Discover Awesome MCP Servers

MCP-QA

An MCP server for the comprehensive analysis of Swagger 2.0 and OpenAPI 3.x contracts. It allows users to extract detailed information about endpoints, request/response schemas, parameters, and security configurations from API documentation.

WeChat Publisher MCP

A Model Context Protocol server that enables AI tools to automatically publish articles to WeChat Official Accounts, supporting Markdown-to-HTML conversion, image handling, and both preview and official publishing modes.

OctSSH

Provides LLMs with safe, controllable, and stateful SSH access to shell environments, enabling remote command execution and file transfers with async support and security features.

claw-mcp-toolkit

All-in-one MCP toolkit with 29 tools across 5 modules: crypto prices, web utilities, social media, finance tracking, and productivity. MIT licensed.

Patent Big Data MCP Server

Enables comprehensive patent information queries and analytics including fuzzy company search, patent search by various criteria (name, application number, applicant), and statistical analysis of patent portfolios including status distribution, application trends, and patent type classification.

Simple MCP Demo

A Python-based demonstration server showcasing multiple Model Context Protocol transport mechanisms, including stdio, SSE, and HTTP. It provides a functional reference for tool discovery and execution using a sample number addition tool.

calendly-mcp

Enables Claude to schedule, query, and cancel Calendly events via Calendly API v2, allowing direct event management without the public booking form.

JsHookMcp

The js hook toolkit that all you need

linear-mcp

MCP server connecting Claude to Linear for searching, creating, updating, and commenting on issues, teams, and projects.

shopify-mcp

Okay, here's a translation of "for Shopify API interaction including product, customer, order" into Chinese, along with some nuances and options depending on the specific context: **Option 1 (Most General):** * **中文:** 用于 Shopify API 交互，包括产品、客户和订单。 * **Pinyin:** Yòng yú Shopify API jiāohù, bāokuò chǎnpǐn, kèhù hé dìngdān. * **Explanation:** This is a straightforward and common translation. It's suitable for general documentation or explanations. **Option 2 (More Emphasis on "Handling" or "Working With"):** * **中文:** 用于 Shopify API 交互，处理产品、客户和订单。 * **Pinyin:** Yòng yú Shopify API jiāohù, chǔlǐ chǎnpǐn, kèhù hé dìngdān. * **Explanation:** The word "处理 (chǔlǐ)" means "to handle," "to process," or "to deal with." This option is better if you want to emphasize the actions you're taking with the data. **Option 3 (More Technical, Emphasizing Data Manipulation):** * **中文:** 用于 Shopify API 交互，涉及产品、客户和订单的数据操作。 * **Pinyin:** Yòng yú Shopify API jiāohù, shèjí chǎnpǐn, kèhù hé dìngdān de shùjù cāozuò. * **Explanation:** This is a more technical translation. "涉及 (shèjí)" means "involving" or "relating to," and "数据操作 (shùjù cāozuò)" means "data manipulation." This is suitable for technical documentation or code comments. **Option 4 (More Specific to Development):** * **中文:** 用于 Shopify API 交互，开发产品、客户和订单相关功能。 * **Pinyin:** Yòng yú Shopify API jiāohù, kāifā chǎnpǐn, kèhù hé dìngdān xiāngguān gōngnéng. * **Explanation:** This option is suitable if you are talking about developing features related to product, customer and order. "开发 (kāifā)" means "to develop", and "相关功能 (xiāngguān gōngnéng)" means "related features". **Key Vocabulary:** * **Shopify API:** Shopify API (No translation needed, commonly used as is) * **交互 (jiāohù):** Interaction * **产品 (chǎnpǐn):** Product * **客户 (kèhù):** Customer * **订单 (dìngdān):** Order * **用于 (yòng yú):** Used for * **包括 (bāokuò):** Including * **处理 (chǔlǐ):** To handle, to process, to deal with * **涉及 (shèjí):** Involving, relating to * **数据操作 (shùjù cāozuò):** Data manipulation * **开发 (kāifā):** To develop * **相关功能 (xiāngguān gōngnéng):** Related features **Which option is best?** The best option depends on the context. If you're writing general documentation, Option 1 is a good choice. If you're describing the actions you're taking, Option 2 is better. If you're writing technical documentation, Option 3 might be more appropriate. If you are talking about development, Option 4 is a good choice. I hope this helps! Let me know if you have any other questions.

skill-retrieval-mcp

Enables AI agents to search and retrieve over 89K skills on-demand at runtime, eliminating the need to manually install skills upfront.

pages-mcp

Enables uploading and serving static websites via MCP tools, with automatic path prefix injection for multi-file sites.

ClinicalTrials.gov MCP Server

Enables searching and retrieving information from the ClinicalTrials.gov database of over 400,000 clinical studies, including trial details, eligibility criteria, locations, and results across 220+ countries.

mcp-server-filemaker

An MCP server that provides AI assistants with direct access to FileMaker databases via OData v4 API, enabling CRUD operations, script execution, and schema introspection.

Mailgent MCP Server

Provides identity infrastructure for AI agents to manage email communications, including sending, replying, and organizing messages. It also includes a secure vault for managing credentials and generating TOTP codes.

AI-Powered Server-Client Computer Use SDK

File containing information about the use of artificial intelligence software development kit (SDK) on servers and clients for computer systems.

Legal Document RAG MCP Server

Enables semantic and keyword search over legal documents, conflict detection, and document overview, supporting Indonesian and English texts.

Muninn

A local-first persistent memory server that provides AI agents with deterministic, multimodal information retrieval across different sessions and projects. It enables long-term memory continuity using a 5-signal hybrid search engine and cognitive reasoning loops designed for complex development workflows.

Pulumi MCP Server

Enables AI assistants to manage cloud infrastructure using Pulumi by running commands like preview, deploy, and stack output retrieval through the Model Context Protocol.

pc-control-mcp

Enables remote PC control and system management through MCP, including hardware info, process and file operations, with security features like blocklists and audit logging.

The Graph Token API MCP

Official MCP server that turns The Graph’s Token API into a plug-and-play web3 data tool. Exposes ERC-20 & NFT metadata, balances, transfers, top-holder stats, prices, and more, allowing LLMs to run SQL queries on structured and indexed blockchain data.

LiDAR Harness MCP

An incremental validation engine that acts as a pluggable MCP middleware for code agents like Claude Code and OpenCode, reducing context overhead by 60-80% through a PGO-inspired four-layer verification architecture.

Tracora MCP Server

Connects Tracora brand and query data to MCP assistants, enabling listing of active brands and AI visibility queries via two read-only tools.

x-mcp-server

Enables reading public X (Twitter) content like profiles, tweets, and search results via a stealth browser, without official API costs.

Multi-Database MCP Server

A plugin-based MCP server that enables interaction with multiple databases (MySQL, PostgreSQL, MongoDB, SQL Server, Redis) through a unified interface with configurable read/write permissions and independent plugin architecture.

MCP Server

一个现代化的 AI 服务代理，它可以通过统一的 API 与多个 AI 提供商（Anthropic Claude、OpenAI）进行交互，并使用 Cloudflare Workers 在全球范围内进行部署。

Opengraph io MCP

MCP server for the OpenGraph.io API -- extract OG metadata, capture screenshots, scrape pages, query sites with AI, and generate branded images with iterative refinement.

MySQL Database Server

MySQL 数据库的 MCP 服务器。通过在 GitHub 上创建一个帐户来参与 yuru-sha/mcp-server-mysql 的开发。

arcgis-flagstaff

Enables querying City of Flagstaff open geospatial data via ArcGIS, including searching datasets, querying feature layers, and retrieving layer schemas.