"How to create an MCP tool" matching MCP servers:

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

A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test and interact with any REST API endpoints directly from your development environment.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

Enables testing how different MCP clients handle tool results containing both content and structuredContent, including outputSchema enforcement and mismatch scenarios.

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

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

An MCP server for interacting with Treasure Data API, allowing users to retrieve database information and check server status through natural language queries.

Enables MCP agents to create test webhook endpoints, read incoming requests, validate payloads against Hookline validators, and manage mock responses directly from the editor.

Enables AI agents to discover and read Typeship API documentation and execute API operations through schema-validated MCP tools, with optional read-only mode and configurable result limits.

An MCP server for Tern that enables the generation, verification, and management of webhook handlers across over 16 platforms and various frameworks. It provides tools to create verified endpoints, debug signature failures, and manage failed event replays via dead letter queues.

Converts any OpenAPI/REST API into MCP tools with dynamic server switching, variable substitution, and runtime configuration. Enables seamless interaction with multiple API environments through natural language without pre-configuration.

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.

An MCP server that enables LLMs to make arbitrary HTTP requests (GET, POST, PUT, DELETE, etc.) with custom headers, bodies, and cookies, supporting JSON and error handling.

An MCP server that makes backend API requests and packages request+response pairs as evidence to prove an endpoint works.

A generic MCP (Model Context Protocol) server that bridges any GraphQL API to Claude Code. It introspects your GraphQL schema and exposes each query and mutation as an individual tool, letting Claude interact with your API directly.

Enables MCP-compatible AI clients to query, search, create, and update YApi API definitions and categories using natural language, with write operations excluding deletion for safety.

Universal HTTP client tool for LLM agents. Enables Claude and other MCP-compatible agents to perform GET, POST, PUT, DELETE, and other HTTP requests to any URL, including localhost and internal network addresses.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

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.

An MCP server for interacting with MockServer, enabling AI assistants to create mock HTTP expectations, verify requests, clear state, and manage MockServer instances programmatically.