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AgentDB Advanced Features

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

Updated May 8, 2026
Search Tags:#embeddings#multi-agent#distributed systems#agentdb#vector search#quic sync#hybrid search
One-click install
npx skills add https://github.com/FrekiManagarm/d-chambaud --skill agentdb-advanced-features-frekimanagarm
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: AgentDB Advanced Features
Source: https://github.com/FrekiManagarm/d-chambaud/tree/main/.agents/skills/agentdb-advanced
Command: npx skills add https://github.com/FrekiManagarm/d-chambaud --skill agentdb-advanced-features-frekimanagarm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires agentic-flow, agentdb.

What problem does it solve? Building distributed AI systems with vector databases requires solving cross-node synchronization, redundant search results, and metadata filtering challenges that basic vector search setups cannot handle. ## Core Features & Use Cases - QUIC Synchronization: Synchronize AgentDB instances across network nodes with sub-millisecond latency, built-in 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 & MMR: Shard databases by domain, apply Maximal Marginal Relevance for diverse results, and synthesize context from multiple memories. - Use Case: Deploy a three-node AgentDB cluster where learned patterns from AI agents replicate across all nodes in under 1ms, then run hybrid searches filtering research papers by year, category, and citation count. ## Quick Start Set up AgentDB with QUIC synchronization enabled across two peer nodes and run a hybrid vector search with metadata filters.

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 and providing syncPeers addresses when creating the adapter. Patterns replicate across all peers in under 1ms using UDP port 4433 with TLS 1.3 encryption.

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 similarity for text embeddings and semantic search, euclidean distance for spatial or image data where magnitude matters, and dot product for pre-normalized vectors requiring fast computation.

Why is QUIC sync not working between AgentDB nodes?▼

QUIC sync commonly fails when the firewall blocks UDP port 4433 or peers are unreachable. Allow the port with ufw, verify connectivity with ping, and enable debug logging with DEBUG=agentdb:quic.

How do I get diverse search results instead of redundant ones?▼

Enable Maximal Marginal Relevance by setting useMMR to true in retrieveWithReasoning. Adjust mmrLambda between 0 (maximum relevance) and 1 (maximum diversity), with 0.5 as the balanced default.

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