Discover our curated collection of MCP servers for api development. Browse 9132servers and find the perfect MCPs for your needs.
Integrates the Dify AI API to serve as a Model Context Protocol server.
Provides an MCP server implementation for interacting with the Unstructured API, offering tools to manage data sources, destinations, and workflows.
Enables AI assistants to manage and operate GitHub Actions workflows.
Retrieves information from the Pinecone Assistant service.
Fetches and transforms web content into various formats such as HTML, JSON, Markdown, and plain text.
Enables Model Context Protocol (MCP) clients to interact with RabbitMQ queues and topics.
Integrates with Freshdesk to enable AI models to perform support operations, such as ticket management and updates.
Enables AI assistants to interact with the Alibaba Cloud Yunxiao DevOps platform.
Demonstrates Model Context Protocol (MCP) integration with Pokemon data through a client, server, and HTTP interface.
Provides real-time cryptocurrency analysis via CoinCap's API, enabling analysis of market trends and tracking of historical data.
Enables AI assistants to generate images, text, and audio through the Pollinations APIs using the Model Context Protocol.
Manages Redis Cloud resources using natural language through the Model Context Protocol.
Retrieves IP address details using the ipinfo.io API.
Orchestrates research using Claude and Perplexity/GPT/Gemini models via OpenRouter.
Enables AI models to interact with a global network measurement platform through natural language.
Connects to Bluesky and provides tools to interact with the ATProtocol, enabling natural language access and integration with LLM-based applications.
Enables applications to provide context to large language models for Algorand blockchain interactions.
Enables integration between Claude AI and desktop applications through Cursor IDE, facilitating AI-powered development workflows.
Enables AI agents to access real-time Binance cryptocurrency market data.
Enables seamless integration between LLM applications and RAG data sources and tools through the Model Context Protocol.
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