Tool Store

Zero-config MCP server for searchable documentation. Loads markdown into SQLite (default) or PostgreSQL with FTS5/tsvector keyword search and optional pgvector hybrid semantic search.

Local FAISS vector database for RAG with document ingestion (PDF/TXT/MD/DOCX), semantic search, re-ranking, and CLI tools for indexing and querying

Connect to any MediaWiki wiki (Wikipedia, Fandom, corporate wikis). 33+ tools for search, read, edit, link analysis, revision history, and Markdown conversion. Supports stdio and HTTP transport.

Persistent memory for AI coding agents with semantic search, auto-capture, cross-session learning, and intelligent forgetting. 12 MCP tools, local-first.

MCP server for Mendeley reference manager. Search your library, browse folders, get document metadata, search the global catalog, and add papers to your collection.

Security-hardened NotebookLM MCP with post-quantum encryption (ML-KEM-768), GDPR/SOC2/CSSF compliance, and 14 security layers. Query Google's Gemini-grounded research from Claude and AI agents.

Persistent intelligence infrastructure for agentic development that gives AI coding assistants cumulative memory and pattern learning. Hybrid TypeScript/Rust implementation with local-first storage using SQLite + SurrealDB for semantic analysis and incremental codebase understanding.

Visual explorer for [MCP Memory Service](https://github.com/doobidoo/mcp-memory-service) SQLite-vec databases. Browse, search, filter, edit memories with dashboard, timeline, UMAP projection, semantic clustering, duplicate detection, and association graph.

Connects to your Pinecone Assistant and gives the agent context from its knowledge engine.

A self-contained Memory server with single-binary architecture (embedded DB & models, no dependencies). Provides persistent semantic and graph-based memory for AI agents.

Retrieve context from your [Ragie](https://www.ragie.ai) (RAG) knowledge base connected to integrations like Google Drive, Notion, JIRA and more.

LLM-driven context and memory management with wide-recall + precise-reranking RAG architecture. Features multi-dimensional retrieval (vector/timeline/knowledge graph), short/long-term memory, and complete MCP support (HTTP/WebSocket/SSE).

Privacy-first document search server running entirely locally. Supports semantic search over PDFs, DOCX, TXT, and Markdown files with LanceDB vector storage and local embeddings - no API keys or cloud services required.

Five-level AI collaboration system with persistent memory and anticipatory capabilities. MCP-native integration for Claude and other LLMs with local-first architecture via MemDocs.

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.

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.

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.

Memory manager for AI apps and Agents using various graph and vector stores and allowing ingestion from 30+ data sources