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.
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.
Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.
Provides implementation guidance, code validation, and troubleshooting tools for Searchspring's e-commerce APIs including search, autocomplete, recommendations, and tracking. Helps developers properly integrate Searchspring functionality with platform-specific code examples and best practices.
Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.
So I tried out this cool tool I saw in a LinkedIn post https://openapitools.com All you need is your API schema (OpenAPI/Swagger), and it automatically generates an MCP schema for you. You can then drop it straight into Claude Desktop (or Cursor, LangChain, etc.) and instantly start chatting with
One workspace for every AI coding assistant. Governance tools for API lint, diff, persistent ledger, multi-model deliberation, security audit, and test verification. Works with Claude Code, Codex, Cursor, and Gemini CLI.
A standalone Model Context Protocol server that enables AI models to access the Australian Pharmaceutical Benefits Scheme (PBS) API data, including medicine listings, pricing, and availability information.
The Stripe Model Context Protocol server allows you to integrate with Stripe APIs through function calling. This protocol supports various tools to interact with different Stripe services.
A utility tool that analyzes Next.js application routes and provides detailed information about API paths, HTTP methods, parameters, status codes, and request/response schemas.
Transforms Swagger/OpenAPI documented APIs into conversational interfaces, enabling natural language interaction with APIs through an MCP server for use with AI assistants.
Probes your live API and classifies why each endpoint failed (root cause, evidence, and a calibrated confidence level), exposed over MCP so your AI assistant debugs from evidence instead of guessing. Works with FastAPI, Express, Next.js, tRPC, and GraphQL.
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.
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.