"Creating an MCP Server Using an API" matching MCP servers:

Enables AI to manage and interact with a running magic-api instance, including CRUD operations on APIs, groups, functions, and datasources, with built-in magic-script knowledge.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

A Multi-Agent Conversation Protocol Server for the GitHub API, auto-generated using AG2's MCP builder, allowing users to interact with GitHub services through natural language.

An MCP server for the VTEX Subscriptions API (v3) that enables managing subscription services through natural language interactions, auto-generated using AG2's MCP builder.

An auto-generated MCP server that enables interaction with the OpenAI API, allowing users to access OpenAI's models and capabilities through the Multi-Agent Conversation Protocol.

A Model Context Protocol server that allows Claude to make API requests on your behalf, providing tools for testing various APIs including HTTP requests and OpenAI integrations without sharing your API keys in the chat.

Enables full ABAP development workflows against SAP systems via the ADT API, including reading and editing objects, running code, managing transports, executing tests, and performing code analysis.

A server implementation of the Model Context Protocol (MCP) that provides REST API endpoints for managing and interacting with MCP resources.

An MCP Server that enables natural language interaction with the Open Policy Agent REST API, allowing users to manage policies, decisions, and data through conversational interfaces.

Enables Gemini-powered multimodal analysis (video, audio, image, documents), Google search, and code execution via the API易 service. Supports Docker deployment and flexible configuration.

Cuts AI token costs by running user code in a secure sandbox, so data never enters the context window, enabling efficient data processing with MCP protocol.

A lightweight TypeScript-based MCP server that demonstrates how to build custom MCP tools by implementing a simple addition calculator. Serves as a starting point for building MCP-compatible tools.

An auto-generated MCP server for Google's Serverless VPC Access API, enabling communication with Google Cloud VPC networks through natural language interactions.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with Google Workflows API, allowing management of workflow executions and definitions through natural language commands.

Allows LLMs to execute Wolfram Language code in a secure, session-based environment by providing an interface to interact with a Wolfram Mathematica kernel.

Enables running one Codex CLI task at a time in an isolated temporary folder, returning Codex's answer and a manifest of produced files for manual review and selective copying.

An MCP bridge that lets Codex supervise Reasonix as an implementation worker in an isolated Git worktree, ensuring safe delegation with scoped writes and sandboxed execution.

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

An integration tool that enables AI assistants like Claude to directly access and interact with Bitbucket repositories, pull requests, and code without requiring copy/paste operations.

An MCP server for Task Trellis that provides tools for AI coding agents to manage tasks, currently featuring a simple hello_world demonstration tool.

An MCP server that gives AI agents access to the full Cumulocity API surface through a compact code-mode interface.

An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.

An MCP server that enables AI applications to access 20+ model providers (including OpenAI, Anthropic, Google) through a unified interface for text and image generation.

An MCP server that manages an IPython kernel, allowing LLMs to execute Python code in a project's virtual environment.

MCP bridge between an AI assistant and the Godot editor, enabling control via 6 tools (call methods, run GDScript, screenshots, etc.) over WebSocket.

An MCP server that enables coding agents to execute and manage long-running shell commands asynchronously with capabilities for process monitoring, interaction, and lifecycle management.

MCP server to give every agent an ephemeral Linux sandboxes for executing shell commands.

An MCP server that lets Claude Code consult stronger AI models (o3, Gemini 2.5 Pro, DeepSeek Reasoner) when you need deeper analysis on complex problems.