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MCP Server ESA provides a bridge to Alibaba Cloud's Edge Security Acceleration (ESA) service, enabling AI assistants to manage edge routines, deployments, routes, and sites. Developed by Aliyun, this TypeScript implementation exposes over 20 specialized tools for operations including creating and deploying edge routines, managing code versions, configuring routes, and handling site records through the ESA API. The server authenticates with Alibaba Cloud using access keys and handles complex operations like code uploads to OSS, making it particularly valuable for developers who need to automate edge computing deployments or manage ESA resources through AI assistants.

> OpenClaw is powerful.

Enables interaction with Phabricator via MCP tools for task/revision management and RAG-based semantic search over indexed tasks and revisions.

Provides free Google Trends data (interest over time, term comparison, related queries, trending now, regional breakdown) to MCP-compatible AI clients without needing an API key.

Build your own Local MCP Client with LlamaIndex

An unofficial MCP server for Cambridge's CamCORS system, enabling supervision report management through a Chrome browser.

Provides access to real-time and historical water conditions of the Aare river in Switzerland, including water temperature, flow rates, swimming recommendations, and data from multiple monitoring locations along the river.

Fetches Wordle solutions from the Wordle API for dates ranging from May 19, 2021 to 23 days in the future.

Connects AI assistants to the ThinkPrompt platform, enabling management of style guides, requirements, projects, documents, and workflows through 85 tools.

Enables autonomous satellite agents to communicate and coordinate for orbital operations such as collision avoidance, maneuver planning, and mission execution.

Enables direct integration with YApi API documentation platform in MCP-compatible editors like Cursor, allowing users to query API details, list interfaces, and search endpoints by simply pasting YApi URLs.

A Simple WeatherForecastServer: Get Weather Easily and Freely

Provides US real estate data including housing stats, demographics, nearby amenities, area comparisons, cost-of-living analysis, and neighborhood search via free public APIs without any API keys.

Enables AI assistants to query and search library documentation from GitHub repositories or web pages using RAG and web scraping.

A practical governance framework for organizations adopting the Model Context Protocol (MCP), the open standard that lets AI agents connect to external tools, data sources, and systems.

Enables natural language interaction with your T-Invest brokerage account for portfolio analysis, dividend tracking, and optional trading with safety confirmations.

Enables sending and receiving Telegram messages through MCP clients like Claude Desktop and Gemini Spark.

This MCP server implementation provides a bridge to an OpenAI-compatible AI agent. Developed by Matt Levine, it allows for seamless integration of AI capabilities into applications through a standardized protocol. The server supports customizable tool names, environment variable configuration, and includes comprehensive testing scripts. It's designed for use cases requiring AI-powered task automation, natural language processing, or interactive chat functionalities within larger systems or applications.

Flexible multi-leg, multi-airport flight search that finds the cheapest route across an entire itinerary — available as a CLI and as an MCP server for AI agents.

This MCP implementation provides an interactive chat interface that combines Ollama's LLM capabilities with PostgreSQL database access. Built with TypeScript and leveraging the Model Context Protocol, it enables natural language querying of SQL databases. The system automatically generates SQL queries based on user input, executes them through a secure, read-only connection, and returns AI-interpreted results. Key features include schema-aware responses and support for the qwen2.5-coder:7b-instruct model. This implementation is particularly useful for data analysts, business users, and developers who need to quickly extract insights from PostgreSQL databases without writing SQL queries manually.