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Sell and retrieve priced graph answers through parameterized Cypher query templates.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "cypher-mcp" yet — see the docs or source repo.
Use the Cypher template named company_supply_chain with parameter company=Tesla. Return its first-tier suppliers, relationship types, and data sources, and show the required payment amount.
Returns pricing details and, after payment, provides structured graph query results for suppliers.
Call the named_person_connection template with personA=Satoshi Nakamoto and personB=Hal Finney. Output the shortest relationship path in the graph and list each node and edge step.
Returns the query price and, after payment, the detailed shortest-path result.
Design a parameterized Cypher query template for a knowledge graph operator to query funding history by company name. Include the template name, parameter definitions, return fields, and pricing suggestions.
Produces a query template design suitable for operators to offer paid graph answers externally.
Query and explore Neo4j graph databases with natural language and Cypher.
Ingest documents into Neo4j to build and query a knowledge graph.
Query code structure and cross-language relationships via MCP with auditable access logs.
Index codebases into Neo4j for analysis, dependency mapping, and impact assessment.
Enable AI agents to query knowledge graphs and delegate shell tasks efficiently.
Provide persistent graph memory, semantic search, and traversal for AI agents.