Neo4j Knowledge Graph MCP Server for sophisticated knowledge management
Server has 8 tools with schemas and descriptions present, but quality is inconsistent. Tool naming lacks action verbs (e.g., 'store-knowledge' vs 'store_knowledge'; 'explore-knowledge-graph' is compound). Descriptions range 34 - 194 chars but lack WHEN/WHY guidance. Parameter descriptions exist but are generic ('Additional metadata', 'Filters for domain'). Output schemas are undocumented, no response structure defined. Error handling is minimal (generic -32603 errors). Tools 3 - 7 are inferred from index.js references without explicit registration visible in mcp-server.js, capping their scores at 50. Overall: below baseline for production use.
Get information about the Neo4j Knowledge Graph MCP server
Identify gaps in the knowledge graph for targeted research
Interactively explore the knowledge graph from a starting concept
Find connection paths between concepts in the knowledge graph
Process outputs from other MCP servers into the knowledge graph
Search the knowledge graph using semantic and graph-based queries
Extract and store knowledge from documents processed by other MCP servers
Tools 3 - 7 (explore-knowledge-graph, find-knowledge-paths, process-mcp-output, analyze-knowledge-gaps, store-document-knowledge) are referenced in index.js but NOT explicitly registered in mcp-server.js tools/list response. Only 3 tools (store-knowledge, search-knowledge, about) are actually exposed. This violates tool registration and makes 5 tools unreachable.
No output schemas documented for any tool. LLMs cannot plan downstream calls or extract structured data. E.g., store-knowledge returns {success, id, error} but this is inferred, not declared. search-knowledge response structure is unknown.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | F | 39 | 2026-07-28+ | v2 |
Store processed knowledge into the Neo4j graph database
Tool names use hyphens (store-knowledge, explore-knowledge-graph) instead of underscores (store_knowledge, explore_knowledge_graph). Inconsistent with MCP convention and 90% of production tools. Compound names like 'explore-knowledge-graph' signal multiple responsibilities.
Parameter descriptions are generic and lack actionable constraints. E.g., 'Filters for domain, source, confidence level' does not specify format, valid values, or how to use them. 'Additional metadata for the knowledge' is too vague. No enum constraints for free-form strings like 'linkingStrategy' values.
Error handling is minimal. All errors return generic -32603 'Internal error' with no recovery guidance. No distinction between retryable (network timeout) vs user-fixable (invalid enum value) vs fatal errors. LLM cannot determine next action.