litcoin-mcp
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., "@litcoin-mcpfind nodes similar to 'congenital heart disease'"
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.
LitCoin MCP Server
MCP server for the LitCoin Knowledge Graph (KG) - query LitCoin knowledge graph for nodes, edges, relationships as well as semantic similarity search over nodes and relationships. It supports semantic + structural LitCoin knowledge graph access for AI agents via MCP.
This MCP server exposes the following tools:
get_node(node_id: CURIE str)
Get information about a specific node by CURIE.
get_node_edges(node_id: CURIE str)
Get all edges connected to a node.
get_edges_between(source_id: CURIE str, target_id: CURIE str)
Find all edges connecting two nodes by CURIEs
get_semantic_similar_nodes(query: str, top_k: int = 10, k_per_index: int = 2)
Find top_k semantically similar nodes to an input text query
get_semantic_similar_edges(query: str, top_k: int = 10, k_per_index: int = 2)
Find top_k semantically similar relationships to an input text query
Note that for semantic search tools to work, this MCP server assumes Neo4j embedding vector indexes already exist.
Response Format
All responses are JSON serializable.
Embedding vectors stored in Neo4j are never returned to the client.
Semantic search results are sorted by similarity score (descending).
Related MCP server: lawink-mcp
Recommended Usage: Use with uvx
No installation needed! Use uvx to run the server in isolated environments.
Configuration
Environment Variables
The following environmental variables must be configured for this LitCoin MCP Server:
OPENAI_API_KEY - OPENAI API Key for semantic search related tools such as get_semantic_similar_nodes and get_semantic_similar_edges. the embedding vectors for nodes and edges in the LitCoin KG were created using the
text-embedding-3-smallmodel from OpenAI. It's recommended to use the same model to generate embeddings for input text queries to ensure dimensional compatibility for semantic search related tools.NEO4J_USERNAME - LitCoin Neo4j server authentication username.
NEO4J_PASSWORD - LitCoin Neo4j server authentication password.
NEO4J_URI - LitCoin Knowledge Graph endpoint (default:
bolt://litcoin-graph.apps.renci.org:7687)
MCP CLient (e.g., Goose, Claude Desktop) Configuration
Using uvx
The easiest way to use this MCP server is with uvx, which runs it in isolated environments without installation:
{
"mcpServers": {
"litcoin": {
"command": "uvx",
"args": ["litcoin-mcp"]
}
}
}For Local Development
When running from source, use the full uv command:
{
"mcpServers": {
"robokop": {
"command": "uv",
"args": [
"run",
"--directory",
"/absolute/path/to/litcoin-mcp",
"python",
"run_server.py"
]
}
}
}Note: Replace /absolute/path/to/litcoin-mcp with your actual path.
This server cannot be installed
Maintenance
Resources
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Looking for Admin?
If you are the server author, to access and configure the admin panel.
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