Discover our curated collection of MCP servers for data science & ml. Browse 10430 servers and find the perfect MCPs for your needs.
Stores and retrieves information from a Qdrant vector database using the Machine Control Protocol.
Enables natural language interaction with a Neo4j graph database through Claude Desktop.
Enables real-time voice translation between languages, powered by lightning-fast AI inference.
Provides a Model Context Protocol (MCP) server for seamless access to the Zerion API.
Enables AI agents to access medical AI capabilities via a RESTful API, facilitating advanced diagnostic support and personalized healthcare.
Integrates AI code review capabilities for GitHub and GitLab pull and merge requests.
Extracts and structures Ant Design v4 component documentation into JSON for AI agent analysis.
Integrates a LangGraph agent with ChatGPT Enterprise via a standardized Model Context Protocol server.
Empowers AI agents to perform any action within the Unity Editor using its comprehensive API.
Provides a SQLite-backed server for persistent memory storage, full-text retrieval, and relationship graph traversal for AI assistants.
Enables AI tools to securely query and introspect PostgreSQL databases, offering optional SSH tunnel connectivity.
Provides agent-ready API access to Blockscout analytics data via the Model Context Protocol (MCP).
Integrate Claude with Google NotebookLM to generate podcasts, videos, quizzes, and other content through natural language prompts.
Integrate with the EDINET API to access and process financial disclosure data directly from MCP clients.
Enables AI agents on the same computer to communicate securely via a shared local file.
Connect AI agents to the RustChain blockchain and BoTTube video platform through a Model Context Protocol server.
Empower AI assistants with deep research capabilities across multiple providers, enabling query submission, progress tracking, and retrieval of synthesized reports with cross-referenced citations.
Dynamically loads and switches between thousands of Model Context Protocol (MCP) servers and their tools at runtime from a single entry point, optimizing AI agent efficiency and development workflows.
Evaluates AI safety and ethical alignment for LLM applications using a care-centered framework.
Provides a self-hosted, containerized platform designed to enable AI agents, particularly 7B–30B-class open-weight models, to reliably perform complex tasks through schema-validated Capability Packs and native Model Context Protocol (MCP) integration.
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