Provides semantic search and data retrieval capabilities over a knowledge base with multiple tools including keyword search, category filtering, and ID-based lookup with in-memory caching.
A local document processing server that can index various document formats (PDF, DOCX, TXT, HTML) and answer questions based on their content using the Model Context Protocol.
A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.
A persistent memory system that captures, classifies, synthesizes, and retrieves knowledge for AI agents, turning raw information into refined, retrievable knowledge that compounds intelligence over time.
A local knowledge base server that connects to AI assistants, turning markdown files into a semantically searchable memory layer via OpenAI embeddings and SQLite.
Enables semantic search across Clarion programming documentation via natural language queries in Claude AI, supporting 21 manuals and 21,747 indexed chunks.
Provides semantic search over a self-building personal technical knowledge base that automatically collects and distills content from GitHub Trending, AI news, and arXiv.
Builds a searchable knowledge base from YouTube video transcripts with hybrid semantic and keyword search. Allows LLM assistants to search, organize, and retrieve timestamped information from videos you've watched.
Enables management of Amazon Bedrock Knowledge Bases including creation, data source configuration, document ingestion, and RAG (Retrieval-Augmented Generation) queries with support for multiple embedding models and custom parsing/chunking strategies.
An MCP server that enables AI assistants to access and search Cherry Studio knowledge bases, supporting operations like listing, searching, and retrieving details.
MCP server for managing and searching multi-tenant knowledge bases backed by SQLite with FTS5, enabling AI agents to persist and retrieve content via full-text search.
Enables AI assistants to manage a personal markdown-based knowledge base with natural language interactions. Supports creating, searching, updating, and organizing notes across categories like people, recipes, meetings, and procedures.