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stevepridemore

Graph-Memory

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    Gives your AI persistent memory across conversations. Stores facts automatically, finds them by meaning using hybrid search with query expansion, and organizes everything into topics without manual tagging.
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TDQS

A4.5/5.0

Scored across 23 tools

Disambiguation5/5

Every tool has a clearly distinct purpose: audit, boost, build context, find communities, contradictions, run cypher, decay, delete, browse entities, export, ingest, merge, suggest merges, prune, query, read transcript, re-embed, relate, search, stats, unmerge, validate, weaken. No two tools overlap in function.

Naming Consistency5/5

All tool names follow the consistent pattern 'graph_' + lowercase_snake_case action verb or noun (e.g., graph_audit, graph_boost, graph_build_context). No mixing of camelCase or other conventions, making prediction easy.

Tool Count4/5

With 23 tools, the server covers the full lifecycle of a knowledge graph (CRUD, maintenance, quality, analysis). While on the high side, each tool is justified; it could be trimmed slightly but is not excessive.

Completeness5/5

The tool set provides comprehensive coverage: entity creation via graph_relate, reading via multiple tools, updating via boost/weaken/merge/reembed, deletion via delete/prune, plus management (export, ingest, decay, validate, contradictions, merge suggestions, unmerge, audit, build context, communities, stats, read transcript, cypher). No obvious gaps.

Maintenance

ActivityInactive
ResponsivenessNo issues