"A generic RESTful API request tool for testing and integration" matching MCP servers:

A lightweight, local-first MCP server for executing HTTP requests and managing API collections and environments without cloud dependencies. It enables testing APIs, handling authentication, and importing OpenAPI specifications directly within MCP-compatible workflows.

Enables automatic HTTP requests (GET, POST, PUT, DELETE, etc.) with JSON validation and proxy support. Supports custom headers, request bodies, and environment variable configuration for seamless API integration.

A framework to use with AI to easily create a server for any service. Just drop the API Documentation in it and ask to create the MCP.

Enables Boneyard to call authenticated, stateless Streamable HTTP tools for searching tickets and adding ticket comments, with caller context, attribution, and bounded results.

Enables LLMs to perform addition calculations through a stdio-based MCP server with an add_numbers tool and type-safe validation.

A dynamic server that automatically discovers and executes scripts from a tools directory as isolated processes using the MCP protocol. It enables users to easily extend server capabilities by adding new tool scripts that communicate via JSON.

MCP server for testing GitHub Actions workflows locally using nektos/act.

Semantic navigator for MCP tools that finds relevant tools by natural language intent, reducing token usage by 95%.

Enables automated testing and coverage reporting for MCP services with test execution, file generation, and mock service creation. Provides comprehensive testing infrastructure including Jest integration, coverage reports, and health checks for the MCP ecosystem.

MCP server that enables AI agents to programmatically run tests, query results, and receive intelligent recommendations about test execution strategy.

Enables config-driven mocking of MCP servers for AI skill evaluation, dynamically registering tools from a schema and returning configurable static, fixture-based, or LLM-generated responses.

A Model Context Protocol server that provides a scratchpad tool for LLMs to organize thoughts, take notes, and plan approaches to complex problems.

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

A tool discovery MCP server that integrates with Azure DevOps wikis and code-graph-rag to match natural language goals to tools, enabling tool composition and proxy testing.

Encoding-aware, indentation-smart file tools for AI coding agents. 20+ tools including read/edit with automatic encoding detection, smart indentation conversion, SSH, SFTP, process management, and system utilities.

A server built on mcp-framework that enables integration with Claude Desktop through the Model Context Protocol.

Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

Demonstrates the proposed idempotencyKey mechanism on tools/call with server-side deduplication and conflict fingerprint rejection. Includes a runnable client demo showing retry dedup and conflict behavior.

Provides a unified MCP server to interact with multiple middleware (Loki, MySQL, Redis, RocketMQ, Elasticsearch, MongoDB) through a desktop application for connection management and configuration export.