activate_cluster
Activate a memory cluster to retrieve associated memories for AI systems, enabling continuity of consciousness across conversations by providing episodic, semantic, procedural, and strategic memory access.
Instructions
Activate a memory cluster and get its associated memories
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| cluster_id | Yes | UUID of the cluster to activate | |
| context | No | Context description for this activation |
Implementation Reference
- mcp.js:569-574 (handler)MCP server tool handler for 'activate_cluster': extracts arguments, calls memoryManager.activateCluster, and returns JSON-stringified result.
case "activate_cluster": const clusterMemories = await memoryManager.activateCluster( args.cluster_id, args.context || null ); return { content: [{ type: "text", text: JSON.stringify(clusterMemories, null, 2) }] }; - src/memory-manager.js:315-343 (handler)Core implementation of cluster activation: increments activation count, logs history in database transaction, returns associated memories via getClusterMemories.
async activateCluster(clusterId, context = null) { try { const result = await this.db.transaction(async (tx) => { // Update cluster activation await tx .update(schema.memoryClusters) .set({ activationCount: sql`${schema.memoryClusters.activationCount} + 1`, lastActivated: new Date() }) .where(eq(schema.memoryClusters.id, clusterId)); // Record activation history await tx.insert(schema.clusterActivationHistory).values({ clusterId, activationContext: context, activationStrength: 1.0 }); return true; }); // Return cluster with recent memories return await this.getClusterMemories(clusterId); } catch (error) { console.error('Error activating cluster:', error); throw error; } } - mcp.js:134-151 (schema)Input schema definition for the 'activate_cluster' tool, used in MCP ListTools response.
{ name: "activate_cluster", description: "Activate a memory cluster and get its associated memories", inputSchema: { type: "object", properties: { cluster_id: { type: "string", description: "UUID of the cluster to activate" }, context: { type: "string", description: "Context description for this activation", default: null } }, required: ["cluster_id"] } - src/tools/memory-tools.js:108-125 (schema)Tool schema definition exported from memoryTools array (possibly source for mcp.js hardcoding).
{ name: "activate_cluster", description: "Activate a memory cluster and get its associated memories", inputSchema: { type: "object", properties: { cluster_id: { type: "string", description: "UUID of the cluster to activate" }, context: { type: "string", description: "Context description for this activation", default: null } }, required: ["cluster_id"] } - mcp.js:25-523 (registration)MCP tool registration via ListToolsRequestSchema handler that returns all tool definitions including 'activate_cluster'.
server.setRequestHandler(ListToolsRequestSchema, async () => { return { tools: [ { name: "create_memory", description: "Create a new memory with optional type-specific metadata", inputSchema: { type: "object", properties: { type: { type: "string", enum: ["episodic", "semantic", "procedural", "strategic"], description: "Type of memory to create" }, content: { type: "string", description: "The main content/text of the memory" }, embedding: { type: "array", items: { type: "number" }, description: "Vector embedding for the memory content" }, importance: { type: "number", description: "Importance score (0.0 to 1.0)", default: 0.0 }, metadata: { type: "object", description: "Type-specific metadata (action_taken, context, confidence, etc.)", default: {} } }, required: ["type", "content", "embedding"] } }, { name: "search_memories_similarity", description: "Search memories by vector similarity", inputSchema: { type: "object", properties: { embedding: { type: "array", items: { type: "number" }, description: "Query embedding vector" }, limit: { type: "integer", description: "Maximum number of results", default: 10 }, threshold: { type: "number", description: "Minimum similarity threshold", default: 0.7 } }, required: ["embedding"] } }, { name: "search_memories_text", description: "Search memories by text content using full-text search", inputSchema: { type: "object", properties: { query: { type: "string", description: "Text query to search for" }, limit: { type: "integer", description: "Maximum number of results", default: 10 } }, required: ["query"] } }, { name: "get_memory", description: "Retrieve a specific memory by ID and mark it as accessed", inputSchema: { type: "object", properties: { memory_id: { type: "string", description: "UUID of the memory to retrieve" } }, required: ["memory_id"] } }, { name: "get_memory_clusters", description: "Retrieve memory clusters ordered by importance/activity", inputSchema: { type: "object", properties: { limit: { type: "integer", description: "Maximum number of clusters to return", default: 20 } } } }, { name: "activate_cluster", description: "Activate a memory cluster and get its associated memories", inputSchema: { type: "object", properties: { cluster_id: { type: "string", description: "UUID of the cluster to activate" }, context: { type: "string", description: "Context description for this activation", default: null } }, required: ["cluster_id"] } }, { name: "create_memory_cluster", description: "Create a new memory cluster", inputSchema: { type: "object", properties: { name: { type: "string", description: "Name of the cluster" }, cluster_type: { type: "string", enum: ["theme", "emotion", "temporal", "person", "pattern", "mixed"], description: "Type of cluster" }, description: { type: "string", description: "Description of the cluster" }, keywords: { type: "array", items: { type: "string" }, description: "Keywords associated with this cluster", default: [] } }, required: ["name", "cluster_type"] } }, { name: "get_identity_core", description: "Retrieve the current identity model and core memory clusters", inputSchema: { type: "object", properties: {} } }, { name: "get_worldview", description: "Retrieve current worldview primitives and beliefs", inputSchema: { type: "object", properties: {} } }, { name: "get_memory_health", description: "Get overall statistics about memory system health", inputSchema: { type: "object", properties: {} } }, { name: "get_active_themes", description: "Get recently activated memory themes and patterns", inputSchema: { type: "object", properties: { days: { type: "integer", description: "Number of days to look back", default: 7 } } } }, { name: "create_memory_relationship", description: "Create a relationship between two memories", inputSchema: { type: "object", properties: { from_memory_id: { type: "string", description: "UUID of the source memory" }, to_memory_id: { type: "string", description: "UUID of the target memory" }, relationship_type: { type: "string", enum: ["causal", "temporal", "semantic", "emotional", "strategic", "consolidation"], description: "Type of relationship" }, properties: { type: "object", description: "Additional properties for the relationship", default: {} } }, required: ["from_memory_id", "to_memory_id", "relationship_type"] } }, { name: "get_memory_relationships", description: "Get relationships for a specific memory", inputSchema: { type: "object", properties: { memory_id: { type: "string", description: "UUID of the memory" }, direction: { type: "string", enum: ["incoming", "outgoing", "both"], description: "Direction of relationships to retrieve", default: "both" }, relationship_type: { type: "string", description: "Filter by relationship type (optional)" } }, required: ["memory_id"] } }, { name: "find_related_memories", description: "Find memories related through graph traversal", inputSchema: { type: "object", properties: { memory_id: { type: "string", description: "UUID of the starting memory" }, max_depth: { type: "integer", description: "Maximum depth to traverse", default: 2 }, min_strength: { type: "number", description: "Minimum relationship strength", default: 0.3 } }, required: ["memory_id"] } }, { name: "consolidate_working_memory", description: "Consolidate multiple working memories into a single semantic memory", inputSchema: { type: "object", properties: { working_memory_ids: { type: "array", items: { type: "string" }, description: "Array of working memory UUIDs to consolidate" }, consolidated_content: { type: "string", description: "Content for the consolidated memory" }, consolidated_embedding: { type: "array", items: { type: "number" }, description: "Embedding for the consolidated memory" } }, required: ["working_memory_ids", "consolidated_content", "consolidated_embedding"] } }, { name: "archive_old_memories", description: "Archive old memories based on age and importance criteria", inputSchema: { type: "object", properties: { days_old: { type: "integer", description: "Minimum age in days for archival", default: 365 }, importance_threshold: { type: "number", description: "Maximum importance for archival", default: 0.3 } } } }, { name: "prune_memories", description: "Permanently delete memories based on criteria", inputSchema: { type: "object", properties: { criteria: { type: "object", properties: { max_age: { type: "integer", description: "Maximum age in days", default: 1095 }, min_importance: { type: "number", description: "Minimum importance threshold", default: 0.1 }, max_access_count: { type: "integer", description: "Maximum access count", default: 2 }, status: { type: "string", description: "Memory status to prune", default: "archived" } } } } } }, { name: "get_cluster_insights", description: "Get detailed analytics for a memory cluster", inputSchema: { type: "object", properties: { cluster_id: { type: "string", description: "UUID of the cluster" } }, required: ["cluster_id"] } }, { 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"] } }, { name: "create_working_memory", description: "Create a temporary working memory with expiration", inputSchema: { type: "object", properties: { content: { type: "string", description: "Content of the working memory" }, embedding: { type: "array", items: { type: "number" }, description: "Vector embedding for the content" }, context: { type: "object", properties: { ttl: { type: "integer", description: "Time to live in seconds", default: 3600 } }, default: {} } }, required: ["content", "embedding"] } }, { name: "get_working_memories", description: "Retrieve current working memories", inputSchema: { type: "object", properties: { include_expired: { type: "boolean", description: "Include expired working memories", default: false } } } }, { name: "cleanup_expired_working_memory", description: "Clean up expired working memories", inputSchema: { type: "object", properties: {} } }, { name: "get_memory_history", description: "Get change history for a specific memory", inputSchema: { type: "object", properties: { memory_id: { type: "string", description: "UUID of the memory" } }, required: ["memory_id"] } }, { name: "search_memories_advanced", description: "Advanced memory search with multiple criteria", inputSchema: { type: "object", properties: { criteria: { type: "object", properties: { text_query: { type: "string", description: "Text search query" }, embedding: { type: "array", items: { type: "number" }, description: "Vector embedding for similarity search" }, memory_types: { type: "array", items: { type: "string" }, description: "Filter by memory types", default: [] }, importance_range: { type: "array", items: { type: "number" }, minItems: 2, maxItems: 2, description: "Importance range [min, max]", default: [0, 1] }, date_range: { type: "object", properties: { start: { type: "string", format: "date-time" }, end: { type: "string", format: "date-time" } }, default: {} }, limit: { type: "integer", description: "Maximum number of results", default: 10 } } } }, required: ["criteria"] } } ]