"Methods for Reading PDF Files" matching MCP servers:

Enables LLMs to make HTTP requests using structured cURL commands with support for multiple authentication methods, custom headers, and comprehensive request/response control.

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.

ozon-mcp is a knowledge-rich MCP server that turns the entire Ozon seller toolkit into 15 high-leverage tools. AI agents (Claude, Cursor, Cline, Continue, Goose, Zed, …) can search the API in Russian or English, drill into any of 466 methods with a fully-resolved JSON Schema, and execute calls with built-in safety guards. Subscription- aware, automatic pagination over all 4 cursor styles, retry/ba

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

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.

A TypeScript-based MCP server that enables AI assistants to execute HTTP requests with full control over methods, headers, and body content. It facilitates seamless interaction with web APIs and endpoints through a versatile tool that handles automatic JSON formatting and response truncation.

An MCP server that automatically discovers API endpoints from any codebase, generates and runs tests, and produces per-role QA audit reports in PDF and XLSX.

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 send HTTP requests to any endpoint with full control over methods, headers, query parameters, and request bodies.

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.

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

An MCP server that crawls and parses OpenAPI JSON or Swagger UI URLs to provide concise endpoint summaries. It enables LLMs to discover and interact with API interfaces by extracting methods, paths, and operation IDs from documentation sources.

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

MCP server for Akamai APIs. 198 tools covering Property Manager, Edge DNS, CPS, WAF, and reporting. Built with TypeScript, featuring modular architecture, comprehensive testing, and multi-account support. Make Akamai accessible to AI assistants.