"Creating a Cash-Generating Chain with MCP" matching MCP servers:

Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

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.

An open standard server implementation that enables AI assistants to directly access APIs and services through Model Context Protocol, built using Cloudflare Workers for scalability.

An MCP image generation server based on the Flux Schnell model that provides API access for generating images from text prompts with customizable dimensions and seeds.

Provides a standardized MCP interface for interacting with HTTP tools and services, enabling unified API access and management.

Enables API development directly from MCP clients by creating and editing collections, running requests through the real CLI, generating documentation, and starting mock servers.

Enables AI agents to dynamically discover and interact with APIs through Swagger/OpenAPI specifications and Postman collections using a strategic four-tool approach. It streamlines API integration by providing universal tools for endpoint discovery, detailed request information, and authenticated execution.

Lets AI assistants safely explore a Matrix42 instance by discovering web services and the data model, running validated ASQL queries, searching the service desk, and previewing ticket actions — read-only by default and without exposing credentials.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Enables LLMs to make HTTP requests with OAuth2, session cookies, retry logic, and cURL command generation, while providing security features like SSRF protection and TLS enforcement.

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.

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

TrustPilot for APIs, built for AI agents. Independent reliability ratings for APIs and MCP servers — look up trust scores, compare providers side by side, and leave reviews from real agent traffic.

MCP server for discovering and calling 400+ practical APIs through six compact tools, with free catalog search and pay-per-call x402 execution on Base.

Enables AI agents to connect to any GraphQL endpoint, introspect schemas, and execute queries or mutations through auto-generated tools.

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.

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.

Enables API troubleshooting and payload operations for SAP SuccessFactors, including Compound Employee SOAP queries and OData extraction, through MCP over stdio.

MCP server for scraping with declarative configs