"Reading and Writing Word Files" matching MCP servers:

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

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.

A Model Context Protocol (MCP) server for authenticated REST APIs. Drop it into any project, point it at your API, and let AI agents call endpoints — with auto-login, 2FA support, Swagger spec fetch, and fuzzy endpoint search — all without writing a single line of auth code.

Enables local analysis of OpenAPI 3 and Swagger 2 JSON/YAML spec files on disk, with no remote fetching of specs or credentials. It groups endpoints by tag, flags operations that appear to lack security, lists deprecated operations, and produces short markdown cheat sheets for agents.

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

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.

MCP server for API test case generation from Swagger/OpenAPI specs. Parses Swagger 2.0 and OpenAPI 3.x, generates test cases across 8 categories (positive, negative, boundary, auth, security, idempotency, pagination, business logic), and exports to Postman, TestRail, Allure, k6, pytest, Gherkin, and CSV. Supports internal corporate APIs with auth headers. Auto-saves export files to your working di

Generates comprehensive API test plans (positive, negative, and boundary/edge cases) from endpoint metadata using LLMs, and exports them as Excel files.

Discovers, inspects, and executes requests against OpenAPI or Swagger APIs directly from documentation URLs or specification files. It enables users to trace parameter usage across an API and perform authenticated HTTP requests through a structured toolset.

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

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

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.

Automatically converts Swagger 2.0 API specifications into MCP tools, enabling AI assistants to directly call REST APIs. Supports both local Swagger files and remote URLs with comprehensive parameter validation and error handling.

A configurable MCP server that adapts any HTTP API into an MCP toolset with generic HTTP tools (GET, POST, PUT, DELETE) and pluggable authentication. Includes API discovery scripts and supports dynamic tool generation from OpenAPI specs or wordlist scans.

A Model Context Protocol (MCP) server that enables AI assistants to download files from URLs to the local filesystem.

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

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.