Discover our curated collection of MCP servers for api development. Browse 9312servers and find the perfect MCPs for your needs.
Enables Claude or other AIs to interact with Iaptic data for insights into customers, purchases, and transactions.
Provides Model Context Protocol (MCP) services for the PLANKA platform.
Integrates external resources, tools, and prompts with the Anthropic AI SDK via the ModelContextProtocol.
Empowers intelligent assistants to answer domain-specific questions by leveraging RAG-based retrieval and Pinecone vector storage on custom knowledge bases.
Generates an MCP (Multi-Agent Conversation Protocol) server from an OpenAPI specification.
Deploys an unauthenticated Model Context Protocol (MCP) server directly on Cloudflare Workers.
Integrates AI assistants with OpenProject for comprehensive project management.
Manages calendar events and integrates a stamina system using Algebraic Data Types (ADT) and functional programming principles.
Implements a basic Model Context Protocol (MCP) server in TypeScript, following official specifications and best practices.
Implements a Model Context Protocol server, enabling AI models to integrate seamlessly with external systems and data sources.
Provides a Model Context Protocol server for accessing MantisBT objects via its REST API.
Showcases a basic example of developing and running serverless Model Context Protocol (MCP) applications using Netlify Functions.
Converts structured JSON data into Excel files, supporting custom headers and automated file management.
Exposes automated API tools via an MCP-compatible server, enabling seamless integration with AI agents and other clients.
Automates the creation and management of posts for an Astro blog deployed on Vercel via a REST API.
Interact with Microsoft Bookings by providing tools through the Microsoft Graph API.
Enriches user profiles by finding and returning social media links from public sources based on name and birth date.
Access and search top Hacker News stories.
Generates and renders infographics from a custom DSL syntax, serving them through various transport modes.
Perform Retrieval Augmented Generation (RAG) on local codebases using a raw Python implementation with support for multiple AI providers.
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