"Building a Flutter and Go Application with PocketBase Backend Deployed on Oracle Cloud" matching MCP servers:

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.

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

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

Enables MCP clients to exercise HTTP tools against an upstream service, secured via bearer-token authentication, along with a resource and prompts.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

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.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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.

Enables AI assistants to explore and interact with the Facets Control Plane API via natural language, supporting operations like searching endpoints, loading schemas, and making authenticated API calls.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Enables Claude to create local, persistent mock REST APIs on demand from plain-language descriptions, with data written to disk so it survives restarts.

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.

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 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.

A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test and interact with any REST API endpoints directly from your development environment.

Validates OpenAPI specs from files, inline content, or URLs, and generates prompts for agent developers based on the API analysis.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

An MCP server for interacting with Treasure Data API, allowing users to retrieve database information and check server status through natural language queries.

Enables LLMs to send HTTP requests to a local development server, allowing interaction with APIs running on localhost.

An MCP server that provides tools to interact with the JSONPlaceholder fake REST API for testing and prototyping, supporting CRUD operations on posts, comments, todos, and users.