A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.
Provides LLMs with secure, read-only access to local documentation by scanning directories, extracting content from PDF, DOCX, Markdown, and text files, and performing keyword searches.
Enables engineers and AI assistants to search source-backed hardware design guidelines, retrieve detailed conditions and limitations, and trace citations to original sources, all through a read-only offline interface.
A thin, local, read-only MCP gateway that exposes governed context documents and producer manifests as logical resources, enabling AI clients to access them without arbitrary filesystem access.
An MCP server serving a curated corpus of thinking techniques for AI agents, with tools to classify intents, find and apply techniques, and verify their effectiveness.
This server provides an API to query Large Language Models using context from local files, supporting various models and file types for context-aware responses.
Fetches and caches public site pages from llms.txt and returns structured answers with source URLs, enabling verification of claims against live public content.
Automatically analyzes project dependencies to discover and download the most relevant documentation, enabling developers to quickly set up comprehensive project context.
Provides context about Toon Boom Harmony and its scripting API, enabling AI assistants to access Harmony's API documentation and help developers work with Harmony's scripting capabilities.
An MCP server that makes project documentation instantly accessible in Claude Code through @ mentions, allowing Claude to understand your codebase's conventions and architecture.
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.
An MCP server that enables AI assistants to manage Context Repo prompts, documents, and collections with semantic search and progressive disclosure navigation.
Enables semantic search across Cairo and Starknet documentation, providing AI assistants with precise code examples and documentation chunks via vector search.
Provides project-aware context for coding agents by selecting relevant AGENTS.md, docs, module paths, and decision records based on task, reducing redundant context loading via MCP stdio.