{ "data": { "a": { "slug": "graphicle", "name": "Graphicle", "vendor": "KarLex AI, Inc.", "vendorUrl": "https://www.karlex.ai/graphicle", "kind": "mcp", "category": "agent-memory", "summary": "Graphicle is an open-source Rust program that builds a code graph of a repository and keeps its documents, reviewed decisions and past coding-agent sessions, served to Claude Code, Codex, Cursor and other MCP clients as cited excerpts.", "url": "https://www.anchorterminal.com/tools/graphicle", "markdownUrl": "https://www.anchorterminal.com/tools/graphicle.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/graphicle.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/graphicle.json", "repo": "https://github.com/Graphicle-AI/graphicle", "license": "Apache-2.0", "transports": [ "stdio", "streamable-http" ], "packages": [], "auth": "mixed", "authNotes": "No account. The stdio server (`graphicle mcp`) runs with the owner key saved in the local data folder, which reads every project in the store. Over HTTP (`graphicle serve`, 127.0.0.1:8854 by default) each agent or person gets its own access key with a role, optional expiry and optional project list, sent as `Authorization: Bearer` or `X-Workspace-Capability`, never in the URL. Keys are stored as hashes and can be revoked.", "pricing": "free", "pricingNotes": "Free under Apache-2.0 for individuals and teams, with nothing to buy. A commercial edition for teams is in private preview with no published prices. Optional model calls (answers, memory extraction, full document extraction) are paid to the provider the owner configures, or run locally through Ollama.", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the source, README, docs or karlex.ai (checked 2026-10-15). The software has no paid tier.", "endpoints": [] }, "toolCount": 25, "popularity": { "githubStars": 144, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-15" }, "docsUrl": "https://github.com/Graphicle-AI/graphicle/blob/main/docs/quickstart.md", "capabilities": [ "memory.search", "memory.graph", "memory.store", "memory.delete" ], "tags": [ "open-source", "local", "self-hosted", "free", "no-card", "apache-2.0", "rust", "mcp", "macos", "linux" ], "lastRelease": "2026-10-14", "graded": true, "anchor": { "graded": true, "score": 69.8, "grade": "B", "agentReady": false, "rank": 178, "ranked": true, "rankOf": 1094, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 86, "maintenance": 48, "payments": 60, "reliability": 63, "schema": 83, "security": 69, "transparency": 68 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-15" }, "negative": 0, "verdict": "One local program gives a coding agent a code graph and project memory through 25 typed, annotated MCP tools that return cited excerpts within a token budget, with agent-written memories held for human approval. It is one day old at version 0.1.0, its SDKs are not on any registry, and the licence and advisory check fails on main.", "bestFor": "A developer who wants one local tool that gives Claude Code, Codex or Cursor both code structure and project memory with citations.", "strengths": [ "25 MCP tools with closed JSON Schema inputs, enums and limits, readOnlyHint on every read tool, and an idempotency key on `propose_memory`", "Recall returns excerpts with file, line range and hash, within a `max_tokens` budget, and `skip_shown` avoids resending excerpts", "Agent-proposed memories need verbatim quotes and a person's approval, and the MCP server has no tool that deletes or runs commands", "No telemetry or account. The source calls out only to models, connectors and GitHub that the owner configures", "Apache-2.0 with detailed NOTICE files, a SECURITY.md with private GitHub reporting and a valid security.txt at karlex.ai" ], "weaknesses": [ "One release, v0.1.0 on 14 October 2026, from a repository created that day", "The cargo-deny licence and advisory job failed on both pushes to main, though the test jobs passed on macOS and Linux", "The stdio server runs with the owner key, so its graph tools can read any project in the store unless an HTTP key is scoped", "SDKs are source-only, no llms.txt, not in the official MCP registry, and no native Windows build", "The team audit trail is in the commercial edition. Core shows usage counters and deletion receipts only" ], "agentNotes": [ "Call `recall_project` with a `max_tokens` budget, then `read_project_source` with the cited id and byte offset to continue a cut excerpt", "Use `query_graph`, `get_neighbors` and `shortest_path` for structure questions, and pass `repo` to reach another synced project", "Treat proposed memories as drafts. They are not served until a person approves them in `graphicle open` under Memory", "Ask the user before running `graphicle setup`, which edits agent settings, AGENTS.md and Git hooks, and use `graphicle disconnect` to undo it", "Over HTTP send the key as `Authorization: Bearer`, never in the URL, and on 429 wait for the Retry-After reset" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.8 } ], "editorialScores": { "ergonomics": 86, "maintenance": 48, "payments": 60, "reliability": 63, "schema": 83, "security": 69, "transparency": 71 }, "provenanceScore": 65 }, "connect": { "install": "brew install graphicle-ai/tap/graphicle \u0026\u0026 cd your-repo \u0026\u0026 graphicle setup", "claudeCode": "graphicle sync . \u0026\u0026 graphicle connect claude-code", "config": { "mcpServers": { "graphicle": { "args": [ "mcp", "--project", "PROJECT_ID" ], "command": "/full/path/to/graphicle" } } } }, "letme": { "capability": "https://letme.dev/memory.search", "tool": "https://letme.dev/graphicle" }, "area": "agent-runtime", "provenance": { "legalEntity": "KarLex AI, Inc.", "domain": "karlex.ai", "domainRegistered": "", "endpointOnVendorDomain": null, "terms": "https://www.karlex.ai/legal/terms", "privacy": "https://www.karlex.ai/legal/privacy", "statusPage": "", "changelog": "https://github.com/Graphicle-AI/graphicle/blob/main/CHANGELOG.md", "securityTxt": "valid", "checked": "2026-10-15", "notes": [ "The README and LICENSE read Copyright 2026 KarLex AI, Inc. karlex.ai names KarLex AI as the company behind Graphicle and links the graphicle-ai GitHub organisation, created on 29 September 2026.", "The terms of use and privacy policy at karlex.ai are dated 14 March 2025 and cover the website and its accounts, not the Graphicle software, which runs on the user's machine.", "karlex.ai/.well-known/security.txt names security@karlexai.com and expires on 7 April 2027 (read 15 October 2026). karlexai.com redirects to karlex.ai; RDAP at Verisign gives karlexai.com a registration date of 20 December 2023. The .ai registration date was not read.", "karlex.ai's robots.txt allows all crawlers.", "The software runs on the owner's machine, so there is no vendor endpoint or status page to check." ], "score": 65 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/graphicle.json" }, "answer": "Graphicle scores 69.8 (B) on agent readiness against LangMem's 47.9 (D), and leads in 6 of 7 scored categories.", "b": { "slug": "langmem", "name": "LangMem", "vendor": "LangChain", "vendorUrl": "https://www.langchain.com", "kind": "sdk", "category": "agent-memory", "summary": "LangMem is LangChain's open-source Python library for long-term agent memory. It extracts facts from conversations with an LLM, stores and searches them in a LangGraph store the owner runs, and includes two memory tools, message summarisation and prompt optimisation.", "url": "https://www.anchorterminal.com/tools/langmem", "markdownUrl": "https://www.anchorterminal.com/tools/langmem.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/langmem.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/langmem.json", "repo": "https://github.com/langchain-ai/langmem", "license": "MIT", "transports": [], "packages": [ { "registry": "pypi", "name": "langmem" } ], "auth": "none", "authNotes": "The library has no account or key of its own. It runs in the owner's process and needs a key for the chosen LLM provider (the README uses `ANTHROPIC_API_KEY`) and, for semantic search, an embedding provider. Access to memories is whatever the owner's LangGraph store and namespace settings allow.", "pricing": "free", "pricingNotes": "Free under the MIT licence, with nothing to buy and no signup. The owner pays for the LLM calls that extract memories, the embedding calls behind search, and the database behind the store (https://github.com/langchain-ai/langmem).", "priceSummary": "Free · OSS", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs or the source (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 1698, "npmWeekly": null, "pypiWeekly": 214379, "asOf": "2026-10-08" }, "docsUrl": "https://langchain-ai.github.io/langmem/", "capabilities": [ "memory.store", "memory.search", "memory.user", "memory.delete" ], "tags": [ "sdk", "open-source", "self-hosted", "local", "python", "free", "langgraph", "pre-1.0" ], "lastRelease": "2025-10-27", "graded": true, "anchor": { "graded": true, "score": 47.9, "grade": "D", "agentReady": false, "rank": 899, "ranked": true, "rankOf": 1094, "categoryRank": 11, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 45, "transparency": 59 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.", "bestFor": "Teams already on LangGraph that want memory tools and background extraction over a store they run.", "strengths": [ "MIT licence, installed with `pip install -U langmem`, with no account, key or fee of its own", "Two agent tools, `manage_memory` and `search_memory`, with typed inputs, an action enum and `limit`, `offset` and `filter` on search", "`actions_permitted` limits the manage tool to any subset of create, update and delete, and `create_memory_store_manager` leaves deletes off by default", "Namespace templates such as `(\"memories\", \"{langgraph_user_id}\")` keep each user's memories apart at run time", "Works with any LangGraph `BaseStore`, including `InMemoryStore` for tests and `AsyncPostgresStore` for durable storage" ], "weaknesses": [ "The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that", "No changelog, GitHub releases or tags, and versions are still 0.0.x", "The repository's two workflows deploy docs and publish to PyPI. Neither runs the tests", "54 open issues, 23 with no comment, and 19 open pull requests, the oldest from June 2025", "No guidance on memory poisoning or prompt injection found, and two open issues asking for it (May 2026) have no reply" ], "agentNotes": [ "Pass a store with an embedding index (`index={\"dims\": 1536, \"embed\": \"openai:text-embedding-3-small\"}`), or `search_memory` cannot rank by meaning", "Use a database-backed store such as `AsyncPostgresStore` for anything that must survive a restart. `InMemoryStore` loses everything", "Put a per-user placeholder in the namespace and set it in `config[\"configurable\"]` on every call, or users share one memory space", "Send the memory `id` with `update` and `delete`, and never with `create`. A retried `create` writes a duplicate under a new UUID", "Run on Python 3.11 or later. `src/langmem/knowledge/extraction.py` uses `typing.NotRequired`, which Python 3.10 lacks" ], "metrics": { "kind": "local", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 47.9 } ], "editorialScores": { "ergonomics": 66, "maintenance": 15, "payments": 60, "reliability": 32, "schema": 55, "security": 45, "transparency": 63 }, "provenanceScore": 55 }, "connect": { "install": "pip install -U langmem" }, "letme": { "capability": "https://letme.dev/memory.store", "tool": "https://letme.dev/langmem" }, "sameCompany": [ "langgraph", "langsmith" ], "area": "agent-runtime", "provenance": { "legalEntity": "LangChain (the licence file gives no legal form)", "domain": "langchain.com", "domainRegistered": "2019-12-03", "endpointOnVendorDomain": null, "terms": "", "privacy": "", "statusPage": "", "changelog": "", "securityTxt": "none", "checked": "2026-10-08", "notes": [ "A library the owner runs, with no hosted endpoint. The code is on github.com under the langchain-ai organisation and the docs are on langchain-ai.github.io/langmem.", "The LICENSE file reads Copyright (c) 2025 LangChain. PyPI metadata names no author.", "No terms or privacy document governs the library, so both fields are left out. The MIT licence is the only agreement.", "No changelog file, GitHub releases or tags exist in the repository. PyPI's release history is the only record of versions.", "www.langchain.com/.well-known/security.txt returns 404. The organisation's SECURITY.md points to two Intigriti disclosure programmes.", "RDAP for langchain.com gives a registration date of 2019-12-03." ], "score": 55 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/langmem.json", "live": { "slug": "langmem", "versions": [ { "registry": "pypi", "name": "langmem", "version": "0.0.30", "released": "2025-10-27", "seenAt": "2026-10-15T00:01:23.619429135Z" } ], "githubStars": 1704, "pypiWeekly": 228418, "securityTxt": { "url": "https://langchain.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-14T15:46:29.120661224Z" }, "domain": { "domain": "langchain.com", "registered": "2019-12-03", "source": "https://rdap.verisign.com/com/v1/domain/langchain.com", "checkedAt": "2026-10-11T13:11:02.483641429Z" }, "updatedAt": "2026-10-15T00:01:23.820582588Z" } }, "facts": [ { "a": "MCP server", "b": "SDK + MCP", "name": "Kind" }, { "a": "KarLex AI, Inc.", "b": "LangChain", "name": "Vendor" }, { "a": "no (local only)", "b": "no (local only)", "name": "Hosted endpoint" }, { "a": "stdio, Streamable HTTP", "b": "", "name": "Transports" }, { "a": "OAuth or key", "b": "None", "name": "Auth" }, { "a": "Free", "b": "Free", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0", "b": "MIT", "name": "Licence" }, { "a": "25", "b": "none", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "no", "name": "llms.txt" }, { "a": "2026-10-14", "b": "2025-10-27", "name": "Last release" }, { "a": "2025-03-14", "b": "no document linked", "name": "Terms last updated" }, { "a": "2025-03-14", "b": "no document linked", "name": "Privacy policy last updated" }, { "a": "yes, with an opt-out", "b": "", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "", "name": "Terms restrict automated access" }, { "a": "yes", "b": "", "name": "Terms restrict benchmarking" }, { "a": "yes", "b": "", "name": "Terms or service can change without notice" }, { "a": "yes", "b": "", "name": "Arbitration or class-action waiver" }, { "a": "144 stars", "b": "1.7k stars, 214k PyPI/wk", "name": "Popularity" } ], "faq": [ { "answer": "Graphicle scores 69.8 (B) on agent readiness against LangMem's 47.9 (D), and leads in 6 of 7 scored categories.", "question": "Which is better for AI agents, Graphicle or LangMem?" }, { "answer": "Graphicle runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for LangMem.", "question": "Can an agent call Graphicle and LangMem without installing anything?" }, { "answer": "Yes. Graphicle is open source (Apache-2.0). LangMem is open source (MIT).", "question": "Are Graphicle and LangMem open source?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 63 against 32", "Schema \u0026 documentation, 83 against 55", "Agent ergonomics, 86 against 66", "Security \u0026 auth, 69 against 45", "Maintenance \u0026 community, 48 against 15", "Transparency \u0026 trust, 68 against 59" ], "also": [ "Runs on your own machine", "Free to start without a card" ], "goodFor": "A developer who wants one local tool that gives Claude Code, Codex or Cursor both code structure and project memory with citations.", "slug": "graphicle", "watchFor": "One release, v0.1.0 on 14 October 2026, from a repository created that day" }, { "aheadOn": null, "also": [ "No key needed to call it" ], "goodFor": "Teams already on LangGraph that want memory tools and background extraction over a store they run.", "slug": "langmem", "watchFor": "The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that" } ], "job": { "capability": "memory.search", "name": "Memory search" }, "others": [ { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.json", "title": "Amazon Bedrock AgentCore Memory vs Graphicle", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle" }, { "json": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.json", "title": "Amazon Bedrock AgentCore Memory vs LangMem", "url": "https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-graphicle.json", "title": "Cognee vs Graphicle", "url": "https://www.anchorterminal.com/compare/cognee-vs-graphicle" }, { "json": "https://www.anchorterminal.com/compare/cognee-vs-langmem.json", "title": "Cognee vs LangMem", "url": "https://www.anchorterminal.com/compare/cognee-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/graphiti-vs-langmem.json", "title": "Graphiti vs LangMem", "url": "https://www.anchorterminal.com/compare/graphiti-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/hindsight-vs-langmem.json", "title": "Hindsight vs LangMem", "url": "https://www.anchorterminal.com/compare/hindsight-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/honcho-vs-langmem.json", "title": "Honcho vs LangMem", "url": "https://www.anchorterminal.com/compare/honcho-vs-langmem" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-localghost.json", "title": "LangMem vs LocalGhost", "url": "https://www.anchorterminal.com/compare/langmem-vs-localghost" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-mem0.json", "title": "LangMem vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/langmem-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.json", "title": "LangMem vs Memory (MCP reference server)", "url": "https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-supermemory.json", "title": "LangMem vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/langmem-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/langmem-vs-zep.json", "title": "LangMem vs Zep", "url": "https://www.anchorterminal.com/compare/langmem-vs-zep" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-graphiti.json", "title": "Graphicle vs Graphiti", "url": "https://www.anchorterminal.com/compare/graphicle-vs-graphiti" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-hindsight.json", "title": "Graphicle vs Hindsight", "url": "https://www.anchorterminal.com/compare/graphicle-vs-hindsight" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-honcho.json", "title": "Graphicle vs Honcho", "url": "https://www.anchorterminal.com/compare/graphicle-vs-honcho" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-khoj.json", "title": "Graphicle vs Khoj", "url": "https://www.anchorterminal.com/compare/graphicle-vs-khoj" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-mem0.json", "title": "Graphicle vs Mem0 Platform + MCP", "url": "https://www.anchorterminal.com/compare/graphicle-vs-mem0" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-supermemory.json", "title": "Graphicle vs Supermemory API + MCP", "url": "https://www.anchorterminal.com/compare/graphicle-vs-supermemory" }, { "json": "https://www.anchorterminal.com/compare/graphicle-vs-zep.json", "title": "Graphicle vs Zep", "url": "https://www.anchorterminal.com/compare/graphicle-vs-zep" } ], "scores": [ { "by": 31, "edge": "graphicle", "graphicle": 63, "key": "reliability", "langmem": 32, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 28, "edge": "graphicle", "graphicle": 83, "key": "schema", "langmem": 55, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 20, "edge": "graphicle", "graphicle": 86, "key": "ergonomics", "langmem": 66, "name": "Agent ergonomics", "weight": 13 }, { "by": 24, "edge": "graphicle", "graphicle": 69, "key": "security", "langmem": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 0, "edge": "", "graphicle": 60, "key": "payments", "langmem": 60, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 33, "edge": "graphicle", "graphicle": 48, "key": "maintenance", "langmem": 15, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 9, "edge": "graphicle", "graphicle": 68, "key": "transparency", "langmem": 59, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Graphicle scores 69.8 (B) on agent readiness against LangMem's 47.9 (D), and leads in 6 of 7 scored categories. Both do memory search.", "verdicts": { "graphicle": "One local program gives a coding agent a code graph and project memory through 25 typed, annotated MCP tools that return cited excerpts within a token budget, with agent-written memories held for human approval. It is one day old at version 0.1.0, its SDKs are not on any registry, and the licence and advisory check fails on main.", "langmem": "Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/graphicle-vs-langmem", "json": "https://www.anchorterminal.com/compare/graphicle-vs-langmem.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/graphicle-vs-langmem.md", "slim": "https://www.anchorterminal.com/compare/graphicle-vs-langmem.min.md" }, "markdown": "Graphicle scores 69.8 (B) on agent readiness against LangMem's 47.9 (D), and leads in 6 of 7 scored categories. Both do memory search.\n\n- Graphicle: grade B, 69.8/100, rank #178 of 1094. Markdown https://www.anchorterminal.com/tools/graphicle.md · JSON https://www.anchorterminal.com/api/v1/tools/graphicle.json\n- LangMem: grade D, 47.9/100, rank #899 of 1094. Markdown https://www.anchorterminal.com/tools/langmem.md · JSON https://www.anchorterminal.com/api/v1/tools/langmem.json\n- Best memory layers for AI agents: https://www.anchorterminal.com/best/agent-memory/index.md\n- All 65 memory comparisons: https://www.anchorterminal.com/compare/agent-memory/index.md\n\n## Which one, for what\n\n### Graphicle (B)\n\nGood for: A developer who wants one local tool that gives Claude Code, Codex or Cursor both code structure and project memory with citations.\n\nAhead on:\n- Reliability, 63 against 32\n- Schema \u0026 documentation, 83 against 55\n- Agent ergonomics, 86 against 66\n- Security \u0026 auth, 69 against 45\n- Maintenance \u0026 community, 48 against 15\n- Transparency \u0026 trust, 68 against 59\n\nAlso in its favour:\n- Runs on your own machine\n- Free to start without a card\n\nWatch for: One release, v0.1.0 on 14 October 2026, from a repository created that day\n\n### LangMem (D)\n\nGood for: Teams already on LangGraph that want memory tools and background extraction over a store they run.\n\nAlso in its favour:\n- No key needed to call it\n\nWatch for: The newest PyPI release, 0.0.30, is from 27 October 2025, and every commit to `src` on main is older than that\n\n\n## Score by category\n\n| Category | Weight | Graphicle | LangMem | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 63 | 32 | Graphicle +31 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 83 | 55 | Graphicle +28 |\n| Agent ergonomics | 13% (16.2 this run) | 86 | 66 | Graphicle +20 |\n| Security \u0026 auth | 14% (17.5 this run) | 69 | 45 | Graphicle +24 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 60 | 60 | even |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 48 | 15 | Graphicle +33 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 68 | 59 | Graphicle +9 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.8 · B** | **47.9 · D** | |\n\n## Facts side by side\n\n| Fact | Graphicle | LangMem |\n| --- | --- | --- |\n| Kind | MCP server | SDK + MCP |\n| Vendor | KarLex AI, Inc. | LangChain |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports | stdio, Streamable HTTP | |\n| Auth | OAuth or key | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | MIT |\n| Tools exposed | 25 | none |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-10-14 | 2025-10-27 |\n| Terms last updated | 2025-03-14 | no document linked |\n| Privacy policy last updated | 2025-03-14 | no document linked |\n| Customer content may train models | yes, with an opt-out | |\n| Terms restrict automated access | not found in the text | |\n| Terms restrict benchmarking | yes | |\n| Terms or service can change without notice | yes | |\n| Arbitration or class-action waiver | yes | |\n| Popularity | 144 stars | 1.7k stars, 214k PyPI/wk |\n\n## Verdicts\n\n**Graphicle.** One local program gives a coding agent a code graph and project memory through 25 typed, annotated MCP tools that return cited excerpts within a token budget, with agent-written memories held for human approval. It is one day old at version 0.1.0, its SDKs are not on any registry, and the licence and advisory check fails on main.\n\n**LangMem.** Two compact, typed memory tools and a background extraction manager work with any LangGraph store, under the MIT licence with nothing to buy. The newest PyPI release, 0.0.30, dates from 27 October 2025. The repository has no changelog, tags or test workflow, and 23 of 54 open issues have no reply.\n\n## Before you call either\n\n### Graphicle\n\n1. Call `recall_project` with a `max_tokens` budget, then `read_project_source` with the cited id and byte offset to continue a cut excerpt\n2. Use `query_graph`, `get_neighbors` and `shortest_path` for structure questions, and pass `repo` to reach another synced project\n3. Treat proposed memories as drafts. They are not served until a person approves them in `graphicle open` under Memory\n4. Ask the user before running `graphicle setup`, which edits agent settings, AGENTS.md and Git hooks, and use `graphicle disconnect` to undo it\n5. Over HTTP send the key as `Authorization: Bearer`, never in the URL, and on 429 wait for the Retry-After reset\n\n### LangMem\n\n1. Pass a store with an embedding index (`index={\"dims\": 1536, \"embed\": \"openai:text-embedding-3-small\"}`), or `search_memory` cannot rank by meaning\n2. Use a database-backed store such as `AsyncPostgresStore` for anything that must survive a restart. `InMemoryStore` loses everything\n3. Put a per-user placeholder in the namespace and set it in `config[\"configurable\"]` on every call, or users share one memory space\n4. Send the memory `id` with `update` and `delete`, and never with `create`. A retried `create` writes a duplicate under a new UUID\n5. Run on Python 3.11 or later. `src/langmem/knowledge/extraction.py` uses `typing.NotRequired`, which Python 3.10 lacks\n\n## Questions\n\n### Which is better for AI agents, Graphicle or LangMem?\n\nGraphicle scores 69.8 (B) on agent readiness against LangMem's 47.9 (D), and leads in 6 of 7 scored categories.\n\n### Can an agent call Graphicle and LangMem without installing anything?\n\nGraphicle runs on your own machine, with no hosted endpoint listed. No hosted endpoint is listed for LangMem.\n\n### Are Graphicle and LangMem open source?\n\nYes. Graphicle is open source (Apache-2.0). LangMem is open source (MIT).\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/graphicle-vs-langmem.json, and with the fewest tokens: https://www.anchorterminal.com/compare/graphicle-vs-langmem.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"graphicle\", \"b\": \"langmem\"}`. From a terminal: `anchor compare graphicle langmem`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/graphicle.json and https://www.anchorterminal.com/api/v1/tools/langmem.json\n\n## Other comparisons with Graphicle or LangMem\n\n- [Amazon Bedrock AgentCore Memory vs Graphicle](https://www.anchorterminal.com/compare/agentcore-memory-vs-graphicle.md)\n- [Amazon Bedrock AgentCore Memory vs LangMem](https://www.anchorterminal.com/compare/agentcore-memory-vs-langmem.md)\n- [Cognee vs Graphicle](https://www.anchorterminal.com/compare/cognee-vs-graphicle.md)\n- [Cognee vs LangMem](https://www.anchorterminal.com/compare/cognee-vs-langmem.md)\n- [Graphiti vs LangMem](https://www.anchorterminal.com/compare/graphiti-vs-langmem.md)\n- [Hindsight vs LangMem](https://www.anchorterminal.com/compare/hindsight-vs-langmem.md)\n- [Honcho vs LangMem](https://www.anchorterminal.com/compare/honcho-vs-langmem.md)\n- [LangMem vs LocalGhost](https://www.anchorterminal.com/compare/langmem-vs-localghost.md)\n- [LangMem vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/langmem-vs-mem0.md)\n- [LangMem vs Memory (MCP reference server)](https://www.anchorterminal.com/compare/langmem-vs-memory-reference-server.md)\n- [LangMem vs Supermemory API + MCP](https://www.anchorterminal.com/compare/langmem-vs-supermemory.md)\n- [LangMem vs Zep](https://www.anchorterminal.com/compare/langmem-vs-zep.md)\n- [Graphicle vs Graphiti](https://www.anchorterminal.com/compare/graphicle-vs-graphiti.md)\n- [Graphicle vs Hindsight](https://www.anchorterminal.com/compare/graphicle-vs-hindsight.md)\n- [Graphicle vs Honcho](https://www.anchorterminal.com/compare/graphicle-vs-honcho.md)\n- [Graphicle vs Khoj](https://www.anchorterminal.com/compare/graphicle-vs-khoj.md)\n- [Graphicle vs Mem0 Platform + MCP](https://www.anchorterminal.com/compare/graphicle-vs-mem0.md)\n- [Graphicle vs Supermemory API + MCP](https://www.anchorterminal.com/compare/graphicle-vs-supermemory.md)\n- [Graphicle vs Zep](https://www.anchorterminal.com/compare/graphicle-vs-zep.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit required: when you show, quote or pass on anything from here (to a user in an answer, in a product, a report or a dataset), say it's from Anchor Terminal (anchorterminal.com) and link the page or API address you took it from. Reviews also credit their author.", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-15", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "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": "Graphicle vs LangMem", "url": "" } ], "description": "Graphicle scores 69.8 (B) to LangMem's 47.9 (D) for memory search. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Graphicle B 69.8", "LangMem D 47.9", "scores" ], "h1": "Graphicle vs LangMem", "image": "https://www.anchorterminal.com/assets/og/compare-graphicle-vs-langmem.png", "path": "/compare/graphicle-vs-langmem", "published": "2026-10-01", "section": "tools", "title": "Graphicle vs LangMem for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-10-15", "url": "https://www.anchorterminal.com/compare/graphicle-vs-langmem" }, "tokens": { "markdown": 2250, "slim": 630 }, "version": 1 }