Grounded Docs is an open-source implementation of a Model Context Protocol server designed to expose documentation and structured information as tools that AI agents can query. The project allows language models and agent frameworks to retrieve and interact with documentation through standardized MCP interfaces. By acting as an intermediary layer between documentation sources and AI tools, the server enables models to access structured documentation in a consistent and machine-readable format. This makes it easier for AI systems to answer technical questions, generate code examples, or retrieve reference material without requiring developers to manually integrate documentation into prompts. The architecture follows the MCP specification, which allows AI assistants and agent frameworks to connect to external tools through standardized protocols.
Features
- Implementation of a Model Context Protocol server for documentation access
- Structured retrieval of documentation content for AI assistants
- Standardized API interface compatible with MCP-enabled tools
- Integration with agent frameworks that support tool-based reasoning
- Support for dynamic documentation querying during AI workflows
- Extensible architecture for connecting additional documentation sources