Awesome/awesome-mcp-servers
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Merge pull request #3398 from yusufkaraaslan/add-skill-seekers

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Add skill-seekers: 35 MCP tools for AI skill & RAG knowledge generation
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Frank Fiegel
2026-03-23 02:00:22 -06:00
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@@ -1400,6 +1400,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
- [rps321321/obsidian-mcp-pro](https://github.com/rps321321/obsidian-mcp-pro) [![rps321321/obsidian-mcp-pro MCP server](https://glama.ai/mcp/servers/rps321321/obsidian-mcp-pro/badges/score.svg)](https://glama.ai/mcp/servers/rps321321/obsidian-mcp-pro) 📇 🏠 🍎 🪟 🐧 - Feature-complete Obsidian vault MCP server with 23 tools and 3 resources. Full-text search, note CRUD, frontmatter queries, tag management, backlinks, graph traversal (BFS up to 5 hops), orphan/broken link detection, and canvas support. Auto-detects vault, path traversal protection, MIT licensed.
- [smith-and-web/obsidian-mcp-server](https://github.com/smith-and-web/obsidian-mcp-server) 📇 🏠 🍎 🪟 🐧 - SSE-enabled MCP server for remote Obsidian vault management with 29 tools for notes, directories, frontmatter, tags, search, and link operations. Docker-ready with health monitoring.
- [smriti-AA/smriti](https://github.com/smriti-AA/smriti) [![smriti MCP server](https://glama.ai/mcp/servers/@Smriti-AA/smriti/badges/score.svg)](https://glama.ai/mcp/servers/@Smriti-AA/smriti) 🦀 🏠 🍎 🪟 🐧 - Self-hosted knowledge store and memory layer for AI agents with knowledge graph, wiki-links, full-text search (FTS5), and agent memory with namespaces and TTL.
- [skill-seekers/Skill_Seekers](https://github.com/yusufkaraaslan/Skill_Seekers) 🐍 🏠 🍎 🪟 🐧 - Transform 17 source types (docs, GitHub repos, PDFs, videos, Jupyter, Confluence, Notion, Slack/Discord) into AI-ready skills and RAG knowledge. 35 MCP tools for scraping, packaging, enhancing, and exporting to vector databases (Weaviate, Chroma, FAISS, Qdrant). Supports 16+ target platforms.
- [TechDocsStudio/biel-mcp](https://github.com/TechDocsStudio/biel-mcp) 📇 ☁️ - Let AI tools like Cursor, VS Code, or Claude Desktop answer questions using your product docs. Biel.ai provides the RAG system and MCP server.
- [tomohiro-owada/devrag](https://github.com/tomohiro-owada/devrag) 🏎️ 🏠 🍎 🪟 🐧 - Lightweight local RAG MCP server for semantic vector search over markdown documents. Reduces token consumption by 40x with sqlite-vec and multilingual-e5-small embeddings. Supports filtered search by directory and filename patterns.
- [topoteretes/cognee](https://github.com/topoteretes/cognee/tree/dev/cognee-mcp) 📇 🏠 - Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources