"Understanding File Reading in Programming" matching MCP servers:

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

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.

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.

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 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.

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

Enables searching and reading published Hoppscotch API documentation, inspecting endpoint details, and retrieving saved response examples through MCP tools.

MCP server providing diagnostic tools to analyze software architecture, security, REST API compliance, and dependencies for multiple programming languages. Enables AI agents to run scans and audits on codebases.

Enables reading and parsing Swagger/OpenAPI specifications to list API endpoints, get detailed endpoint info, search APIs, and generate TypeScript types for request/response.

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.

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.

Enables AI tools to create and manage API requests and collections in Thunder Client, with automated collection and folder creation.

A comprehensive HTTP/HTTPS tool server using curl, supporting various authentication methods, file uploads, downloads, and custom curl commands.

Enables validation of OpenAPI 2.0 and 3.0 specifications in JSON or YAML format using APIMatic's comprehensive API validation service through the Model Context Protocol.

A Model Context Protocol server that loads multiple OpenAPI specifications and exposes them to LLM-powered IDE integrations, enabling AI to understand and work with your APIs directly in development tools like Cursor.

Generates API documentation in Confluence from Swagger/OpenAPI specs or NestJS controller files, including automatic Postman collection generation.