"Building Agentic AI Solutions" matching MCP servers:

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

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.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

Parses Swagger 2.0 and OpenAPI 3.x specifications, exposing API endpoints, schemas, and authentication through MCP tools with local caching to reduce token usage.

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.

Code Mode MCP server for the OVH API. Two tools (search + execute) give LLMs access to all OVH endpoints via sandboxed JavaScript.

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.

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.

A generic MCP server that dynamically exposes any OpenAPI-documented REST API to LLMs by auto-discovering endpoints. It provides tools for exploring API capabilities and making authenticated requests directly through natural language interfaces.

Provides AI-enabled access to Amazon Business API documentation, sample code, and troubleshooting resources. Enables developers to search and retrieve API documentation, generate integration code, and get guided solutions for common errors during the API integration process.

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.

Enables AI agents to lint API artifacts (OpenAPI, AsyncAPI, Arazzo) and manage rulesets conversationally via the Model Context Protocol.

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.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.

HAL (HTTP API Layer) is a Model Context Protocol (MCP) server that provides HTTP API capabilities to Large Language Models.

A lightweight MCP server that enables LLMs to interact with any REST API via HTTP requests, with smart response truncation, TypeScript type generation, and field extraction.

Provides OpenAPI validation and analysis tools to assist developers in building Model Context Protocol servers. It generates developer context and specific agent prompts based on API specifications to streamline the creation of agentic workflows.

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.

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.