Mcp Test Server

Overview

The MCP Test Server is a lightweight, self‑contained implementation of the Model Context Protocol designed to give developers a quick, local playground for experimenting with MCP‑enabled AI assistants. By exposing a minimal set of resources and tools, it demonstrates how an external service can be discovered, queried, and invoked by a client such as Claude or any other MCP‑compliant model. This server is ideal for testing integration flows, debugging tool calls, and validating the shape of prompts before deploying to production.

The server’s core value lies in its simplicity. It runs as a single executable or container, requiring no complex configuration, and listens on a configurable port for standard MCP HTTP endpoints. Clients can discover available resources through the endpoint, fetch metadata about tools via , and send prompt requests that are routed to the appropriate tool handlers. Because it is intentionally lightweight, developers can spin it up on a local machine or CI pipeline to simulate real‑world interactions without incurring external costs.

Key features include:

• Dynamic resource discovery – Clients receive a JSON list of available tools and prompts, enabling automatic UI generation or dynamic call routing.
• Tool execution sandbox – Each tool endpoint validates input schemas, performs a simple operation (e.g., echoing data or computing basic math), and returns structured results, illustrating how a real tool might behave.
• Prompt templating – The server supports placeholder substitution, allowing developers to test prompt variations and see how the model’s response changes in real time.
• Logging and introspection – All incoming requests are logged with timestamps, making it straightforward to trace the sequence of calls during debugging sessions.

Typical use cases for this test server include:

• Rapid prototyping – Quickly validate that an MCP client can discover and invoke a tool before committing to a full‑fledged backend.
• Continuous integration testing – Integrate the server into test suites to ensure that tool contracts remain stable across model updates.
• Developer onboarding – New team members can run the server locally to learn how MCP clients interact with external services without needing access to production endpoints.

By providing a concrete, easy‑to‑run example of an MCP server, the MCP Test Server bridges the gap between abstract protocol specifications and tangible developer workflows. It showcases how external capabilities can be exposed, discovered, and consumed by AI assistants, ultimately accelerating the development of richer, more interactive AI applications.