"Mock Service Worker" matching MCP servers:

Provides AI knowledge base query service for Cocos Creator 3.8.8 + exia-framework, enabling semantic search and API lookup for framework and engine classes.

A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.

Provides access to pdfdancer documentation through search and content retrieval tools, connecting to a Docusaurus search worker to query indexed docs and retrieve markdown content.

MCP server providing access to the Earth616 Defense Supply Chain and Documentation Ontology with tools for ontology lookup and testing.

MCP server wrapping Backstage — query service catalog, fetch TechDocs, and scaffold services via AI agents.

MCP server for the Freshservice ITSM API v2: tickets, changes, problems, assets, requesters, agents, knowledge base and service catalog.

A free, open-source service that transforms GitHub projects into MCP endpoints, enabling AI assistants to access and understand project documentation without any setup.

The Microsoft Learn Docs MCP Server is a cloud-hosted service that enables clients like GitHub Copilot and other AI agents to bring trusted and up-to-date information directly from Microsoft's official documentation. It is a remote MCP Server using streamable http, which is lightweight for clients t

An MCP-based service that enables AI models to seamlessly interact with Feishu (Lark) platform, supporting document reading and chatbot messaging capabilities.

Enables AI agents to retrieve free, source-linked decision methods and optional decision packs through MCP tools such as catalog, method, sample_pack, and pack_offer. It operates without model calls and disables payments by default.

Enables AI assistants and automation tools to search and manage GLPI IT service management data—tickets, changes, problems, assets, users, groups, entities, knowledge base articles and documents—through the Model Context Protocol, with read/write operations, generic API access, and safety modes such as read-only and dry-run.

Transforms static gemini-cli documentation into a queryable RAG service, enabling developers to ask questions about Gemini CLI in natural language and receive instant, accurate answers based on the official documentation directly within their workflow.

Provides AI agents with authoritative OEM automotive repair data including part numbers, torque specs, fluid capacities, and service procedures for vehicles 1982-2013 across 80+ makes, sourced from factory service manuals.

Enables MCP clients to parse charts and chart data out of PDF documents. The deployed service requires a bearer token on every request and rejects any tool argument that the tool's signature does not declare.

A read-only MCP server that enables AI apps to list, search, and read a set of publicly published guides hosted as Google Docs, without authentication. It exposes list_guides, search_guides, and get_guide tools from a Cloudflare Worker endpoint, caching guide text for about an hour.

Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.

Tracks and manages code changes from Git repositories, generates documentation automatically, and provides AI agents with intelligent access to service documentation through MCP server integration with feature mapping and search capabilities.

Enables users and AI assistants to search LinuxServer.io images, audit Compose and docker run configurations, research image requests, validate service specifications, generate Dockerfile/Compose/README scaffolds, and access guidance and best-practice checklists.

Enables AI agents to search and ask questions across versioned service documentation, retrieve documents and diffs, and find related docs with cited answers over Streamable HTTP, SSE, or stdio.

Unified SAP MCP server combining SAP documentation search, ABAP linting, and BTP service exploration into a single extensible ecosystem for AI assistants.