MCP DocGraph
Provides integration with OpenAI's LLM API for generating entity patterns and answering queries.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP DocGraphingest all PDFs in my project folder"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP DocGraph
MCP server for building knowledge graphs from documents.
Ingest PDF/PPTX/DOCX files, transcribe to Markdown, bootstrap domain-specific entity patterns via LLM, and build a JSONL knowledge graph with RAG chunks — all configurable per project.
Quick Start
pipx install .Add to your MCP client config:
{
"mcpServers": {
"docgraph": {
"command": "python",
"args": ["-m", "mcp_docgraph.server"]
}
}
}Set LLM credentials:
export DOCGRAPH_LLM_API_KEY="your-key"
export DOCGRAPH_LLM_PROVIDER="anthropic" # or "openai"Related MCP server: MCP RAG
Tools
Tool | Description |
| Transcribe PDF/PPTX/DOCX → Markdown |
| LLM proposes entity patterns from docs |
| Build knowledge graph + RAG chunks |
| Query graph, get LLM-synthesized answer |
| Check graph integrity |
Workflow
Place documents in a folder
ingest_files→ transcribed Markdownbootstrap_config→ proposedconfig.yaml(review, edit if needed)build_graph→ JSONL nodes, edges, chunksvalidate_graph→ check integrityquery_graph→ ask questions
Design Spec
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Maintenance
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