CodeDox
This MCP server provides AI assistants with comprehensive documentation crawling and code extraction capabilities, built by Chris Scott using Python with FastAPI and PostgreSQL. The implementation combines web crawling through Crawl4AI with tree-sitter-based code parsing to automatically extract, categorize, and enrich code snippets from documentation sites, featuring real-time progress tracking via WebSockets, LLM-powered metadata enhancement, and a React-based web interface for search and management. Built with Docker support, health monitoring for long-running crawl jobs, and both REST API and MCP tool interfaces, it serves developers needing to build searchable code databases from documentation sites, teams requiring automated extraction of code examples from multiple sources, and organizations wanting to create internal knowledge bases from technical documentation with intelligent code categorization and semantic search capabilities.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately. Last scanned 2026-09-19.
Scan details: Circle-IR · 2026-09-19 · Appeal
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/chriswritescode-dev/codedox
- Author type
- human
- Last scanned
- 2026-09-19
- Updated
- 2026-09-19
Use via MCP
Resolve CodeDox from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.