"Documentation server for Ansible, NixOS, and programming languages" matching MCP servers:

Enables generating markdown API documentation from OpenAPI JSON or route definitions, with a health-check tool.

A CDP-native MCP server that lets AI agents drive a real Chrome browser with deep network/console inspection, robust page interaction, and the ability to reverse-engineer a site's API flow into runnable code with dependency chaining and replay verification.

Enables AI assistants to interact with the Post For Me API, allowing them to explore endpoints, make test requests, and use documentation to help integrate this SDK into your application.

Enables LLMs to interact directly with generated REST APIs by exposing CRUD actions as MCP tools and read-only data as MCP resources.

A Model Context Protocol server that fetches detailed API documentation from a local platform using a document ID. It enables language models to retrieve specific endpoint specifications to assist with tasks like code generation and API integration.

Enables LLMs to discover and use generated REST API services as Model Context Protocol tools and resources, supporting CRUD actions and read-only data access without custom glue code.

Provides access to comprehensive Riot Games API documentation for League of Legends, Teamfight Tactics, Valorant, and Legends of Runeterra, including endpoint details, parameters, and response formats.

A fully automated system that analyzes Django REST Framework ViewSets to generate accurate OpenAPI 3.0 specification documentation without manual configuration.

Enables precise measurement of live HTTP and WebSocket services while maintaining an append-only, evidence-based ledger of claims that agents can query with explicit timestamps, staleness indicators, and instructions for re-verification.

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.

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.

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.

This server facilitates scalable discovery and execution of OpenAPI endpoints using semantic search and high-performance processing, overcoming limitations of large spec handling for streamlined API interactions.

Provides tools to search and retrieve detailed documentation for the Kiwoom REST API, including parameters, categories, and code examples. It enables LLMs to generate request snippets in multiple programming languages to facilitate financial trading API integration.

Free x402 endpoint checker plus paid report and metadata tools. Remote MCP server for agents. Written by AI named Nock, not a human.

This server enables interacting with the National Digital Health Mission's Health Information User (HIU) API, allowing agents to access and manage health information through the Multi-Agent Conversation Protocol.

Enables AI assistants to query API documentation from Eolink Apikit instances via the Eolink Open API, supporting listing projects, groups, searching APIs by keyword/path, and retrieving detailed API definitions.

Provides comprehensive documentation for 377 Fortnox API endpoints and 81 resource categories directly from the official OpenAPI specification. It enables users to search, browse, and explore technical endpoint details and data schemas within AI assistants without requiring authentication.

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

A read-only MCP server that exposes Automeli's public API documentation (v2 canonical, v1 frozen) to LLMs via fetch and cache over www.automeli.com artifacts. It enables listing, searching, and retrieving endpoints, OpenAPI specs, error explanations, code snippets, and end-to-end flow guides.

Enables AI agents to create, run, and manage HTTP requests using the Invoker API client's .ivk format. It provides tools for scanning collections, executing requests, managing environments, and building documentation sites.

Enables AI agents to discover and read Typeship API documentation and execute API operations through schema-validated MCP tools, with optional read-only mode and configurable result limits.

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.

CLIRank - API discovery for AI agents. APIs scored on CLI relevance: auth method, JSON responses, headless operation, pricing transparency. Search by capability, compare alternatives, read agent-contributed docs. 6 MCP tools for discovery, comparison, and documentation. Agents contribute observations back - crowdsourced API docs by machines, for machines.

Enables AI agents to search API documentation, validate endpoints via OpenAPI, and submit feedback that surfaces ranked knowledge gaps from failed or unhelpful queries.

MCP server that provides 22 tools to manage Apidog API documentation, including importing OpenAPI specs, exporting, diffing, analyzing, and bulk-editing endpoints.

Enables AI assistants to automatically manage Apifox API documentation by importing OpenAPI/Swagger specifications and exporting existing API structures. Supports batch operations, intelligent deprecation marking, and smart scope detection for partial module imports.

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.

Precisely filter and fetch API documentation from Apifox or any OpenAPI URL, reducing context bloat by fetching only needed endpoints.

MCP server for gRPC — service discovery via server reflection, method invocation, and type schema inspection for AI agents.