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cocaxcode/api-testing-mcp

by Various

The most complete MCP server for API testing. 27 tools: requests, assertions, flows, OpenAPI, mock data, load testing, collections, environments, cURL export, response diffing. Zer

C

MCP

cocaxcode/api-testing-mcp

Added 1 June 2026

#ai-tools #api-testing #claude #codex #cursor #gemini #http-client #load-testing

Overview

An MCP server that provides 27 tools for API testing. It covers requests, assertions, flows, OpenAPI, mock data, load testing, collections, environments, cURL export, and response diffing. Requires zero configuration and zero dependencies.

Best for

Best for
Developers who want a lightweight, zero-config MCP server for API testing

Use cases

  • Running API request assertions
  • Generating mock data for endpoints
  • Comparing API responses with diffing

How to use

Install

claude mcp add --scope user api-testing -- npx -y @cocaxcode/api-testing-mcp@latest

Tools exposed

  • only_fields
  • max_body_bytes

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, ChatGPT

Notes

An MCP server that provides 27 tools for API testing. It covers requests, assertions, flows, OpenAPI, mock data, load testing, collections, environments, cURL export, and response diffing. Requires zero configuration and zero dependencies.

2 stars on GitHub. Last updated 2026-05-02. Licensed MIT.

Use cases

  • Running API request assertions
  • Generating mock data for endpoints
  • Comparing API responses with diffing

Pros

  • Zero configuration and zero dependencies
  • Comprehensive set of 27 testing tools
  • Supports multiple testing workflows in one server

Cons

  • Low star count suggests limited adoption or maturity
  • May lack extensive documentation or community support
  • Unclear maintenance status

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Zero configuration and zero dependencies
  • Comprehensive set of 27 testing tools
  • Supports multiple testing workflows in one server

Cons

  • Low star count suggests limited adoption or maturity
  • May lack extensive documentation or community support
  • Unclear maintenance status
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