"Finding Unity Developers Skilled in C#" matching MCP servers:

Goodday‑MCP is a lightweight Model Context Protocol (MCP) server designed to seamlessly integrate with the Goodday project management platform via its API v2. It enables querying of projects, tasks, and users—without altering any data—making it ideal for secure context-aware applications

A Node In Layers package that simplifies creation of MCP (Model-Control-Protocol) servers with tools for defining models, adding CRUD operations, and interacting with clients.

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.

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

MCP server for reading, writing, and organizing API documentation in Apidog.

Provides Plaid developers with sandbox integration tools for creating test items, reading financial data, simulating webhooks and login failures, plus docs-quality tools for API search and OpenAPI-vs-Postman-vs-docs drift checking.

Provides AI-enabled access to Amazon Business API documentation, sample code, and troubleshooting resources. Enables developers to search and retrieve API documentation, generate integration code, and get guided solutions for common errors during the API integration process.

Point Claude at any API. JitAPI figures out which endpoints to call and in what order — automatically. Register any OpenAPI spec, search endpoints in plain English, and orchestrate multi-step workflows across multiple APIs. No API keys required — works out of the box with local embeddings.

Enables AI assistants to help developers build on the monday.com GraphQL API by validating queries, explaining errors, providing column value formats, introspecting the live schema, executing queries, and scaffolding boilerplate code.

Enables LLMs to dereference and query OpenAPI/Swagger specifications, search endpoints and schemas, validate payloads, extract security schemes, and generate production-ready integration code in multiple languages.

Provides OpenAPI validation and analysis tools to assist developers in building Model Context Protocol servers. It generates developer context and specific agent prompts based on API specifications to streamline the creation of agentic workflows.

An MCP server that indexes the public-apis catalogue, allowing LLMs to search and filter over 1,400 public APIs by category, authentication type, and technical requirements. It facilitates precise API discovery for developers by providing tools to query specific features like HTTPS support and CORS compatibility.

Enables AI agents to create, run, and save API requests and collections as local Gud API files, which are git-committable and viewable in VS Code-compatible editors.

Enables AI coding assistants to discover, inspect, and run API requests in Bruno collections locally, keeping all data private.

Converts REST API code (like NestJS controllers or FastAPI endpoints) to Postman collections and environments, helping developers automatically sync their API endpoints with Postman.

An MCP server to communicate with the App Store Connect API for iOS Developers

Enables direct integration with YApi API documentation platform in MCP-compatible editors like Cursor, allowing users to query API details, list interfaces, and search endpoints by simply pasting YApi URLs.

Enables developers to search and access NicePay payment API documentation, including endpoint details, code samples, and SDK method information through natural language queries.

A Model Context Protocol server that creates tools from API configurations defined in YAML files, allowing easy integration of external APIs into an MCP ecosystem without coding.

Integrates XAPIHub API services with the Cursor IDE to enable user authentication, real-time data fetching, and connection diagnostics. It allows developers to interact with their XAPIHub organization and manage user details directly through natural language commands.