"Tor Project" matching MCP servers:

Provides project-specific guides and instructions by selecting modules based on a project profile, enabling developers to get contextual instructions for their tech stack and architecture.

Enables converting a public release-note URL into ordered upgrade tasks with source excerpts, anchors, confidence, and uncertainty, without executing release text or project code.

Provides Large Language Models with real-time access to the latest documentation for Python libraries like Langchain, LlamaIndex, and OpenAI, enabling accurate and up-to-date code suggestions.

Provides AI assistants with intelligent access to project documentation and API references through smart search, contextual rules, and Docset integration. Enables AI to understand project-specific conventions, patterns, and official framework documentation without token limits.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Automatically analyzes project dependencies to discover and download the most relevant documentation, enabling developers to quickly set up comprehensive project context.

Provides AI coding assistants with access to ITK Dev Docker documentation and project analysis tools, enabling template listing, project detection, and comparison.

Enables personal project documentation management through local markdown files stored in nested directories. Supports organizing context by project and layer (backend/frontend/fullstack) with search functionality across all documentation files.

Automatically crawls documentation websites, converts them to organized markdown files, and generates condensed cheat sheets. Intelligently categorizes content into tools/APIs and provides local-first access to downloaded documentation.

Provides a minimal MCP server with safe tools for AI assistants to search project files, read files, search local documentation, and run pre-approved checks within a single project directory.

Provides AI assistants with structured access to Unity project metadata, build settings, and agent documentation directly from the filesystem. It enables querying project details and scene configurations without requiring the Unity Editor to be running.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

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

A project-agnostic MCP server that exposes Markdown documentation from a project's /docs folder as MCP resources for AI agents. It provides stable, up-to-date context to reduce hallucinations and ensure agents remain aligned with project-specific conventions and goals.

An MCP server that makes project documentation instantly accessible in Claude Code through @ mentions, allowing Claude to understand your codebase's conventions and architecture.

A Model Context Protocol (MCP) server for Specifai project integration and automation with any MCP-compatible AI tool. This server currently exposes tools to read all documents generated by the Specifai project.

Enables semantic search of project documentation using hybrid vector and full-text search with fast and deep query modes for immediate results or complex multi-round synthesis.

Provides project context for AI agents in VS Code by analyzing technologies, structure, AGENTS.md rules, current branch, and source code without allowing arbitrary commands.

Helps ground AI agents in reality by fact-checking responses against official documentation and reading project files to prevent hallucinations during coding sessions.

A Model Context Protocol (MCP) server for project document management with 32 comprehensive prompts covering the complete software development lifecycle.