"A tool or library for executing Python code" matching MCP servers:

This MCP server enables AI agents to search and retrieve exact, cited passages from a large corpus of public-domain books, including full-text search, book metadata, chapters, quotes, and 'ask book' Q&A. Payments are handled via x402 micropayments on Base.

A custom MCP tool that integrates Perplexity AI's API with Claude Desktop, allowing Claude to perform web-based research and provide answers with citations.

Provides a 'library keeper' sub-agent that ingests PDF/EPUB books and answers questions grounded in them via local embedding search, with deterministic classification and knowledge gap logging.

Enables a persistent local library for mathematical PDFs with cached LaTeX extraction, full-text search in English and Greek, and page/image retrieval over MCP.

Enables locally-first literature research through an MCP host by collecting sources, parsing documents, retrieving evidence, validating citations, and exporting research records in multiple formats.

Turns a user's own Markdown wiki into a locally indexed knowledge base, enabling semantic search, per-page retrieval, source listing, and citation-backed RAG question answering. All embedding and generation run through a local Ollama instance, so queries and documents never leave the machine.

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.

A Python MCP server providing AI agents with tools for local knowledge base search, business context retrieval, and text summarization prompt generation.

Local MCP server that provides verified answers about Jimmer and internal libraries using a SQLite FTS5 knowledge base.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Enables semantic search over codebases using natural language queries, returning relevant code snippets with source locations. Integrates with Claude Code for automatic codebase exploration.

An MCP server that provides dynamic codebase context to Claude Code through tools like hybrid search, recent changes, and symbol definitions, enhancing AI-assisted coding with local RAG.

Enables agents to run semantic search across one or more local project directories by automatically maintaining a LAN-local Qdrant index with Ollama embeddings. Indexing, staleness checks, and incremental updates happen transparently, so users can query code by meaning without managing collections, chunks, or hashes.

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.

Self-hosted hybrid code search MCP server with text, symbol, and semantic search layers. Runs locally, no third-party MCP servers, LSP, or SaaS.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.

Provides a retrieval/MCP knowledge server for the Unreal Engine Python API, enabling AI agents to retrieve real signatures and documentation before writing code.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.