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Run Cypher queries and inspect Neo4j schemas for AI-driven graph exploration.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "Neo4j MCP Server" yet — see the docs or source repo.
Connect to my Neo4j database and run this Cypher query: MATCH (p:Person)-[r]->(m:Movie) RETURN p.name, type(r), m.title LIMIT 20, then format the results as a table.
A table showing people, relationship types, and movie titles returned by the query.
Retrieve the current Neo4j database schema, list node labels, relationship types, and key properties, and summarize the graph structure in English.
A clear schema overview with a concise explanation of the graph structure.
Using the database schema, convert this question into Cypher and execute it: 'Find the director-actor pairs with the most collaborations in the last three years.' Show the query first, then explain the results.
An executable Cypher query, the query results, and an explanation of the logic and findings.
Query Neo4j graph databases with natural language for fast relationship insights.
Query and retrieve data across GitHub, Neo4j, PostgreSQL, and Milvus.
Turn PostgreSQL data into a Neo4j graph for natural language querying.
Query structured data in natural language without needing SQL or API expertise.
Connect AI to MySQL for safe querying, SQL execution, and database management.
Give LLMs persistent knowledge graph memory with semantic retrieval and contextual recall.