⚠️ Proof of Concept - This is a prototype implementation for exploring how discourse graphs can be integrated with AI assistants through the Model Context Protocol (MCP). It is intended for prototyping and experimental purposes only.
This MCP server exposes the Akamatsu lab's discourse graph on cellular biophysics (endocytosis, membrane tension, actin dynamics) to AI assistants like Claude. By implementing the Model Context Protocol, it allows AI assistants to explore, search, and traverse a structured knowledge graph of scientific research.
The server provides AI assistants with tools to:
- Search the knowledge graph using keywords and filters
- Retrieve detailed information about specific research nodes
- Traverse relationships between concepts, papers, and findings
- Query the ontology and relationship types
- View research images inline (automatically fetched and displayed)
- Analyze researcher contributions and statistics
All image content is served as native MCP image blocks (base64-encoded) for inline display in compatible MCP clients.
- Protocol: Model Context Protocol (MCP)
- Runtime: Node.js with TypeScript
- Data Format: JSON knowledge graph export
- Image Handling: Firebase URLs fetched and converted to base64 for inline display
search_nodes- Full-text search with type and property filtersget_node- Get complete node details with key imageget_linked_nodes- Graph traversal with typed relationshipsget_schema- Return ontology/node type definitionsget_researcher_contributions- Attribution and statisticsget_node_images- Get all images for a node (inline display)get_relationships- Query typed relationshipsget_relation_types- List relationship type definitions
npm install
npm run buildnpm startSet the DATA_PATH environment variable to specify the location of your discourse graph JSON file:
DATA_PATH=/path/to/your/graph.json npm startAdd to your MCP settings configuration:
{
"mcpServers": {
"discourse-graph": {
"command": "node",
"args": ["/path/to/discourse-graph-mcp/dist/index.js"],
"env": {
"DATA_PATH": "/path/to/your/graph.json"
}
}
}
}src/
├── index.ts # Main MCP server entry point
├── tools.ts # Tool handlers and schemas
├── search.ts # Keyword search implementation
├── dataLoader.ts # JSON data loading and indexing
├── imageParser.ts # Firebase image URL extraction
└── types.ts # TypeScript types and schemas
This is a proof-of-concept implementation for exploring the integration of discourse graphs with AI assistants. It demonstrates:
- How structured knowledge graphs can be exposed through MCP
- Inline image display capabilities for research content
- Graph traversal and relationship queries
- Full-text search over scientific knowledge
- Single static JSON data source (no live updates)
- Image fetching may be slow for large result sets
- Limited error handling and validation
- No authentication or access control
- Prototype-quality code not optimized for production
MIT
This is an experimental prototype. Contributions, suggestions, and feedback are welcome as we explore how discourse graphs can enhance AI-assisted research workflows.