Merge pull request #8869 from teflon07/add-memkeeper

Add memkeeper to Knowledge & Memory 🤖🤖🤖

README.md

@@ -2371,6 +2371,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [zcag/tela](https://github.com/zcag/tela) [![zcag/tela MCP server](https://glama.ai/mcp/servers/zcag/tela/badges/score.svg)](https://glama.ai/mcp/servers/zcag/tela) 🏎️ 🏠 ☁️ - Self-hostable, markdown-native team wiki with a built-in MCP server: agents search, read, and write your wiki pages (ranked Postgres full-text + semantic search, backlink traversal). Plus Atlas, which auto-generates a cited, coverage-checked wiki from your git repos and Jira. Go + Postgres. `npx tela-mcp`
 - [VonderVuflya/Yggdrasil](https://github.com/VonderVuflya/Yggdrasil) [![VonderVuflya/Yggdrasil MCP server](https://glama.ai/mcp/servers/VonderVuflya/Yggdrasil/badges/score.svg)](https://glama.ai/mcp/servers/VonderVuflya/Yggdrasil) 🐍 🏠 🍎 🪟 🐧 - Durable, local-first memory for AI coding agents over MCP. Zero-dependency (pure Python + SQLite/FTS5), curated and semantically de-duped — you own the data as plain rows. Works with Claude Code, Codex & any MCP host. `uvx --from yggdrasil-memory ygg mcp`
 - [Yarmoluk/ckg-mcp](https://github.com/Yarmoluk/ckg-mcp) [![Yarmoluk/ckg-mcp MCP server](https://glama.ai/mcp/servers/Yarmoluk/ckg-mcp/badges/score.svg)](https://glama.ai/mcp/servers/Yarmoluk/ckg-mcp) 🐍 🏠 - Compressed Knowledge Graphs (pre-structured dependency DAGs) as MCP context — agents traverse declared edges instead of inferring from text. Open CKG Benchmark (64 domains, 10,838 queries): 3.8× RAG's F1 at 11× fewer tokens, ~42× RDS, 0 fabricated edges by construction. 97 domains, 4 tools, no DB/embeddings. `pip install ckg-mcp`
+- [teflon07/memkeeper](https://github.com/teflon07/memkeeper) [![teflon07/memkeeper MCP server](https://glama.ai/mcp/servers/teflon07/memkeeper/badges/score.svg)](https://glama.ai/mcp/servers/teflon07/memkeeper) 🦀 🏠 🍎 🐧 - Local-first memory for AI agents: a single self-contained Rust binary over one SQLite file. Hybrid BM25/FTS + on-device ONNX embeddings + cross-encoder rerank; abstains instead of returning a confident wrong memory. No server, no API key, zero marginal cost. `memkeeper mcp`
 - [yamantaka520/Agent-Memory-OS](https://github.com/yamantaka520/Agent-Memory-OS) [![yamantaka520/Agent-Memory-OS MCP server](https://glama.ai/mcp/servers/yamantaka520/Agent-Memory-OS/badges/score.svg)](https://glama.ai/mcp/servers/yamantaka520/Agent-Memory-OS) 🐍 🏠 🍎 🪟 🐧 - Local-first memory engine for AI-agent teams: private/team/project ACL (a hard gate before ranking), associative recall, and federated sync where revocation propagates across nodes. SQLite + FTS5, no LLM required; MCP server + web console included. `pip install 'agent-memory-os[mcp]'`
 
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