MCP 服务器

Official Hugging Face MCP Server that connects AI assistants directly to the Hugging Face Hub ecosystem. Provides tools for searching and retrieving models, datasets, and research papers, running inference on thousands of Gradio-powered AI applications (Spaces), and accessing the full Hub API. Supports remote HTTP-streaming via https://huggingface.co/mcp with OAuth or Bearer token auth, as well as local stdio deployment. Works with Claude, Gemini CLI, VS Code, Cursor, and any MCP-compatible client.

MCP server for Replicate, which hosts thousands of open machine learning models behind a single API. Lets AI agents search models, run predictions (image, video, audio, and text generation), poll prediction status, and retrieve outputs. Useful for adding generative media and specialized ML capabilities to agent workflows without managing infrastructure.

Official OpenAI MCP server for integrating GPT models, DALL-E, and Whisper into agentic workflows. Provides tools for chat completion, image generation, audio transcription, and embeddings through the Model Context Protocol. Supports function calling, structured outputs, and streaming responses.

Official Anthropic MCP server providing direct access to Claude models through the Model Context Protocol. Enables AI agents to invoke Claude for sub-tasks like summarization, analysis, and code generation within agentic workflows. Supports streaming responses, system prompts, and multi-turn conversations.

Official MCP server for the Perplexity API Platform. Provides AI agents with real-time web search, deep research, and advanced reasoning capabilities through Sonar models. Includes tools for quick web search, conversational Q&A with citations, comprehensive deep research reports, and complex analytical reasoning. Returns answers with source attribution and supports configurable timeouts for long research queries.

MCP server for the Google Maps Platform. Enables AI agents to geocode addresses, search for places, retrieve place details, and compute directions and distances, giving models location awareness and routing from AI-powered tools.

Official MCP server for Qdrant vector search engine. Acts as a semantic memory layer enabling AI agents to store and retrieve information using vector similarity search. Supports storing text with metadata, semantic querying, configurable embedding models via FastEmbed, and both cloud-hosted and local Qdrant instances. Useful for building RAG pipelines, code search, knowledge bases, and long-term agent memory.

Official dbt Labs MCP server for analytics engineering workflows. Lets AI agents run dbt commands (build, run, test), inspect models and lineage via the dbt project, and query the Semantic Layer and Discovery API in dbt Cloud. Useful for transforming data, validating models, and answering metric questions grounded in governed definitions.

MCP server that provides access to Wikipedia content. Lets AI agents search articles, fetch full or summarized page content, and resolve references, giving models reliable, citable background knowledge for research and question answering.

The official Azure MCP Server brings Microsoft Azure to AI agents. It lets models query and manage Azure resources through natural language — Storage blobs and tables, Cosmos DB, Azure SQL, Key Vault, Monitor/Log Analytics (KQL), App Configuration, and more — and run Azure CLI commands, enabling cloud automation and infrastructure workflows directly from your tools.

Contentful's official MCP server for the Content Management API. Gives AI agents tools to create, edit, organize, and publish content, manage content models and assets, and work across spaces and environments. Useful for automating editorial workflows and content operations in a Contentful-backed headless CMS.

E2B's MCP server gives AI agents the ability to run arbitrary code in secure, isolated cloud sandboxes. Each sandbox is a fast-booting micro-VM where models can execute Python and shell commands, install packages, read and write files, and capture stdout/stderr — ideal for code interpretation, data analysis, and agentic workflows that need real execution.

Metabase's built-in MCP server that lets AI clients connect directly to a Metabase instance, scoped to the connecting user's permissions. Enables agents to discover databases and models, run queries, and retrieve results and dashboards so teams can ask questions of their business intelligence data in natural language.

Prisma's official MCP server that lets AI tools manage Prisma ORM projects and Prisma Postgres databases through natural language. Provides both a local server for working with a project's Prisma schema and migrations, and a remote server for provisioning and managing Prisma Postgres databases. Useful for scaffolding models, generating and applying migrations, and running database workflows from an AI coding assistant.