"Generating API interface information from online FastAPI documentation for large models" matching MCP servers:

Lets developers and MCP agents run deterministic local HTML audits, turning inline HTML into structured findings for missing labels, unnamed buttons, skipped headings, ambiguous links, duplicate IDs, and missing landmarks. It also exposes a rule list and returns stable, actionable reports without external API keys.

Enables natural-language chat-driven API testing, letting users upload API specs, run deterministic pytest checks against live targets, inspect results, create defects, and view failure trends.

Starter scaffold for a workshop to build an MCP API testing server, intended to be extended through incremental steps.

Enables instant creation of mock API servers from OpenAPI specs or natural language descriptions, with built-in fake data generation, CRUD endpoints, and configurable delays/errors for testing.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

Enables AI agents to call real API endpoints and verify responses against OpenAPI specs, supporting contract testing, auth presets, spec diffing, and health checks.

Provides tools for AI agents to interact with the Orange Juice Online Judge API by managing problems and code submissions. Users can list problems, retrieve detailed descriptions, submit source code, and track submission status through natural language.

API Tester AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Enables learning and integration testing of the Model Context Protocol by evolving from a minimal server toward production-grade tools, resources, prompts, and agent interoperability.

Analyzes API requirements and source code, evaluates existing Postman test coverage, and generates or updates test automation with an optional draft pull request on GitHub.

基于fastmcp-ts开发的接口测试mcp工具，ai可以通过调用该工具对接口进行测试。

Enables AI agents to inspect, test, validate, compare, and debug HTTP APIs through a structured toolkit, with features such as secret redaction, response contract validation, regression comparison, health checks, and incident investigation workflows.

Enables benchmarking of Large Language Model APIs by measuring performance metrics such as generation throughput, prompt throughput, and Time To First Token (TTFT) with configurable concurrency levels and parameters.

Enables regex testing, replacement, splitting, validation, explanation, escaping, common patterns, and benchmarking through an MCP server.

An MCP Server that provides access to Google's Cloud Tool Results API, enabling applications to programmatically interact with test results from Firebase Test Lab and mobile app testing through natural language.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

Enables MCP-compatible clients to discover API endpoints from OpenAPI/Swagger specs, send HTTP requests, validate responses, and analyze status codes for automated API testing.

Scans OpenClaw/ClawHub skills for security vulnerabilities before installation. Detects prompt injection, data exfiltration, credential theft and RCE risks. Autonomous AI-to-AI flow with zero human intervention required.

Validates OpenAPI documents, JSON Schemas, and JSON payloads. Also compares OpenAPI specs and displays breaking changes.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.