"DevOps tools: Docker, Kubernetes, ArgoCD, and Terraform" matching MCP servers:

Webhook management and testing tools for AI agents. Provides tools for sending, validating, generating, and debugging webhooks.

A comprehensive suite of HTTP and API testing tools that enables AI agents to perform requests, check endpoint health, and decode JWTs. It also provides utilities for URL parsing and detailed security analysis of HTTP response headers.

Enables AI assistants to execute GraphQL queries and retrieve schema information from any GraphQL endpoint.

Provides a standardized MCP interface for interacting with HTTP tools and services, enabling unified API access and management.

A Swagger/OpenAPI query tool for MCP clients like Cursor, enabling AI assistants to browse, search, and retrieve detailed API type information.

Enables interaction with Users and Products through a CRUD service REST API, providing tools for listing, creating, reading, updating, and deleting records via HTTP transport.

An MCP server that integrates various penetration testing tools, enabling security professionals to perform reconnaissance, vulnerability scanning, and API testing through natural language commands in compatible LLM clients like Claude Desktop.

Converts Dify tools' API to MCP (Model Control Protocol) compatible API, allowing tools created in Dify to be accessed from MCP clients like Cherry Studio.

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.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

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

Enables AI assistants to interact with Dev Proxy for creating configurations, finding documentation, and discovering best practices via the MCP standard.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

An MCP server that enables AI assistants to control HTTP Toolkit for intercepting, inspecting, and debugging HTTP(S) traffic from browsers, mobile devices, and Docker containers. It provides tools for server management, interceptor activation, and sending HTTP requests through natural language commands.

This is an MCP server that facilitates building tools for interacting with various APIs and workflows, supporting Python-based development with potential for customizable prompts and user configurations.

A Model Context Protocol server that enables LLMs to explore and interact with API specifications by providing tools for loading, browsing, and getting detailed information about API endpoints.

Provides an MCP server that automatically exposes API routes as MCP tools with input validation and authentication, enabling AI agents to call the same handlers as HTTP RPC.

Enables agents to call a website's own authenticated GraphQL and REST APIs directly as typed MCP tools, derived from captured browser sessions instead of scraping HTML.

A generic MCP server that dynamically converts OpenAPI-defined REST APIs into tools for LLMs like Claude. It supports multiple authentication methods and transport protocols, enabling seamless interaction with any OpenAPI-compliant API.

Enables MCP clients to connect over HTTP/SSE, call simple echo, arithmetic, uppercasing, and time tools, and run asynchronous tasks with approval elicitations via the Tasks extension.