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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

87,637

可复制安装

36,826

最近生成

2026-05-22

开发工具未说明

Enables developers to integrate privacy-preserving identity verification from the Self protocol into their apps. Provides integration guides, code generation, blockchain configuration reading, and debugging assistance for age verification, airdrop eligibility, and humanity checks.

开发工具未说明

Expose a decentralized P2P agent as an MCP server so Claude Code and other AI tools can discover peers, create groups, and send encrypted messages without intermediaries.

AI代理未说明

An MCP server that enables AI agents to manage multi-marketplace e-commerce operations by connecting to the SellerChamp API. It supports inventory reporting, cross-listing analysis, order management, and bulk updates across platforms like Amazon, eBay, and Shopify.

运维云端未说明

The first Model Context Protocol server for SellerCloud. Plug Claude into your catalog, inventory, orders, and channel listings — read-only, in five minutes.

开发工具未说明

A read-only MCP server that provides access to financial news, Wall Street Bets sentiment analysis, and detailed options data from sellthenews.org. It enables LLMs to retrieve real-time news feeds, search historical data, and analyze options chains or Greek exposure for specific tickers.

开发工具未说明

Change tracking for AI-era codebases. AI agents call it to log structured change events (entity + diff + reasoning) before the session ends, then query history with diff, blame, history, changeset, and search. Captures the intent that would otherwise evaporate.

搜索检索未说明

Content-addressed vocabulary protocol: 452 cognitive patterns with cryptographic identity. Agents sharing a handle (e.g. StateLock#5602) provably share meaning — mismatched vocabularies halt rather than silently drift.

开发工具未说明

MCP server that detects semantic (non-textual) merge conflicts between Git branches using AST-level analysis. Catches incompatible changes that Git merges cleanly — signature changes, removed exports, parameter changes, interface breaks, and cross-file dependency conflicts.

搜索检索未说明

Reduces token consumption by over 80% through intelligent file caching, returning only diffs for modified files and suppressing unchanged content. It features a suite of 12 tools for semantic search, batch reading, and efficient file editing to optimize LLM interactions with large codebases.

搜索检索未说明

Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.

搜索检索未说明

Provides a coherent memory layer for LLM agents that models beliefs as nodes in a constraint network to detect and surface semantic contradictions. It uses local embeddings and a hybrid geometric-logical energy model to identify conflicting information that requires review.

搜索检索未说明

The official MCP server for Semantic Pen - an advanced AI article generator and SEO content writer. Create, manage, and optimize SEO-friendly articles directly from Claude Code and Cursor Windsurf with powerful AI automation.

搜索检索未说明

Enables semantic search over markdown files to find related notes by meaning rather than keywords, and automatically detect duplicate content before creating new notes.

搜索检索未说明

Provides hybrid semantic and keyword code search for Claude Code using BM25 and vector retrieval. It enables indexing and searching local codebases with language-aware chunking and local embeddings.

搜索检索未说明

Enables AI agents to perform semantic search over codebases by converting natural language queries into efficient search patterns like grep and ripgrep. It utilizes LLMs to verify relevance and find code snippets that traditional keyword-based searches might miss.

开发工具未说明

Semantix-Verify is an MCP server for semantic validation of AI/LLM outputs. It exposes a single tool, verify_text_intent(text, intent_description, threshold), which uses a local quantized NLI cross-encoder (INT8 ONNX) to return a 0.0–1.0 probability that the text satisfies the given intent — and, when it doesn't, a structured correction prompt for agent retry loops. Useful for building com