Awesome/awesome-mcp-servers
1
0
Fork 0
mirror of https://github.com/punkpeye/awesome-mcp-servers.git synced 2026-10-02 10:44:17 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #13191 from dat999zx/add-knowl

Browse Source 
Add knowl to Knowledge & Memory 🤖🤖🤖
This commit is contained in:
Frank Fiegel
2026-09-22 22:08:27 -07:00
committed by GitHub
parent e10f20117d 11fe1d4047
commit 83fe44d051
1 changed files with 1 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+1
View File
@@ -3051,6 +3051,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
- [Mnemosyne-OS/Mnemosyne-Neural-OS](https://github.com/Mnemosyne-OS/Mnemosyne-Neural-OS) [![Mnemosyne-OS/Mnemosyne-Neural-OS MCP server](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS/badges/score.svg)](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS) 🎖️ 📇 🏠 🍎 🪟 🐧 - Memory the human governs: vaults separated by domain (code, notes, journal) on your own machine, hybrid retrieval (BM25 fused with vectors by RRF), and a declared vault list, so a vault left out cannot be read by mistake. Also reads what the OTHER coding agents on this machine wrote to disk, and flags when two are live in the same git worktree. Needs the Mnemosyne OS desktop app running. `npx -y @mnemosyne_os/mcp` - [Mnemosyne-OS/Mnemosyne-Neural-OS](https://github.com/Mnemosyne-OS/Mnemosyne-Neural-OS) [![Mnemosyne-OS/Mnemosyne-Neural-OS MCP server](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS/badges/score.svg)](https://glama.ai/mcp/servers/Mnemosyne-OS/Mnemosyne-Neural-OS) 🎖️ 📇 🏠 🍎 🪟 🐧 - Memory the human governs: vaults separated by domain (code, notes, journal) on your own machine, hybrid retrieval (BM25 fused with vectors by RRF), and a declared vault list, so a vault left out cannot be read by mistake. Also reads what the OTHER coding agents on this machine wrote to disk, and flags when two are live in the same git worktree. Needs the Mnemosyne OS desktop app running. `npx -y @mnemosyne_os/mcp`
- [liza-studio/skillmem](https://github.com/liza-studio/skillmem) [![liza-studio/skillmem MCP server](https://glama.ai/mcp/servers/liza-studio/skillmem/badges/score.svg)](https://glama.ai/mcp/servers/liza-studio/skillmem) 🐍 🏠 🍎 🪟 🐧 - Self-improving skill memory for coding agents: skills that help get reinforced, unused ones fade on an Ebbinghaus decay curve. $0 write path (SQLite FTS5 + local ONNX embeddings, no LLM calls), bilingual EN/RU hybrid search, SHA256 tamper-evident history, deterministic LongMemEval benchmark in-repo (hit@5 0.871). 8 mem_* tools; deep Claude Code hook integration optional. `pip install skillmem` - [liza-studio/skillmem](https://github.com/liza-studio/skillmem) [![liza-studio/skillmem MCP server](https://glama.ai/mcp/servers/liza-studio/skillmem/badges/score.svg)](https://glama.ai/mcp/servers/liza-studio/skillmem) 🐍 🏠 🍎 🪟 🐧 - Self-improving skill memory for coding agents: skills that help get reinforced, unused ones fade on an Ebbinghaus decay curve. $0 write path (SQLite FTS5 + local ONNX embeddings, no LLM calls), bilingual EN/RU hybrid search, SHA256 tamper-evident history, deterministic LongMemEval benchmark in-repo (hit@5 0.871). 8 mem_* tools; deep Claude Code hook integration optional. `pip install skillmem`
- [zensation-ai/zenbrain](https://github.com/zensation-ai/zenbrain) [![zensation-ai/zenbrain MCP server](https://glama.ai/mcp/servers/zensation-ai/zenbrain/badges/score.svg)](https://glama.ai/mcp/servers/zensation-ai/zenbrain) 📇 🏠 🍎 🪟 🐧 - Seven-layer agent memory over MCP. `zenbrain_store` routes what it is given: a general statement becomes a semantic fact, a narrated event an episode, a sequence of instructions a procedure. `zenbrain_recall` searches every layer and tags each result with the layer it came from; `zenbrain_consolidate` runs one sleep-like maintenance pass that promotes repeated episodes into facts and decays stale slots. Local SQLite file, no account and no network call. Apache-2.0, zero-dependency TypeScript core. - [zensation-ai/zenbrain](https://github.com/zensation-ai/zenbrain) [![zensation-ai/zenbrain MCP server](https://glama.ai/mcp/servers/zensation-ai/zenbrain/badges/score.svg)](https://glama.ai/mcp/servers/zensation-ai/zenbrain) 📇 🏠 🍎 🪟 🐧 - Seven-layer agent memory over MCP. `zenbrain_store` routes what it is given: a general statement becomes a semantic fact, a narrated event an episode, a sequence of instructions a procedure. `zenbrain_recall` searches every layer and tags each result with the layer it came from; `zenbrain_consolidate` runs one sleep-like maintenance pass that promotes repeated episodes into facts and decays stale slots. Local SQLite file, no account and no network call. Apache-2.0, zero-dependency TypeScript core.
- [dat999zx/knowl](https://github.com/dat999zx/knowl) [![dat999zx/knowl MCP server](https://glama.ai/mcp/servers/dat999zx/knowl/badges/score.svg)](https://glama.ai/mcp/servers/dat999zx/knowl) 📇 🏠 🍎 🪟 🐧 - Persistent memory for Claude Code, Cursor and Codex where a replaced fact is retired at write time, so what an agent reads back is the current answer rather than the one that was true in March. Facts are typed and carry provenance and a review trail; nothing is deleted, it stops being current. Local SQLite, queries answered from a local replica and never sent to a server, no API keys. `npx -y @dat999zx/knowl serve`
### ⚖️ <a name="legal"></a>Legal ### ⚖️ <a name="legal"></a>Legal
Access to legal information, legislation, and legal databases. Enables AI models to search and analyze legal documents and regulatory information. Access to legal information, legislation, and legal databases. Enables AI models to search and analyze legal documents and regulatory information.