MCP 服务器

Provides persistent memory capabilities through a knowledge graph stored in a local JSON file. Enables AI agents to create, read, update, and delete entities and their relationships. Useful for maintaining context across conversations, storing user preferences, and building structured knowledge bases that persist between sessions.

Provides a structured sequential thinking tool through the Model Context Protocol. Enables AI agents to break down complex problems into numbered thought steps, revise previous thoughts, branch into alternative paths, and adjust the total number of steps dynamically. Useful for multi-step reasoning, planning, and analysis tasks that benefit from explicit step-by-step thinking.

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 ElevenLabs audio platform. Gives AI agents text-to-speech, voice cloning, speech-to-text transcription, sound-effect generation, and voice library management. Useful for building voice agents, narration, audiobooks, dubbing, and accessible audio experiences.

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.

MCP server for Langfuse, the open-source LLM observability and prompt management platform. Enables AI agents to fetch and render managed prompts, list prompt versions, and query traces, helping teams manage prompts and inspect LLM application behavior from AI-powered tools.

An MCP server that lets AI assistants delegate work to the Google Gemini CLI, taking advantage of Gemini's very large context window for whole-file and codebase analysis. Exposes tools to ask Gemini questions with file references, brainstorm ideas, and stream long responses in chunks, so a client model can offload large-context reasoning to Gemini without leaving the current session.

MindsDB's MCP integration gives agents access to AI workflows, data integrations, and automation capabilities through the MindHub platform.