"Using Jira MCP API in Python" matching MCP servers:

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

Enables validating API responses against expected schemas/JSON and listing OpenAPI endpoints to enforce API contracts between services.

Enables measuring, comparing, and health-checking endpoint response times through natural language, using tools to probe URL latency and compare two URLs.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

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

Provides access to Ics Ap Apis API endpoints with authentication support, enabling API interactions through the MCP protocol.

Enables interaction with Nullplatform's API endpoints for managing deployments, scopes, services, and other cloud resources through natural language using the official OpenAPI specification.

MCP server enabling AI agents to interact with the Kobra API through authenticated HTTP requests, including partner, bearer, and session auth.

Enables testing and interacting with any REST API endpoint directly from MCP clients like Claude and Cline. Supports GET, POST, PUT, DELETE, and PATCH requests with configurable authentication (Basic, Bearer, API Key), custom headers, SSL verification control, and response size limits.

Enables AI assistants to interact with Magic-API development environment, supporting script syntax query, API management, debugging, and knowledge search for efficient development.

An MCP server that generates MCP servers. Give it an API definition - OpenAPI 3.0/3.1 or a Postman collection - and it scaffolds a complete, runnable, ownable TypeScript or Python MCP server for that API.

Provides comprehensive development tools for Magic-API including documentation lookup, API testing, resource management, debugging with breakpoints, backup operations, and code search capabilities. Enables developers to efficiently build, test, and maintain Magic-API projects through natural language interactions.

Exposes REST API endpoints defined in an OpenAPI Specification as MCP tools, allowing AI models to call them via the ModelContext Protocol.

Enables AI assistants like Claude to interact with any REST API through typed, validated MCP tools. Provides a pattern to wrap REST APIs as MCP servers.

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.

A Model Context Protocol server that fetches detailed API documentation from a local platform using a document ID. It enables language models to retrieve specific endpoint specifications to assist with tasks like code generation and API integration.

Exposes Bruno API collections as Model Context Protocol (MCP) tools, allowing AI agents and MCP clients to interact with your API collections.

Transforms OpenAPI specs into an MCP server, enabling dynamic API interaction through natural language with automatic authentication and endpoint discovery.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

This MCP server enables interaction with Google's Verified Access API, allowing users to verify the security posture of Chrome OS and Chrome Browser devices through natural language commands.