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Let AI send flexible HTTP API requests to connect services and automate workflows.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "api-mcp" yet — see the docs or source repo.
Use the GET method to request https://api.example.com/users?limit=10, add the Authorization: Bearer <token> header, and return a summary of the response and key fields.
Returns the API response and summarizes key fields, status code, and whether the request succeeded.
Send a POST request to https://api.example.com/orders with Content-Type application/json, include customerId, items, and totalAmount in the body, and tell me the creation result.
Outputs the API response, such as the order ID, processing status, or error message.
Call https://api.example.com/report with both valid and invalid API keys, compare status codes, error messages, and response differences, then summarize the testing conclusions.
Provides API authentication test results, compares behavior under different request conditions, and summarizes issues found.
Let LLMs make secure HTTP requests with auth, retries, and debugging support.
Configure authenticated endpoints and send API requests with uploads.
Deploy MCP servers over HTTP for AI-accessible text, math, and content tools.
Turn any OpenAPI API into callable AI tools with authentication support.
Call many AI models and read live web data from any MCP client.
Turn existing APIs and databases into MCP tools for direct AI use.