"Using Claude Desktop and Code MCP to manage Google Cloud Platform/Vertex AI projects" matching MCP servers:

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

A bridge that enables any LLM to access and interact with documented REST APIs through the Model Context Protocol (MCP).

A minimal MCP server that auto-generates tools from your OpenAPI spec, optimized for Vercel.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Automatically converts Swagger/OpenAPI specifications into dynamic MCP tools, enabling interaction with any REST API through natural language by loading specs from local files or URLs.

Converts any REST API endpoints into MCP tools, enabling AI clients like Cursor and Claude Desktop to call internal services directly.

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.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

Enables interaction with Google Ads through the Google Ads API using GCloud authentication. Supports GAQL query execution, performance data retrieval, account management, and resource discovery with pagination and multiple output formats.

MCP server that fetches API responses and generates ready-to-use model/POJO classes in your configured language, with built-in login/refresh token handling.

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

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.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Turn any GraphQL API into MCP tools. Zero config, zero code. Auto-introspection, flat InputObject schemas for better LLM accuracy, smart truncation, retry logic with exponential backoff.

An MCP server for validating JSON against schemas, checking email deliverability, verifying URLs, assessing data quality, and validating API responses using RFC-compliant checks and heuristic analysis.

Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.

Automatically converts any OpenAPI specification or Postman Collection into an MCP server, enabling AI assistants like Claude to directly interact with REST APIs without writing any code.

Schema Validator AI - MCP server providing AI-powered tools and automation by MEOK AI Labs

Webhook management and debugging. Validate signatures, log events, replay, and analyze webhook traffic.

An LLM-driven API testing platform exposed over MCP, enabling declarative test definition and DAG-based execution.