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:

• Vector & fulltext indexes (for search)

• Node/relationship schemas with property types

• Warnings for large properties (helps choose efficient return_properties)

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 sample_size value if requested by the user, or tuning performance.

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):

• Embedding property used by the vector index → automatically excluded (vector_search only)

• Large lists (≥128 items) → replaced with placeholders

• Large strings (≥10K chars) → truncated with suffix

• Total response limited to 8000 tokens (results dropped if needed)

Property Selection:

• Default (no return_properties): Returns ALL properties (sanitized)

• With return_properties: Returns ONLY specified properties

• Example: return_properties="pageNumber,id" → returns only these two

• Check get_neo4j_schema_and_indexes for property warnings to avoid large fields

Performance Optimization: Internally fetches max(top_k × 2, 100) results to avoid local maximum problems in kANN algorithms.

Performs fulltext search on a Neo4j fulltext index using Lucene query syntax.

Lucene Syntax Supported:

• Boolean: "legal AND compliance", "privacy OR security"

• Wildcards: "compli*", "te?t"

• Fuzzy: "complience~"

• Phrases: ""exact phrase""

Automatic Sanitization (always applied):

• Large lists (≥128 items) → replaced with placeholders

• Large strings (≥10K chars) → truncated with suffix

• Total response limited to 8000 tokens (results dropped if needed)

Property Selection:

• Default (no return_properties): Returns ALL properties (sanitized)

• With return_properties: Returns ONLY specified properties

• Example: return_properties="pageNumber,id" → returns only these two

• Check get_neo4j_schema_and_indexes for property warnings to avoid large fields

Returns node/relationship IDs, labels/types, properties (sanitized), and relevance scores.

Execute a read Cypher query on the Neo4j database.

Execute a Cypher query that uses vector and/or fulltext search indexes.

This powerful tool allows you to:

1. Use vector search ($vector_embedding) and/or fulltext search ($fulltext_text) in Cypher

2. Post-filter large result sets (fetch 100-1000, filter with WHERE)

3. Combine search with graph traversal

4. Aggregate over search results

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:

• $vector_embedding: Replaced with embedding vector

• $fulltext_text: Replaced with text string for fulltext