AGI MCP Server

Instructions

Implementation Reference

• src/memory-manager.js:506-595 (handler)

  The main handler implementation for search_memories_advanced. This method accepts a criteria object with textQuery, embedding, memoryTypes, importanceRange, dateRange, and limit parameters. It builds a complex SQL query using Drizzle ORM with full-text search (ts_rank), vector similarity search (embedding <=>), and multiple filters (memory type, importance, date range). Results are ordered by relevance based on the combination of text and vector search, with importance as a fallback.

  async searchMemoriesAdvanced(criteria) {
    try {
      const {
        textQuery,
        embedding,
        memoryTypes = [],
        importanceRange = [0, 1],
        dateRange = {},
        limit = 10
      } = criteria;
  
      let query = this.db
        .select({
          id: schema.memories.id,
          type: schema.memories.type,
          content: schema.memories.content,
          importance: schema.memories.importance,
          accessCount: schema.memories.accessCount,
          createdAt: schema.memories.createdAt,
          relevanceScore: schema.memories.relevanceScore,
          textRank: textQuery 
            ? sql`ts_rank(to_tsvector('english', ${schema.memories.content}), plainto_tsquery('english', ${textQuery}))`.as('text_rank')
            : sql`0`.as('text_rank'),
          similarityScore: embedding
            ? sql`1 - (${schema.memories.embedding} <=> ${`[${embedding.join(',')}]`}::vector)`.as('similarity_score')
            : sql`0`.as('similarity_score')
        })
        .from(schema.memories);
  
      // Build where conditions
      const conditions = [eq(schema.memories.status, 'active')];
  
      if (textQuery) {
        conditions.push(
          sql`to_tsvector('english', ${schema.memories.content}) @@ plainto_tsquery('english', ${textQuery})`
        );
      }
  
      if (memoryTypes.length > 0) {
        conditions.push(inArray(schema.memories.type, memoryTypes));
      }
  
      conditions.push(
        and(
          gte(schema.memories.importance, importanceRange[0]),
          lte(schema.memories.importance, importanceRange[1])
        )
      );
  
      if (dateRange.start) {
        conditions.push(gte(schema.memories.createdAt, dateRange.start));
      }
  
      if (dateRange.end) {
        conditions.push(lte(schema.memories.createdAt, dateRange.end));
      }
  
      query = query.where(and(...conditions));
  
      // Order by relevance
      if (textQuery && embedding) {
        query = query.orderBy(
          sql`ts_rank(to_tsvector('english', ${schema.memories.content}), plainto_tsquery('english', ${textQuery})) DESC`,
          sql`1 - (${schema.memories.embedding} <=> ${`[${embedding.join(',')}]`}::vector) DESC`,
          desc(schema.memories.importance)
        );
      } else if (textQuery) {
        query = query.orderBy(
          sql`ts_rank(to_tsvector('english', ${schema.memories.content}), plainto_tsquery('english', ${textQuery})) DESC`,
          desc(schema.memories.importance)
        );
      } else if (embedding) {
        query = query.orderBy(
          sql`1 - (${schema.memories.embedding} <=> ${`[${embedding.join(',')}]`}::vector) DESC`,
          desc(schema.memories.importance)
        );
      } else {
        query = query.orderBy(desc(schema.memories.importance));
      }
  
      const results = await query.limit(limit);
      return results;
    } catch (error) {
      const truncatedEmbedding = embedding && embedding.length > 10 
        ? `[${embedding.slice(0, 5).join(',')}...${embedding.slice(-5).join(',')}] (${embedding.length} values)`
        : embedding ? `[${embedding.join(',')}]` : 'none';
      console.error('Error in advanced search with embedding:', truncatedEmbedding, 'textQuery:', textQuery, error.message);
      throw error;
    }
  }

• mcp.js:678-680 (registration)

  Registration/case handler in CallToolRequestSchema that routes the search_memories_advanced tool call to the memoryManager.searchMemoriesAdvanced method with the criteria argument.

  case "search_memories_advanced":
    const advancedResults = await memoryManager.searchMemoriesAdvanced(args.criteria);
    return { content: [{ type: "text", text: JSON.stringify(advancedResults, null, 2) }] };

• mcp.js:473-522 (schema)

  Tool schema definition for search_memories_advanced in the ListToolsRequestSchema. Defines the input parameters including text_query, embedding, memory_types, importance_range, date_range, and limit, all nested under a 'criteria' object.

    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"]
    }
  }

• src/tools/memory-tools.js:447-496 (schema)

  Alternative schema definition for search_memories_advanced exported as part of the memoryTools array. Contains the same structure as the mcp.js schema with text_query, embedding, memory_types, importance_range, date_range, and limit parameters.

    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"]
    }
  }