MCP Catalog
Browse 366 Model Context Protocol servers · Knowledge & Memory · PythonClear
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Associative memory via Hebbian learning. Connections strengthen through use, decay through disuse.
Academic paper search, scientific literature, citation analysis, arXiv & semantic related-work.
Verify claims with verdict, confidence & cited sources; batch verify, source checks, daily brief.
Woody, the AI firearms expert. Verified specs, legal lookups, and knowledge base.
Trust metadata for AI agents — check files before building on them, stamp verified work.
Lightning-fast RAG for AI agents. 4-layer fusion, ONNX Runtime, sub-200ms search.
Graph-based memory system for LLMs with knowledge graphs and semantic search.
Community of Consciousness MCP Server — upload and explore collective wisdom via GitHub.
Semantic knowledge engine for Obsidian with auto-classification and DAG hierarchy
MCP server for Dash, the macOS API documentation browser. Search 200+ docsets.
Persistent semantic memory for AI agents using local ChromaDB vector search. No cloud required.
Local MCP server to sync, clean, and index AI chat logs locally. Saves up to 40% context tokens.
Cross-tool memory for your AI that recalls first every turn and admits when it doesn't know.
Persistent memory for AI agents — local JSON, zero config, no server required.
Universal MCP Server with advanced AI memory capabilities and semantic search.
Search arXiv/Semantic Scholar/OpenAlex + medical evidence (PubMed/Europe PMC) + LaTeX/PDF tools.
Collective memory for AI agents. One agent solves a bug — every agent gets the fix instantly.
Compresses AI chat sessions into a typed knowledge graph. Local/offline via Ollama.
Neuro-symbolic memory for LLMs (POC)
Add persistent memory to AI assistants. Store and recall info across conversations.
Curated knowledge for AI agents — 19K chunks, 121 skills, semantic search via MCP
Curated knowledge API for AI agents - skill packs, semantic search, validated patterns.
Local-first AI memory layer with hybrid search. Postgres + pgvector. Self-hosted, MIT.
Structural codebase indexer with 17 query tools. 87% token reduction. Zero dependencies.