"A search for guests for a podcast using Google and LinkedIn" matching MCP servers:

A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.

Enables users to ingest PDF/DOCX/TXT/MD documents and ask natural language questions about them, using local embeddings and Groq-powered retrieval-augmented generation.

A semantic search system for Claude Code transcript history, exposed as an MCP server so Claude Code can query its own past sessions.

Enables AI agents to search local Markdown documents using natural language, with automatic indexing and section-level retrieval.

Indexes codebases using semantic embeddings for natural language search, enabling developers to find code with queries like 'how does authentication work'.

Semantic, on-demand skill retrieval for Claude Code that saves tokens and improves skill discovery by replacing the native skill listing with vector embedding search.

Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.

A tiny RAG-lite retrieval engine that indexes files on disk and provides semantic search via MCP, returning relevant text chunks (file, line, score) without generating answers.

An MCP server that enables hybrid semantic and keyword retrieval over your documents, using PostgreSQL and pgvector as the backend. It fuses rankings from both methods to provide high-quality search results to the language model.

MCP server that searches documents in Qdrant using embeddings from LMStudio. Takes a text query, converts it to a vector via LMStudio's OpenAI-compatible API, and performs semantic search in Qdrant.

An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.

Enables Claude to store and retrieve information with semantic search using Qdrant vector database, providing persistent memory for conversations, code, and documentation.

An MCP server for semantic code search using Qdrant vector database, enabling natural language queries to find relevant code snippets across indexed codebases.

A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.

Enables semantic search over documentation stored in a Vectorize database using the Cloudflare Agents SDK, allowing users to query indexed content via natural language.

Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic

Combines Neo4j graph database with vector search using OpenAI embeddings for intelligent semantic search across knowledge graphs.

A Model Context Protocol server that searches transcript segments in a Turso database using vector similarity, allowing users to find relevant content by asking questions without generating new embeddings.

A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.

Enables natural-language search over locally indexed files such as markdown, text, images, videos, and PDFs, and retrieves indexed text or media metadata by path. It lets Cursor query a local embedding index built with Gemini and SQLite.