"A tool to capture audio and convert an oral account into a medical history" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Local semantic search over Claude Code sessions and shell command history, exposed to Claude Code as an MCP tool. Everything is indexed into one vector space and runs entirely on your machine.

MCP server that enables semantic search over macroeconomic data using the Lambda Capture API.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Enables AI-powered medical information retrieval through FHIR clinical document search and GraphRAG-based exploration of medical entities and relationships. Combines vector search with knowledge graph queries for comprehensive healthcare data analysis.

Enables searching, indexing, and recovering past AI chat sessions and agent actions from local AI coding tools, with optional vector database semantic search and direct filesystem access.

Provides medical evidence tools including PubMed search, citation verification, clinical trial lookup, drug information, drug interaction checking, PICO extraction, and medical entity recognition via MCP.

Provides medical symptom extraction, differential diagnosis generation, PubMed literature search, and abstract summarization tools for LLM agents.

Enables searching through vectorized Cursor IDE chat history via a FastAPI service powered by LanceDB and Ollama.

Enables transcription of audio files using Google Gemini AI and creates a searchable knowledge base, allowing users to ask natural language questions about content in meetings, podcasts, lectures, and other audio recordings.

Read-only MCP bridge for searching and browsing RikkaHub app conversations through its Web API.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Config-driven MCP server for cross-domain full-text search across agent session logs, meeting transcripts, and notification files.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

A narrative graph engine that enables LLMs to generate, track, and mutate complex fictional worlds while maintaining consistency between factions, characters, and locations. It acts as a specialized RAG framework for storytelling, allowing models to manage thousands of entities without exceeding context limits.

Enables semantic search over local AI-agent session logs (e.g., Claude Code, Hermes) using local embeddings, returning relevant chunks without exposing full transcripts.

An MCP (Model Context Protocol) server that chains calls to other MCP tools, reducing token usage by allowing sequential tool execution with result passing

A universal MCP tool gateway that manages multiple remote tool processes, enabling LLMs to dynamically invoke web scraping, summarization, and knowledge retrieval through standardized Function Calling.