F
licenseNot graded
qualityD
maintenanceAn MCP server that enables graph database interactions with Neo4j, allowing users to access and manipulate graph data through natural language commands.
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@littlebigbrain/mcp
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TDQS
A4/5.0
Scored across 8 tools
Disambiguation5/5
Each tool has a clearly distinct purpose: lbb_rdf handles RDF/OWL document import/update, lbb_commit writes/retracts graph facts and feedback, lbb_inspect reads graph context/metadata, lbb_query executes SPARQL, lbb_configure manages schema metadata, lbb_branch handles branch lifecycle, lbb_models provides model training data, and lbb_observe captures conversations. Despite some overlap in write operations, the descriptions explicitly delineate boundaries (e.g., lbb_rdf vs. lbb_commit), eliminating ambiguity.
Naming Consistency4/5
All tools share the 'lbb_' prefix and use lowercase single-word names, which is readable and predictable. However, the second part mixes verbs (inspect, query, commit, configure, observe) and nouns (rdf, branch, models), so it does not follow a strict verb_noun pattern. The consistency of the prefix and clarity of each name mitigate this minor inconsistency.
Tool Count5/5
With 8 tools, the server is well-scoped for its domain (a knowledge graph with RDF support, schema management, branching, and observation). This falls comfortably within the ideal 3-15 range, and each tool provides a distinct capability without redundancy.
Completeness4/5
The server covers core lifecycle operations: RDF import/update, graph fact writes/retraction, SPARQL querying, schema definition/evolution, branching/merging, model data access, and observation. However, there is no direct RDF deletion (only additive updates via lbb_rdf and retraction via lbb_commit), and no tool for exporting or bulk deleting graph data, leaving minor gaps that agents can work around.
Maintenance
ActivityActive
ResponsivenessNo issues