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.
Enables AI assistants to interact with the Scorecard REST API for exploring endpoints, making test requests, and integrating the SDK into applications.
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 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.
Provides AI assistants with access to OpenAPI specifications, enabling API discovery, schema retrieval, and direct API execution with support for OAuth 2.0 and other authentication methods.
A service that enables agents to build deterministic workflows across apps, databases and APIs using natural language, handling schema mapping, drift detection, and execution of integration pipelines automatically.
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.
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.
Optimizes REST API calls for AI agents by returning compact schemas instead of full responses, allowing agents to fetch only needed fields via jq masks, reducing token consumption by up to 50x.
CLIRank - API discovery for AI agents. APIs scored on CLI relevance: auth method, JSON responses, headless operation, pricing transparency. Search by capability, compare alternatives, read agent-contributed docs. 6 MCP tools for discovery, comparison, and documentation. Agents contribute observations back - crowdsourced API docs by machines, for machines.
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.