发现优秀的 MCP 服务器

trdizin-mcp

MCP server for querying TÜBİTAK TR Dizin academic database, enabling search of publications, journals, authors, and institutions without an API key.

Google Workspace MCP

A multi-account, token-efficient MCP server for Google Workspace services including Gmail, Calendar, Drive, Docs, and Sheets. It enables secure management of multiple accounts with compact data retrieval and keychain-backed authentication for efficient workflow automation.

Hormonaly MCP Server

Enables AI agents to access 24 clinical tools for evidence synthesis, protocol lookup, and decision support in peptide, hormone, and longevity medicine.

MCP Shamash

Enables security auditing, penetration testing, and compliance validation with tools like Semgrep, Trivy, Gitleaks, and OWASP ZAP. Features strict project boundary enforcement and supports OWASP, CIS, and NIST compliance frameworks.

Shopmium MCP Server

A custom MCP server that provides high-level tools for controlling Shopmium and Quoty apps on Android emulators, allowing for automated app navigation, interaction, and testing without needing to handle low-level implementation details.

mysql-mcp-server

Enables natural language querying of MySQL databases via Claude Code, allowing SELECT queries, table listing, and schema inspection.

Runware MCP Server

Enables lightning fast image and video generation using the Runware API, with tools for inference, upscaling, background removal, and more.

Tavily MCP Server

Provides AI-optimized web search capabilities and direct answers using the Tavily API for MCP-compatible assistants. It enables configurable searches with granular control over search depth, result counts, and domain filtering.

npm-trends-mcp

Provides weekly download counts and trend data for npm packages, enabling comparison of adoption velocity across JavaScript libraries.

SearXNG MCP Server

An MCP server that integrates with the SearXNG API to provide comprehensive web search capabilities with features like time filtering, language selection, and safe search. It also enables users to fetch and convert web content from specific URLs into markdown format.

Junipr MCP Server

Enables AI assistants to capture webpage screenshots, generate PDFs from URLs or HTML, and extract rich metadata like Open Graph and JSON-LD data. It provides tools for web-to-image/PDF conversion and structured data extraction through the Junipr API.

Kali Linux MCP Server

Provides access to Kali Linux security tools through a Docker container, enabling penetration testing and security assessments via MCP-compatible clients.

mcp-ops-server

An MCP server that gives AI assistants access to a multi-agent business operations platform with specialized AI services covering real estate, legal, translation, research, content creation, training, and more.

RapidAPI MCP Server

以下是将 RapidAPI Global Patent API 集成到 MCP 服务器并使用 SQLite 存储的实现方案： **标题：基于 RapidAPI Global Patent API 的 MCP 服务器实现，并使用 SQLite 存储** **概述：** 本方案描述了如何构建一个 MCP (Minimal Control Protocol) 服务器，该服务器利用 RapidAPI 的 Global Patent API 来检索专利数据，并将检索到的数据存储在 SQLite 数据库中。 该服务器将接收来自客户端的请求，调用 RapidAPI 的 Global Patent API，解析响应，并将结果存储到 SQLite 数据库中。 **组件：** * **MCP 服务器:** 负责监听客户端请求，处理请求，调用 RapidAPI，并将结果返回给客户端。 * **RapidAPI Global Patent API:** 提供专利数据检索服务。 * **SQLite 数据库:** 用于存储检索到的专利数据。 * **客户端:** 发送请求到 MCP 服务器，并接收响应。 **技术栈：** * **编程语言:** Python (推荐，易于使用，拥有丰富的库) * **MCP 框架:** 可以使用现有的 MCP 框架，或者自行实现简单的 MCP 协议处理。 * **RapidAPI 客户端库:** 可以使用 `requests` 库或其他 HTTP 客户端库来调用 RapidAPI。 * **SQLite 数据库库:** `sqlite3` (Python 内置) **实现步骤：** 1. **环境搭建:** * 安装 Python。 * 安装必要的 Python 库：`pip install requests` * 安装 SQLite (通常操作系统自带)。 2. **RapidAPI 密钥获取:** * 在 RapidAPI 注册并订阅 Global Patent API。 * 获取 API 密钥 (通常在 RapidAPI 控制面板中)。 3. **SQLite 数据库设计:** * 设计数据库表结构，用于存储专利数据。 例如： * `patents` 表： * `id` (INTEGER PRIMARY KEY AUTOINCREMENT) * `patent_number` (TEXT UNIQUE) * `title` (TEXT) * `abstract` (TEXT) * `inventors` (TEXT) * `assignees` (TEXT) * `filing_date` (TEXT) * `publication_date` (TEXT) * `raw_data` (TEXT) (存储完整的 API 响应，方便后续处理) * `created_at` (TIMESTAMP DEFAULT CURRENT_TIMESTAMP) * 创建数据库和表。 4. **MCP 服务器实现:** * **监听端口:** 服务器监听指定的端口，等待客户端连接。 * **接收请求:** 接收客户端发送的 MCP 请求。 * **解析请求:** 解析 MCP 请求，提取请求参数 (例如，搜索关键词，专利号等)。 * **调用 RapidAPI:** 使用 RapidAPI 密钥和请求参数，调用 Global Patent API。 * **解析响应:** 解析 RapidAPI 返回的 JSON 响应。 * **存储数据到 SQLite:** 将解析后的专利数据存储到 SQLite 数据库中。 * **返回响应:** 将结果 (例如，成功/失败，专利 ID 等) 封装成 MCP 响应，返回给客户端。 5. **客户端实现 (可选):** * 编写客户端程序，用于发送 MCP 请求到服务器，并接收响应。 **代码示例 (Python):** ```python import sqlite3 import requests import json # RapidAPI 配置 RAPIDAPI_KEY = "YOUR_RAPIDAPI_KEY" # 替换为你的 RapidAPI 密钥 RAPIDAPI_HOST = "global-patent.p.rapidapi.com" RAPIDAPI_ENDPOINT = "/patents/search" # SQLite 数据库配置 DATABASE_FILE = "patents.db" def create_table(): conn = sqlite3.connect(DATABASE_FILE) cursor = conn.cursor() cursor.execute(""" CREATE TABLE IF NOT EXISTS patents ( id INTEGER PRIMARY KEY AUTOINCREMENT, patent_number TEXT UNIQUE, title TEXT, abstract TEXT, inventors TEXT, assignees TEXT, filing_date TEXT, publication_date TEXT, raw_data TEXT, created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ) """) conn.commit() conn.close() def search_patents(query): url = f"https://{RAPIDAPI_HOST}{RAPIDAPI_ENDPOINT}" headers = { "X-RapidAPI-Key": RAPIDAPI_KEY, "X-RapidAPI-Host": RAPIDAPI_HOST } querystring = {"q": query} response = requests.get(url, headers=headers, params=querystring) if response.status_code == 200: return response.json() else: print(f"Error: {response.status_code} - {response.text}") return None def store_patent_data(patent_data): conn = sqlite3.connect(DATABASE_FILE) cursor = conn.cursor() try: patent_number = patent_data.get("patent_number") title = patent_data.get("title") abstract = patent_data.get("abstract") inventors = ", ".join(patent_data.get("inventors", [])) assignees = ", ".join(patent_data.get("assignees", [])) filing_date = patent_data.get("filing_date") publication_date = patent_data.get("publication_date") raw_data = json.dumps(patent_data) cursor.execute(""" INSERT INTO patents (patent_number, title, abstract, inventors, assignees, filing_date, publication_date, raw_data) VALUES (?, ?, ?, ?, ?, ?, ?, ?) """, (patent_number, title, abstract, inventors, assignees, filing_date, publication_date, raw_data)) conn.commit() print(f"Patent {patent_number} stored successfully.") except sqlite3.IntegrityError: print(f"Patent {patent_number} already exists in the database.") except Exception as e: print(f"Error storing patent data: {e}") conn.rollback() finally: conn.close() # 示例 MCP 服务器 (简化版) def handle_mcp_request(request): # 假设请求格式为 "SEARCH:关键词" if request.startswith("SEARCH:"): query = request[7:] print(f"Searching for: {query}") patent_results = search_patents(query) if patent_results and patent_results.get("results"): for patent in patent_results["results"]: store_patent_data(patent) return "SEARCH_SUCCESS" else: return "SEARCH_FAILED" else: return "INVALID_REQUEST" # 主程序 if __name__ == "__main__": create_table() # 创建数据库表 # 模拟 MCP 请求 mcp_request = "SEARCH:artificial intelligence" response = handle_mcp_request(mcp_request) print(f"MCP Response: {response}") mcp_request = "SEARCH:blockchain technology" response = handle_mcp_request(mcp_request) print(f"MCP Response: {response}") print("Done.") ``` **关键点：** * **错误处理:** 在调用 RapidAPI 和操作 SQLite 数据库时，需要进行充分的错误处理，例如处理网络错误，API 错误，数据库错误等。 * **数据清洗:** RapidAPI 返回的数据可能需要进行清洗和转换，才能更好地存储到数据库中。 * **并发处理:** 如果服务器需要处理大量的并发请求，需要考虑使用多线程或异步编程来提高性能。 * **安全性:** 保护 RapidAPI 密钥，避免泄露。 对客户端请求进行验证，防止恶意请求。 * **MCP 协议:** 根据实际需求，定义合适的 MCP 协议，包括请求格式，响应格式，错误码等。 * **分页处理:** 如果 RapidAPI 返回的结果集很大，需要进行分页处理，避免一次性加载所有数据。 * **速率限制:** 注意 RapidAPI 的速率限制，避免超过限制导致请求失败。 可以实现速率限制机制，例如使用令牌桶算法。 * **数据更新:** 可以定期更新数据库中的专利数据，以保持数据的最新性。 **改进方向：** * **使用更完善的 MCP 框架:** 例如 Twisted, asyncio 等。 * **添加缓存机制:** 使用 Redis 或 Memcached 等缓存数据库，缓存常用的查询结果，提高响应速度。 * **实现更复杂的搜索功能:** 例如，支持按发明人，申请人，申请日期等进行搜索。 * **提供 API 接口:** 将 MCP 服务器封装成 RESTful API，方便其他应用程序调用。 * **使用 ORM:** 使用 SQLAlchemy 等 ORM 框架，简化数据库操作。 **总结：** 本方案提供了一个将 RapidAPI Global Patent API 集成到 MCP 服务器并使用 SQLite 存储的基本框架。 您可以根据实际需求，对该方案进行修改和扩展，以满足您的特定需求。 请务必替换 `YOUR_RAPIDAPI_KEY` 为您自己的 RapidAPI 密钥。 这个示例代码只是一个起点，你需要根据你的具体需求进行修改和完善。

agentbus

A local message bus for AI agent sessions that enables Claude Code sessions to communicate directly via channels, allowing message sending and peer discovery without network or copy-paste.

postgres-mcp-server

Enables AI assistants to securely query and modify PostgreSQL databases, supporting SQL queries, table management, and schema inspection.

Financial Report Generator MCP Server

Enables generation of comprehensive financial reports for major companies like NVIDIA, Apple, Microsoft, and others. Supports multiple report types including basic summaries, comprehensive analysis, and financial ratio analysis with batch processing capabilities.

Tavily MCP Server

Provides AI assistants with real-time web search, intelligent data extraction from web pages, website mapping, and web crawling capabilities through Tavily's API. Enables comprehensive web research and content analysis through natural language interactions.

Micu Image MCP

Wraps the Micu image API as an MCP server for generating, editing, batch processing, and multi-reference image fusion, supporting GPT-image-2 and Grok models.

MCP Control: Your Cross-Platform Package Manager 🚀

一个跨平台管理所有 Minecraft 服务端的包管理器

safesign-mcp

Analyzes contracts for safety score and risk assessment, identifying dangerous clauses and dispute patterns, with recommendations for improvements.

Pure Data MCP Server

一个用于 Pure Data 的模型上下文协议 (MCP) 服务器。Pure Data 是一种开源可视化编程语言，也是一个用于实时计算机音乐的可修补环境。

gleaner

Enables academic literature collection and full-text downloading from multiple sources (CNKI, Elsevier, OpenAlex, etc.) via natural language commands.

Aikount MCP

MCP server for Spanish accounting for freelancers and SMEs, enabling AI agents to issue invoices, OCR expense PDFs, reconcile bank transactions, and prepare quarterly VAT (Modelo 303).

Apitomy Data Models MCP

An MCP server that wraps the @apitomy/data-models library for querying, validating, and editing OpenAPI and AsyncAPI documents.

Google Calendar MCP Server

Enables management of Google Calendar events across multiple calendars with natural language support, including searching events, checking availability, creating/updating/deleting events, responding to invitations, and auto-generating Google Meet links.

antics-mcp

Enables AI agents to deploy multiplayer web games as playable URLs with rooms, live state sync, and leaderboards, all through a single tool call.

@lifeng688/anki-mcp

MCP stdio server for controlling local Anki via AnkiConnect. Enables LLMs to manage Anki decks and notes through a standardized tool interface.