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AgentDB Advanced Features

Configure QUIC synchronization, hybrid search, and multi-database management for AgentDB vector stores.

Updated Mar 25, 2026
Search Tags:#embeddings#multi-agent#distributed systems#agentdb#vector search#quic sync#hybrid search
One-click install
npx skills add https://github.com/dmuhoro/EasyTutor --skill agentdb-advanced-features-dmuhoro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: AgentDB Advanced Features
Source: https://github.com/dmuhoro/EasyTutor/tree/main/archive/.claude/skills/agentdb-advanced
Command: npx skills add https://github.com/dmuhoro/EasyTutor --skill agentdb-advanced-features-dmuhoro

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires agentdb, agentic-flow.

What problem does it solve? Building distributed AI systems with vector search requires solving cross-node synchronization, metadata-filtered retrieval, and multi-database coordination, which are difficult to implement correctly from scratch. ## Core Features & Use Cases - QUIC Synchronization: Synchronize AgentDB instances across network peers with sub-millisecond latency, TLS 1.3 encryption, and automatic retry. - Hybrid Search: Combine vector similarity with metadata filters (price ranges, categories, dates) and weighted scoring for precise retrieval. - Multi-Database Management: Run separate databases per domain or shard data horizontally for horizontal scaling. - Use Case: Deploy a three-node AgentDB cluster where learned patterns replicate across all nodes in under 1ms, then query with hybrid filters like "ML papers from 2023+ with 50+ citations". ## Quick Start Set up an AgentDB adapter with QUIC sync enabled across two peers and run a hybrid vector search filtered by metadata.

Frequently Asked Questions about AgentDB Advanced Features

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I synchronize AgentDB across multiple nodes?▼

Enable QUIC synchronization by setting enableQUICSync to true, specifying a syncPort, and listing peer addresses in syncPeers. Patterns replicate across all peers in under 1ms with TLS 1.3 encryption and automatic retry.

How to combine vector search with metadata filters in AgentDB?▼

Use retrieveWithReasoning with a filters object supporting operators like $gte, $lte, $in, and $contains. You can also set hybridWeights to balance vector similarity against metadata match scores.

Which distance metric should I use for vector search?▼

Use cosine for text embeddings and semantic search, euclidean for spatial or image data where magnitude matters, and dot product for pre-normalized vectors needing fast computation. Cosine is the default for most general-purpose applications.

Why is AgentDB QUIC sync not working between nodes?▼

QUIC uses UDP, so verify your firewall allows UDP traffic on port 4433 and confirm peers are reachable via ping. Enable debug logging with DEBUG=agentdb:quic to inspect connection errors.

What does MMR do in vector search results?▼

MMR (Maximal Marginal Relevance) diversifies results to avoid redundant matches. Set useMMR to true and tune mmrLambda between 0 (maximum relevance) and 1 (maximum diversity), with 0.5 as the balanced default.

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