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find_similar_clusters

Identify clusters with similar characteristics to a specified cluster using similarity thresholds to support memory continuity in AI systems.

Instructions

Find clusters similar to a given cluster

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cluster_idYesUUID of the reference cluster
thresholdNoMinimum similarity threshold

Implementation Reference

  • Core handler function that executes the tool logic: queries the database for memory clusters similar to the given clusterId using vector embedding cosine similarity (pgvector <=> operator).
    async findSimilarClusters(clusterId, threshold = 0.7) { try { const embeddingVector = `[${Array(1536).fill(0).join(',')}]`; const results = await this.db.execute(sql` SELECT mc2.*, 1 - (mc1.centroid_embedding <=> mc2.centroid_embedding) as similarity FROM memory_clusters mc1 CROSS JOIN memory_clusters mc2 WHERE mc1.id = ${clusterId} AND mc2.id != ${clusterId} AND 1 - (mc1.centroid_embedding <=> mc2.centroid_embedding) >= ${threshold} ORDER BY similarity DESC `); return results.rows || []; } catch (error) { console.warn('Similar clusters query failed:', error.message); return []; }
  • mcp.js:387-404 (registration)
    Registration of the tool in the MCP server's tools array, defining name, description, and input schema.
    { name: "find_similar_clusters", description: "Find clusters similar to a given cluster", inputSchema: { type: "object", properties: { cluster_id: { type: "string", description: "UUID of the reference cluster" }, threshold: { type: "number", description: "Minimum similarity threshold", default: 0.7 } }, required: ["cluster_id"] }
  • mcp.js:649-654 (handler)
    MCP server request handler that dispatches to memoryManager.findSimilarClusters and returns JSON-formatted response.
    case "find_similar_clusters": const similarClusters = await memoryManager.findSimilarClusters( args.cluster_id, args.threshold || 0.7 ); return { content: [{ type: "text", text: JSON.stringify(similarClusters, null, 2) }] };

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