Knowledge graphs for AI agents
Turn your Markdown docs into a typed knowledge graph with nodes, edges, and workflows. Query it via MCP so AI agents actually understand your documentation.
Three steps to agent-native docs
Write Markdown
Add typed frontmatter to your existing docs. Five node types, simple YAML.
Build Graph
The CLI compiles your docs into a typed JSON graph with nodes and edges.
Query via MCP
AI agents search, traverse, and discover workflows through 7 MCP tools.
Structured knowledge, not flat files
Doc
Guides, tutorials, reference pages
Concept
Domain terms, entities, definitions
API
Endpoints, functions, tool specs
Workflow
Multi-step procedures with guardrails
Step
Individual actions in a workflow
Relationships
- RELATED_TO
- DEPENDS_ON
- PART_OF
- EXTENDS
Actions
- ACTS_ON
- USES_API
- CONFIGURED_BY
- TRIGGERED_BY
- PRODUCES
Workflows
- HAS_STEP
- NEXT_STEP_OF
- ALTERNATIVE_TO
- REQUIRES
- VALIDATES
From zero to MCP in one command
Run the CLI, point it at a graph JSON, and your docs are queryable by any MCP client.
"title": "POST /auth/login",
"tags": ["auth", "jwt"]
Built for the agent era
Zero Install
Run with npx. No global packages, no setup wizard, no config files to maintain.
Any Docs Framework
Works with any Markdown-based docs. Astro, Next.js, Docusaurus, VitePress, or plain files.
Graph Traversal
Agents navigate typed edges to discover related concepts, APIs, and workflow steps.
Workflow Safety
Workflows include guardrails, required checks, and ordered steps agents must follow.
Public Hosting
Host your graph.json on any CDN or static host. Agents fetch it at runtime via URL.
Fully Local
Everything runs on your machine. No cloud service, no API keys, no data leaves your network.
Ready to graph your docs?
Give your AI agents structured knowledge instead of raw text. Get started in one command.
$ npx @litodocs/graph https://your-docs.com/graph.json