{"data":{"slug":"alibaizhanov-mengram","name":"mengram","tagline":"Semantic, episodic, and procedural memory for AI agents, like human记忆被切断了，请稍后尝试重新生成。","github_url":"https://github.com/alibaizhanov/mengram","owner":"alibaizhanov","repo":"mengram","owner_avatar_url":"https://avatars.githubusercontent.com/u/32927647?v=4","primary_language":"Python","stars":184,"forks":27,"topics":["agent-memory","ai-agents","ai-memory","claude-desktop","cognitive-architecture","cohere","cursor-ai","episodic-memory","knowledge-graph","letta-alternative","llm-memory","mcp-server","mem0-alternative","model-context-protocol","multilingual-embeddings","pgvector","procedural-memory","python","rag","semantic-search"],"archived":false,"github_pushed_at":"2026-07-30T11:21:44+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/alibaizhanov-mengram","markdown_url":"https://www.graphcanon.com/tools/alibaizhanov-mengram.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/alibaizhanov-mengram","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=alibaizhanov-mengram","description":"Human-like memory for AI agents — semantic, episodic & procedural. Experience-driven procedures that learn from failures. Free API, Python & JS SDKs, LangChain, CrewAI & OpenClaw integrations.","homepage_url":"https://mengram.io","license":"Apache-2.0","open_issues":27,"watchers":4,"ai_summary":"Offers memory capabilities for AI agents including semantic, episodic, and procedural memory with integrations into various platforms like LangChain, CrewAI, and OpenClaw. Provides Python and JS SDKs alongside a free API.","readme_excerpt":"## Install in one prompt (any AI tool)\n\nPaste this into Claude Desktop, Cursor, Codex, Claude Code, or Windsurf — the agent reads our [setup guide](https://mengram.io/agent-install.txt), installs the SDK, configures the MCP server, and verifies the round-trip end-to-end. **No terminal context-switching.**\n\n```\nInstall Mengram for me. Fetch the canonical install guide at\nhttps://mengram.io/agent-install.txt and follow it precisely.\nMy email is YOUR_EMAIL_HERE.\n```\n\nWorks in any agent with shell + file-edit + web-fetch tools. Prefer doing it manually? See the [plain-text guide](https://mengram.io/agent-install.txt) — it's structured for human eyes too.\n\n---\n\n---\n\n# 2. Install the plugin (hooks + MCP server + skill)\nclaude plugin marketplace add alibaizhanov/mengram\nclaude plugin install mengram@mengram\n\n---\n\n#    and Railway. Recently debugged pgvector deployment. Prefers direct\n\n---\n\n## License\n\nApache 2.0 — free for commercial use.\n\n---\n\n<div align=\"center\">\n\n**[Get your free API key](https://mengram.io/#signup)** · Built by **[Ali Baizhanov](https://github.com/alibaizhanov)** · **[mengram.io](https://mengram.io)**\n\n</div>","github_created_at":"2026-02-10T19:20:33+00:00","created_at":"2026-07-11T23:17:05.273774+00:00","updated_at":"2026-08-02T12:00:37.464536+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"agent-memory","name":"agent-memory"},{"slug":"ai-agents","name":"ai-agents"},{"slug":"ai-memory","name":"ai-memory"},{"slug":"cognitive-architecture","name":"cognitive-architecture"},{"slug":"episodic-memory","name":"episodic-memory"},{"slug":"knowledge-graph","name":"knowledge-graph"},{"slug":"llm-memory","name":"llm-memory"},{"slug":"model-context-protocol","name":"model-context-protocol"}],"trust":{"provenance":{"is_fork":false,"github_id":1154785536,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-02T12:00:36.012Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":1,"days_since_push":3,"last_release_at":"2026-05-14T12:23:24Z"},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":23,"high_count":0,"last_scan_at":"2026-07-11T23:17:11.881Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"mcp":{"source":"repo_scan","observed_at":"2026-08-02T12:00:36.441Z","server_manifest":false},"scan":{"source":"repo_scan","observed_at":"2026-08-02T12:00:36.441Z"},"deploy":{"source":"dockerfile:docker-compose.yml","self_host":true,"observed_at":"2026-08-02T12:00:36.441Z","managed_saas":false},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-08-02T12:00:36.441Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-02T12:00:36.441Z"},"has_docker":{"value":true,"source":"dockerfile:docker-compose.yml","observed_at":"2026-08-02T12:00:36.441Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-02T12:00:36.441Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Use Mengram if your project requires a comprehensive suite of human-like memory capabilities (semantic, episodic, procedural) for AI agents.","Prefer Mengram when you need smooth integration into multiple platforms such as LangChain, CrewAI, and OpenClaw without the need to build custom connectors.","Select Mengram for its streamlined setup process, especially effective in environments like Claude Desktop where it minimizes manual intervention."],"when_not_to_use":["Avoid Mengram if your project focuses solely on a specific type of memory (e.g., only semantic) and requires more specialized functionality not provided by Mengram.","Mengram might be less appealing if direct terminal access is preferred over the provided one-prompt setup method, which some users might deem as more complex or cumbersome."],"source":"enrich:decision_facts","observed_at":"2026-07-12T05:38:29.766Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Mengram offers memory functionalities tailored for AI agents, including semantic, episodic, and procedural capabilities with integrations into platforms like LangChain, CrewAI, and OpenClaw."}]}}