OpenMCP Server

OpenMCP – Bridging Web APIs with AI Assistants

OpenMCP provides a unified, token‑efficient gateway that lets conversational AI models request data or invoke actions from any web API. By translating standard HTTP, gRPC, GraphQL, SOAP, and other protocols into the Model Context Protocol (MCP) format, it removes the friction that developers normally face when integrating disparate services into an AI workflow. The result is a single, consistent interface that can be added to any MCP‑compatible client—whether it’s Claude Desktop, Cursor, or a custom application—without the need for bespoke adapters.

The core value of OpenMCP lies in its server registry. Every server registered on the public index adheres to the OpenMCP specification, ensuring that clients can discover and interact with a broad spectrum of services—weather data, payment processing, database queries, and more—without writing new code for each domain. For developers, this means that a single API call can be routed to the appropriate server, automatically handling authentication tokens, request shaping, and response parsing. The registry also acts as a marketplace for community‑built connectors, accelerating feature rollout and fostering collaboration.

Key capabilities include:

• Token‑efficient communication: Requests are compacted into MCP messages, reducing bandwidth and cost for large language models.
• Automatic protocol conversion: REST OpenAPI specs, gRPC protobufs, GraphQL schemas, and even legacy SOAP or PostgREST definitions are parsed into MCP resources.
• Rich resource description: Each server exposes a declarative list of actions, parameters, and expected responses, enabling AI assistants to generate accurate prompts and tool calls.
• Secure credential handling: Environment variables or client‑side configuration can inject API keys, keeping secrets out of the model’s context.

Typical use cases span from customer support bots that need to pull real‑time ticket data, to financial advisors querying market feeds, to automation scripts that trigger cloud infrastructure changes. In each scenario, the AI assistant can issue a high‑level command—“Show me the latest sales figures for Q3”—and OpenMCP translates that into a precise API request, returning structured data that the model can use to formulate a response or perform further calculations.

Because OpenMCP servers are both standards‑based and openly registrable, developers can quickly spin up new connectors for internal APIs or third‑party services. The integration process is streamlined via the CLI, which injects server definitions into client configuration files with minimal effort. This plug‑and‑play model ensures that AI workflows remain modular, maintainable, and scalable as new services are added or existing ones evolve.