tencentdb-agent-memory.json", "title": "past.dev vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/past-dev-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/supermemory-vs-tencentdb-agent-memory.json", "title": "Supermemory API + MCP vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/supermemory-vs-tencentdb-agent-memory" }, { "json": "https://www.anchorterminal.com/compare/tencentdb-agent-memory-vs-tokenrip.json", "title": "TencentDB Agent Memory vs Tokenrip", "url": "https://www.anchorterminal.com/compare/tencentdb-agent-memory-vs-tokenrip" }, { "json": "https://www.anchorterminal.com/compare/tencentdb-agent-memory-vs-zep.json", "title": "TencentDB Agent Memory vs Zep", "url": "https://www.anchorterminal.com/compare/tencentdb-agent-memory-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-tencentdb-agent-memory.json", "title": "AI Memory vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/ai-memory-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Context Mode Engine vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/context-mode-vs-tencentdb-agent-memory" }, { "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-tencentdb-agent-memory.json", "title": "Graphicle vs TencentDB Agent Memory", "url": "https://www.anchorterminal.com/compare/graphicle-vs-tencentdb-agent-memory" } ], "panel": null, "scores": [ { "by": 0, "edge": "", "key": "reliability", "memmachine": 51, "name": "Reliability", "tencentdb-agent-memory": 51, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 18, "edge": "memmachine", "key": "schema", "memmachine": 79, "name": "Schema \u0026 documentation", "tencentdb-agent-memory": 61, "weight": 13 }, { "by": 3, "edge": "tencentdb-agent-memory", "key": "ergonomics", "memmachine": 65, "name": "Agent ergonomics", "tencentdb-agent-memory": 68, "weight": 13 }, { "by": 6, "edge": "memmachine", "key": "security", "memmachine": 41, "name": "Security \u0026 auth", "tencentdb-agent-memory": 35, "weight": 14 }, { "by": 20, "edge": "tencentdb-agent-memory", "key": "payments", "memmachine": 40, "name": "Payments \u0026 pricing", "tencentdb-agent-memory": 60, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 13, "edge": "memmachine", "key": "maintenance", "memmachine": 83, "name": "Maintenance \u0026 community", "tencentdb-agent-memory": 70, "weight": 7 }, { "by": 11, "edge": "tencentdb-agent-memory", "key": "transparency", "memmachine": 57, "name": "Transparency \u0026 trust", "tencentdb-agent-memory": 68, "weight": 7 } ], "summary": "MemMachine scores 58 (C) on agent readiness against TencentDB Agent Memory's 50.9 (D), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on payments \u0026 pricing and transparency \u0026 trust. 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.", "tencentdb-agent-memory": "A self-hosted team memory stack with layered recall, per-asset visibility and ACLs, documented HTTP APIs and frequent releases, 2.0.1 to 2.0.3 since August. The default deployment publishes its ports on all interfaces with the core's bearer gate off, the proxy's admin routes have no authentication, and two 2026 access-control fixes came without advisories." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory", "json": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.min.md" }, "markdown": "MemMachine scores 58 (C) on agent readiness against TencentDB Agent Memory's 50.9 (D), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on payments \u0026 pricing and transparency \u0026 trust. Both do agent memory.\n\n- MemMachine: grade C, 58/100, rank #767 of 1486. Markdown https://www.anchorterminal.com/tools/memmachine.md · JSON https://www.anchorterminal.com/api/v1/tools/memmachine.json\n- TencentDB Agent Memory: grade D, 50.9/100, rank #1040 of 1486. Markdown https://www.anchorterminal.com/tools/tencentdb-agent-memory.md · JSON https://www.anchorterminal.com/api/v1/tools/tencentdb-agent-memory.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- Schema \u0026 documentation, 79 against 61\n- Security \u0026 auth, 41 against 35\n- Maintenance \u0026 community, 83 against 70\n\nAlso in its favour:\n- No key needed to call it\n- Runs on your own machine\n- No incidents deducted, where TencentDB Agent Memory loses 6 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### TencentDB Agent Memory (D)\n\nGood for: Small teams that run several coding agents on a host they control and want shared, permissioned memory, skills and code context injected through a proxy.\n\nAhead on:\n- Payments \u0026 pricing, 60 against 40\n- Transparency \u0026 trust, 68 against 57\n\nAlso in its favour:\n- Free to start without a card\n\nWatch for: The core's bearer gate is off by default, and the deploy notes say enabling it breaks the proxy's auth and session setup\n\n\n## Why the edge\n\n### Payments \u0026 pricing: TencentDB Agent Memory +20\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- TencentDB Agent Memory (60): Read with the self-hosted rule. MIT software with nothing to buy from Tencent, so 20 for pricing, 20 for a free start and 20 for use without an account. No x402, MPP or L402 (0). Memory extraction, wiki and code-graph building and the proxied model are paid to whichever LLM provider the owner configures.\n\n### Schema \u0026 documentation: MemMachine +18\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- TencentDB Agent Memory (61): API reading for a self-hosted HTTP service. The Knowledge service has an OpenAPI 3.0.3 file of 28 paths with no security scheme. Memory Core's 109 endpoints and the proxy's routes are described only in Markdown references, and the proxy's main LLM paths are outside them (10 of 25). No website and no llms.txt. The docs are Markdown in the repository and readable raw (5 of 10). Each Core endpoint states what it does, its limits and caveats, such as which deletes skip user checks, and Knowledge's tool list marks its tools read-only. The API references and the changelog are in Chinese; the README and install guide are in English (11 of 20). Zod-checked inputs with bounds (1 to 100 messages, 8,192 characters per message, `limit` up to 100) and enums for atom types, but the reference records that `version` comes back as a string from `atomic/update` and a number from `query` (10 of 15). Worked request and response examples per endpoint and error tables per module, with the three different error-message formats set out (12 of 15). `/v3` paths with v1 and v2 routes listed as deprecated, and a dated public changelog for every release since 0.1.0 (13 of 15).\n\n### Maintenance \u0026 community: MemMachine +13\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- TencentDB Agent Memory (70): Release 2.0.3 on 26 October 2026 by the changelog and its tag, 9 days before this check (30). Six changelog releases in the 90 days from 6 August, 2.0.1-beta.1 (13 August), 2.0.1 (25 August), 2.0.2-beta.1 (7 September), 2.0.2 (9 October), 2.0.3-beta.1 (13 October) and 2.0.3, with image tags v1.0.2 (8 September) and v1.0.3 (22 September) between. The three stable releases 2.0.1, 2.0.2 and 2.0.3 meet the line without the pre-releases, which this run doesn't count (20). GitHub issues and pull requests weren't readable, so reply times weren't judged. The plugin changelog credits fixes to numbered issues and outside pull requests, and the README says issues get a reply within 24 hours, which we couldn't check. A workflow added on 28 October posts an automatic acknowledgement on new external pull requests, which isn't a maintainer reply (10 of 25). Official TypeScript and Python SDKs exist but only as betas, the TypeScript one last published on 14 August 2026, and the Python package name differs between the changelog and its pyproject. No MCP server, so the registry line doesn't apply (6 of 15). npm packages carry registry signatures but no provenance attestations, the deploy pulls `:latest` images, the one CI workflow skips the tests and doesn't run on the default branch, and 2.0.3 fixed a Knowledge service broken by OpenTelemetry dependency drift (4 of 10).\n\n### Transparency \u0026 trust: TencentDB Agent Memory +11\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- TencentDB Agent Memory (68): MIT on both branches and in npm metadata, with the codegraph and Hermes Agent code it reuses credited in the README (30 of 30). The README says new chat memory and skills are private by default and sets out what each visibility means. No privacy statement says what each layer keeps or for how long. The proxy records every turn's upstream messages and model replies, the plugin's L0 and L1 retention defaults to never, `chat-memory/clear` empties L0, L1 and profile content while keeping the asset, and switching storage backends leaves data behind (12 of 30). v1 and v2 routes are marked deprecated with removal 'planned' and no date, and known limitations promise fixes 'in the next version' without dates (6 of 20). The plugin's metrics reporting is off by default and writes to local logs only, and ClickHouse analytics are off by default and documented. Core depends on OpenTelemetry exporters, and we didn't audit whether anything exports by default. The Hermes Docker image's default model endpoint is Tencent Cloud LKE, which the README states (13 of 20).\n\n### Security \u0026 auth: MemMachine +6\n\n- MemMachine (41): 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- TencentDB Agent Memory (35): Read as self-hosted software with a network API. Per-user `sk-mem-` keys, several per user and revocable, and OAuth2 for panel login. Against that, Memory Core's bearer gate is off by default and the .env template says setting it breaks the proxy's auth and session setup, the data plane takes team, agent and user IDs from the caller and needs only `x-tdai-service-id`, the proxy's rate-limit and session admin routes have no authentication, `/v3/instance/destroy` rests on the same unset bearer, the deploy README's defaults include an `admin` key, and the start scripts publish every port on all interfaces (8 of 30). Private-by-default assets with team, restricted and agent visibility, ACLs by user, role and agent, and read-only Knowledge tools. Data-plane deletes and `chat-memory/clear` make no user-level check and nothing asks for confirmation. Asset reads were scoped to the caller only in 2.0.2, and Agent and Task reads only in an unreleased commit of 28 October (8 of 20). The proxy injects stored memory, skills, imported documents and code into the system prompt, and we found no guidance on prompt injection or memory poisoning. Personal skills are private until shared after review (3 of 15). Participation logs, memory-generation logs and the raw L0 record let the operator trace what was written, and per-call analytics to ClickHouse is available but off by default (9 of 15). CONTRIBUTING.md asks for vulnerability reports by email to agentmemory@tencent.com rather than public issues, with no acknowledgement time, so a disclosure route without a stated time (7). No SECURITY.md on any branch, no security.txt on www.tencent.com, and no bounty or audit named. The npm plugin's postinstall runs a bash script that rewrites OpenClaw's installed files, with output sent to /dev/null. Two access-control fixes in 2026 are under the negative events.\n\n## Score by category\n\n| Category | Weight | MemMachine | TencentDB Agent Memory | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 51 | 51 | even |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 79 | 61 | MemMachine +18 |\n| Agent ergonomics | 13% (16.2 this run) | 65 | 68 | TencentDB Agent Memory +3 |\n| Security \u0026 auth | 14% (17.5 this run) | 41 | 35 | MemMachine +6 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 60 | TencentDB Agent Memory +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 83 | 70 | MemMachine +13 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 57 | 68 | TencentDB Agent Memory +11 |\n| Negative events | ≤15 | 0 | -6 | |\n| **Total** | | **58 · C** | **50.9 · D** | |\n\n## Facts side by side\n\n| Fact | MemMachine | TencentDB Agent Memory |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | MemVerge, Inc. | Tencent Cloud |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | HTTP, stdio, Streamable HTTP | HTTP |\n| Auth | None | API key |\n| Pricing | Freemium | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Tools exposed | 3 | none |\n| Read-only variant documented | no | no |\n| llms.txt | yes | no |\n| Last release | 2026-10-08 | 2026-10-26 |\n| Terms last updated | no date given | no document linked |\n| Privacy policy last updated | 2026-05-20 | no document linked |\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 | 2.2k npm/wk |\n\n## How the scores have moved\n\n### MemMachine\n\nNo score change since it was listed.\n\n### TencentDB Agent Memory\n\n- -5.1 on 4 November 2026 (C to D): security, correction\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**TencentDB Agent Memory.** A self-hosted team memory stack with layered recall, per-asset visibility and ACLs, documented HTTP APIs and frequent releases, 2.0.1 to 2.0.3 since August. The default deployment publishes its ports on all interfaces with the core's bearer gate off, the proxy's admin routes have no authentication, and two 2026 access-control fixes came without advisories.\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### TencentDB Agent Memory\n\n1. Set `MEMORY_CORE_GATEWAY_API_KEY`, `KNOWLEDGE_SERVICE_KEY` and a non-default admin key before exposing ports 8420, 8424, 8096 or 8125 beyond the host\n2. In headless runs send `x-team-id`, `x-agent-id` and `x-task-id` headers to the proxy. Without all three it falls back to an interactive picker and skips memory\n3. Expect every proxied turn to be stored. The proxy records upstream messages and model replies to Memory Core, and injected memory lands in your system prompt\n4. Check `data.valid` on `/v3/meta/auth/verify` and `data.isError` on `/v3/tools/call`. Both can fail inside a success envelope\n5. Retry `/v3/session/add` only on 500, 503 or a network error. The API reference says it isn't idempotent and writes a new object each call\n6. Build from the default branch past 2.0.3, or wait for the next release, before giving several users one Memory Core. Agent and Task reads were unscoped until 28 October\n\n## Questions\n\n### Which is better for AI agents, MemMachine or TencentDB Agent Memory?\n\nMemMachine scores 58 (C) on agent readiness against TencentDB Agent Memory's 50.9 (D), and leads in 3 of 7 scored categories. TencentDB Agent Memory leads on payments \u0026 pricing and transparency \u0026 trust.\n\n### Do MemMachine and TencentDB Agent Memory need an API key?\n\nMemMachine needs no key. TencentDB Agent Memory needs an API key.\n\n### Can an agent call MemMachine and TencentDB Agent Memory without installing anything?\n\nMemMachine runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for TencentDB Agent Memory.\n\n### Are MemMachine and TencentDB Agent Memory open source?\n\nYes. MemMachine is open source (Apache-2.0). TencentDB Agent Memory is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.json, and with the fewest tokens: https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"memmachine\", \"b\": \"tencentdb-agent-memory\"}`. From a terminal: `anchor compare memmachine tencentdb-agent-memory`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/memmachine.json and https://www.anchorterminal.com/api/v1/tools/tencentdb-agent-memory.json\n\n## Other comparisons with MemMachine or TencentDB Agent Memory\n\n- [Amazon Bedrock AgentCore Memory vs MemMachine](https://www.anchorterminal.com/compare/agentcore-memory-vs-memmachine.md)\n- [Amazon Bedrock AgentCore Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/agentcore-memory-vs-tencentdb-agent-memory.md)\n- [Basic Memory vs MemMachine](https://www.anchorterminal.com/compare/basic-memory-vs-memmachine.md)\n- [Basic Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/basic-memory-vs-tencentdb-agent-memory.md)\n- [claude-mem vs MemMachine](https://www.anchorterminal.com/compare/claude-mem-vs-memmachine.md)\n- [claude-mem vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/claude-mem-vs-tencentdb-agent-memory.md)\n- [Cognee vs MemMachine](https://www.anchorterminal.com/compare/cognee-vs-memmachine.md)\n- [Cognee vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/cognee-vs-tencentdb-agent-memory.md)\n- [EverOS vs MemMachine](https://www.anchorterminal.com/compare/everos-vs-memmachine.md)\n- [EverOS vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/everos-vs-tencentdb-agent-memory.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 TencentDB Agent Memory](https://www.anchorterminal.com/compare/google-memory-bank-vs-tencentdb-agent-memory.md)\n- [Graphiti vs MemMachine](https://www.anchorterminal.com/compare/graphiti-vs-memmachine.md)\n- [Graphiti vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/graphiti-vs-tencentdb-agent-memory.md)\n- [Hindsight vs MemMachine](https://www.anchorterminal.com/compare/hindsight-vs-memmachine.md)\n- [Hindsight vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/hindsight-vs-tencentdb-agent-memory.md)\n- [Honcho vs MemMachine](https://www.anchorterminal.com/compare/honcho-vs-memmachine.md)\n- [Honcho vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/honcho-vs-tencentdb-agent-memory.md)\n- [Hy Memory vs MemMachine](https://www.anchorterminal.com/compare/hy-memory-vs-memmachine.md)\n- [Hy Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/hy-memory-vs-tencentdb-agent-memory.md)\n- [LangMem vs MemMachine](https://www.anchorterminal.com/compare/langmem-vs-memmachine.md)\n- [LangMem vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/langmem-vs-tencentdb-agent-memory.md)\n- [LocalGhost vs MemMachine](https://www.anchorterminal.com/compare/localghost-vs-memmachine.md)\n- [LocalGhost vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/localghost-vs-tencentdb-agent-memory.md)\n- [Mem0 Platform + MCP vs MemMachine](https://www.anchorterminal.com/compare/mem0-vs-memmachine.md)\n- [Mem0 Platform + MCP vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/mem0-vs-tencentdb-agent-memory.md)\n- [MemMachine vs Memori](https://www.anchorterminal.com/compare/memmachine-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 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 TencentDB Agent Memory](https://www.anchorterminal.com/compare/memori-vs-tencentdb-agent-memory.md)\n- [Memory (MCP reference server) vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/memory-reference-server-vs-tencentdb-agent-memory.md)\n- [MemPalace vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/mempalace-vs-tencentdb-agent-memory.md)\n- [past.dev vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/past-dev-vs-tencentdb-agent-memory.md)\n- [Supermemory API + MCP vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/supermemory-vs-tencentdb-agent-memory.md)\n- [TencentDB Agent Memory vs Tokenrip](https://www.anchorterminal.com/compare/tencentdb-agent-memory-vs-tokenrip.md)\n- [TencentDB Agent Memory vs Zep](https://www.anchorterminal.com/compare/tencentdb-agent-memory-vs-zep.md)\n- [AI Memory vs MemMachine](https://www.anchorterminal.com/compare/ai-memory-vs-memmachine.md)\n- [AI Memory vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/ai-memory-vs-tencentdb-agent-memory.md)\n- [Context Mode Engine vs MemMachine](https://www.anchorterminal.com/compare/context-mode-vs-memmachine.md)\n- [Context Mode Engine vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/context-mode-vs-tencentdb-agent-memory.md)\n- [Graphicle vs MemMachine](https://www.anchorterminal.com/compare/graphicle-vs-memmachine.md)\n- [Graphicle vs TencentDB Agent Memory](https://www.anchorterminal.com/compare/graphicle-vs-tencentdb-agent-memory.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 TencentDB Agent Memory", "url": "" } ], "description": "MemMachine scores 58 (C) to TencentDB Agent Memory's 50.9 (D) for agent memory. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "MemMachine C 58", "TencentDB Agent Memory D 50.9", "scores" ], "h1": "MemMachine vs TencentDB Agent Memory", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/memmachine-vs-tencentdb-agent-memory", "published": "2026-10-01", "section": "tools", "title": "MemMachine vs TencentDB Agent Memory for AI agents (2026)", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/memmachine-vs-tencentdb-agent-memory" }, "tokens": { "markdown": 5400, "slim": 2780 }, "version": 1 }