Skip to main content
Glama

search_memories_text

Search stored memories by text content to retrieve relevant information, enabling continuity of thought and context in AI systems using full-text queries.

Instructions

Search memories by text content using full-text search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results
queryYesText query to search for

Implementation Reference

  • Core handler function implementing full-text search on active memories using PostgreSQL tsvector/tsquery and ts_rank for relevance scoring.
    async searchMemoriesByText(query, limit = 10) { try { const results = await 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: sql`ts_rank(to_tsvector('english', ${schema.memories.content}), plainto_tsquery('english', ${query}))`.as('text_rank') }) .from(schema.memories) .where( and( eq(schema.memories.status, 'active'), sql`to_tsvector('english', ${schema.memories.content}) @@ plainto_tsquery('english', ${query})` ) ) .orderBy( sql`ts_rank(to_tsvector('english', ${schema.memories.content}), plainto_tsquery('english', ${query})) DESC`, desc(schema.memories.relevanceScore) ) .limit(limit); return results; } catch (error) { console.error('Error searching memories by text:', error); throw error; } }
  • mcp.js:554-559 (registration)
    MCP tool dispatch/registration in CallToolRequestHandler switch statement, calling the memoryManager handler and formatting response.
    case "search_memories_text": const textResults = await memoryManager.searchMemoriesByText( args.query, args.limit || 10 ); return { content: [{ type: "text", text: JSON.stringify(textResults, null, 2) }] };
  • mcp.js:88-104 (schema)
    Tool schema definition in ListToolsRequestHandler response, defining input parameters and validation.
    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"] }

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/QuixiAI/agi-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server