"Developing a Flutter application with embedded React Native" 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.

A REST API built with FastAPI that exposes endpoints via Model Context Protocol (MCP), allowing clients to interact with CRUD operations through MCP interfaces.

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.

Automated QA for .NET microservice backends and React frontends, enabling API contract testing, UI crawling, YAML flows, and run diffing against a stage environment.

Enables AI assistants to search, analyze, and debug application API traffic captured by Tusk Drift, including HTTP requests, database queries, distributed traces, latency metrics, and error rates.

AI-native HTTP security testing MCP server — 18 tools with raw HTTP/1.1 + HTTP/2 control

Enables interaction with AIApp BaaS authentication system through keyword-based document search and automatic generation of framework-specific client code. Supports React, Next.js, Vue, and Vanilla JS with TypeScript integration and automatic project ID injection.

Provides tools to communicate with a service dependency API, enabling users to query and interact with service relationship data and dependency mappings.

Enables AI assistants to configure and manage session-based REST and WebSocket mock servers for application development and testing. It allows for dynamic endpoint setup, request history inspection, and real-time WebSocket communication through natural language commands.

Converts FastAPI application OpenAPI documentation into MCP tools for AI assistants to efficiently query API information. Reduces token consumption by enabling on-demand, structured API queries instead of loading complete OpenAPI specifications.

A server based on Model Context Protocol that parses Swagger/OpenAPI documents and generates TypeScript types and API client code for different frameworks (Axios, Fetch, React Query).

A TypeScript-based template for developing Model Context Protocol servers with features like dependency injection and service-based architecture, facilitating the creation and integration of custom data processing tools.

A Model Context Protocol server that enables LLMs to explore and interact with API specifications by providing tools for loading, browsing, and getting detailed information about API endpoints.

A Model Context Protocol server that enables interaction with Chop's Setup system, providing an interface to retrieve setup information via a REST API.

Enables AI assistants to interact with the Nimble REST API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables AI assistants to interact with the Roark REST API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

A generic MCP server that dynamically converts OpenAPI-defined REST APIs into tools for LLMs like Claude. It supports multiple authentication methods and transport protocols, enabling seamless interaction with any OpenAPI-compliant API.

A standalone MCP server for API testing and management, allowing AI assistants to interact with RESTful APIs through natural language.