"Creating files in Xcode development environment" matching MCP servers:

Enables developers to access kintone API specifications, field type documentation, and development best practices through natural language queries. Supports API request validation and provides comprehensive development guidance for kintone customizations.

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 AI assistants to interact with Magic-API development environment, supporting script syntax query, API management, debugging, and knowledge search for efficient development.

Connects external APIs like Open-Meteo and AgroMonitoring to your development environment through URI-like requests, allowing access to live data directly in MCP-compatible tools.

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.

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

MCP server that validates dashboardbase setup files and widget endpoint responses against the dashboardbase JSON contract, reporting errors and warnings before deployment.

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.

Provides a generic HTTP client tool allowing AI agents to make arbitrary HTTP requests from their environment, with support for environment-variable placeholders for secrets.

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.

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

Enables AI assistants to fetch and understand API endpoint definitions from Apifox projects in real-time. Supports retrieving complete API specifications including request methods, parameters, headers, and response schemas to improve development efficiency and code generation quality.

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.

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.

An MCP server for parsing and analyzing HAR files, enabling AI assistants to inspect network traffic with automatic redaction of sensitive authentication headers.

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.

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.

A local MCP server that lets clients discover, inspect, and execute Bruno OpenCollection API collections, while delegating request execution, authentication, scripting, assertions, and environment resolution to the Bruno CLI.