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MCP 工具与服务目录

找到适合你的 MCP Server,快速完成接入

按功能、传输方式和来源整理 MCP Server,提供安装命令、配置方式、仓库与文档入口,方便你快速比较并接入合适的服务。

正式条目

87,640

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36,828

最近生成

2026-05-22

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Enhanced MCP memory system with dynamic compression, context management and thinking process integration. Based on the original MCP memory server.

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Enables searching personal knowledge vaults using hybrid semantic and keyword matching through the Fondu Knowledge Vault API. Retrieves and reranks relevant information from personal knowledge bases with flexible authentication options.

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An MCP server that enables interaction with Ky2Help, providing tools to retrieve and manage Ky2Help changes. It leverages the Model Context Protocol to bridge language models with Ky2Help management systems.

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A context-efficient proxy that replaces individual tool schemas with three meta-tools for semantic search, schema retrieval, and tool routing. It enables agents to manage hundreds of backend tools while maintaining a constant context footprint of approximately 500 tokens.

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Enables OSINT research by searching usernames across hundreds of social networks and websites, and analyzing URLs to extract information and find associated usernames using the Maigret tool.

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A server-based tool that enables the generation of mathematical animations from natural language prompts by leveraging Manim.

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Helps users discover and install MCP servers from PlayMCP using hybrid search (keyword matching + semantic search) based on their requests, and provides installation guidance.

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Meelion MCP ) connects AI assistants and automated clients to Meelion's structured data: a Brazilian platform for researching, comparing, and tracking investments, focusing on fixed income, indicators (Selic, CDI, IPCA, savings) and exchange rates (dollar, euro, gold, silver, Bitcoin).

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Provides AI agents with persistent long-term memory capabilities using semantic search. Enables storing, retrieving, and searching memories through three core tools integrated with Mem0 and vector storage.

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A robust server for managing long-term agent memory using Mem0, providing efficient storage and retrieval of agent memories with a lightweight Python-based implementation.

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A powerful, production-ready context management system for Large Language Models (LLMs). Built with ChromaDB and modern embedding technologies, it provides persistent, project-specific memory capabilities that enhance your AI's understanding and response quality.

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Enables AI assistants to remember user information across conversations using vector search technology. Built on Cloudflare infrastructure with isolated user namespaces for secure, persistent memory storage and retrieval.

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A cloud-based vector memory service that provides AI assistants with persistent storage, semantic search, and entity management via the Model Context Protocol. It features multi-tenant isolation and bidirectional synchronization with macOS and Google contacts and calendars.

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Enables persistent storage and retrieval of decisions, settings, and operational rules across chat sessions, maintaining context continuity and decision consistency for long-term development projects through structured memory management.