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Give AI agents persistent memory with relevant context retrieval and lower token usage.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "dolores" yet — see the docs or source repo.
I am building a customer support AI agent. Explain how to use dolores as an MCP tool with Postgres and pgvector for persistent conversation memory and relevant context retrieval, and provide integration steps and sample configuration.
A setup guide with architecture notes, sample config, memory write/retrieval flow, and integration details.
Help me design a dolores memory retrieval strategy that returns only the most relevant past context for the current query, reduces token usage, and preserves response continuity. Provide retrieval rules, threshold suggestions, and tuning ideas.
An actionable retrieval strategy covering relevance filtering, threshold settings, context assembly, and optimization suggestions.
Generate a local deployment plan for dolores using Postgres and pgvector, including environment setup, database initialization, MCP server startup, connection testing, and common troubleshooting steps.
A complete deployment guide with install commands, configuration items, verification steps, and troubleshooting advice.
Connect AI to Dolibarr to manage customers, proposals, contracts, and invoices.
Provide AI agents with searchable long-term memory and conflict-aware recall.
Use Doris MCP tools on AWS to run SQL and manage data operations.
Find official Korean senior-care support guidance across welfare, medical, and administrative services.
Provide AI tools with persistent personal memory across all conversations.
Connect Dust.tt agents with Claude Desktop for querying, listing, and configuration.