Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| NEO4J_URI | Yes | Neo4j connection URI | bolt://localhost:7687 |
| AZURE_API_KEY | No | API Key for Azure embedding provider | |
| AZURE_API_BASE | No | API Base URL for Azure embedding provider | |
| COHERE_API_KEY | No | API Key for Cohere embedding provider | |
| NEO4J_DATABASE | No | Database name | neo4j |
| NEO4J_PASSWORD | Yes | Neo4j password | password |
| NEO4J_USERNAME | Yes | Neo4j username | neo4j |
| OPENAI_API_KEY | No | API Key for OpenAI embedding provider | |
| EMBEDDING_MODEL | No | Embedding model format (e.g. text-embedding-ada-002, azure/deployment-name, bedrock/amazon.titan-embed-text-v1, cohere/embed-english-v3.0, ollama/nomic-embed-text) | text-embedding-3-small |
| AWS_ACCESS_KEY_ID | No | AWS Access Key ID for Bedrock embedding provider | |
| AWS_SECRET_ACCESS_KEY | No | AWS Secret Access Key for Bedrock embedding provider |
Capabilities
Features and capabilities supported by this server
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_neo4j_schema_and_indexes | Returns Neo4j graph schema with search indexes and property size warnings. IMPORTANT: Call this tool BEFORE using any search tools (vector_search, fulltext_search, search_cypher_query). This tool provides:
Property size warnings help you avoid token limits when using search tools. For example, if a property has warning "avg ~100-200KB", avoid returning it unless necessary. You should only provide a |
| vector_search | Performs vector similarity search on a Neo4j vector index. This tool embeds your text query using OpenAI and searches the specified vector index. Returns node IDs, labels, node properties (automatically sanitized), and similarity scores. Automatic Sanitization (always applied):
Property Selection:
Performance Optimization: Internally fetches max(top_k × 2, 100) results to avoid local maximum problems in kANN algorithms. |
| fulltext_search | Performs fulltext search on a Neo4j fulltext index using Lucene query syntax. Lucene Syntax Supported:
Automatic Sanitization (always applied):
Property Selection:
Returns node/relationship IDs, labels/types, properties (sanitized), and relevance scores. |
| read_neo4j_cypher | Execute a read Cypher query on the Neo4j database. |
| search_cypher_query | Execute a Cypher query that uses vector and/or fulltext search indexes. This powerful tool allows you to:
Example: search_cypher_query(
cypher_query='''
CALL db.index.vector.queryNodes('chunk_embedding_vector', 500, $vector_embedding)
YIELD node, score
WHERE score > 0.75
MATCH (node)-[:BELONGS_TO]->(d:Document)
WHERE d.year >= 2020
RETURN node.chunkId, d.title, score
ORDER BY score DESC
LIMIT 20
''',
vector_query="student requirements"
) Placeholders:
|
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |