"Using Jira MCP to comment on subtasks, read descriptions, and create a test plan" matching MCP servers:

A Model Context Protocol (MCP) server that enables interaction with JIRA APIs through Claude Desktop, allowing users to search, create, update, and manage JIRA issues using natural language commands.

Enables AI agents to test WCF/SOAP and REST services directly, with WSDL discovery, authenticated calls, and deterministic assertions. Supports YAML multi-step scenarios with variable extraction, JSONPath/JSON Schema checks, and CI runs without spawning PowerShell or curl.

It enables AI agents and CI to run profile-driven SOAP/REST service tests with automatic login/session handling, test-customer locking, masked transaction-log/HAR catalog import, and cross-environment scenario execution.

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。

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Enables MCP clients to expose selected operations from local OpenAPI 3.0/3.1 documents as tools, with stdio serving or generated standalone server projects and read-only defaults.

An end-to-end test MCP server built with FastMCP that exposes a REST API as a set of tools for AI agents. It enables LLMs to perform CRUD operations on an upstream API by mapping HTTP methods to MCP tools.

A Spring Boot REST API testing server that supports functional testing with assertions, database queries, and performance testing with configurable concurrency and stress testing.

An MCP server that mocks payments, third-party API responses, and test data to enable QA flows for donation, checkout, SIP, and subscription pages without depending on a live gateway.

Provides AI agents and LLMs access to the test 12 API (Petstore Swagger) through standardized MCP tools for seamless integration and interaction.

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

Enables users to turn any API's documentation into a tested MCP server whose tools expose the API's own operations, with linting, contract tests, and live verification. It accepts OpenAPI/Swagger, Postman, RAML, WSDL, GraphQL, RSS, and HTML docs.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

Enables AI agents to drive API testing from YAML definitions, executing and chaining requests without hand-written curl, while keeping credentials out of the conversation and responses token-cheap, plus a VANDER-based QA review of endpoints.

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

Generates standalone, human-readable MCP servers from RAML 1.0 or OpenAPI 3.x specs, exposing one tool per resource and method that makes real HTTP calls. It understands Mule/Anypoint auth patterns such as Client ID enforcement and OAuth2, wiring the expected credentials from environment variables at call time.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.