AgentDB Advanced Features

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

Updated Jul 16, 2026
One-click install
npx skills add https://github.com/optimaxin/Tredev_Gems --skill agentdb-advanced-features-optimaxin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: AgentDB Advanced Features
Source: https://github.com/optimaxin/Tredev_Gems/tree/main/.claude/skills/agentdb-advanced
Command: npx skills add https://github.com/optimaxin/Tredev_Gems --skill agentdb-advanced-features-optimaxin

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 latency, redundant search results, and the complexity of combining semantic similarity with metadata filtering across multiple databases. ## Core Features & Use Cases - QUIC Synchronization: Synchronize AgentDB instances across network nodes with sub-millisecond latency, multiplexed streams, and TLS 1.3 encryption. - Hybrid Search: Combine vector similarity (cosine, euclidean, dot product) with metadata filters and weighted scoring for precise retrieval. - Multi-Database Management & MMR: Shard databases by domain, pool connections, and use Maximal Marginal Relevance to diversify search results. - Use Case: Deploy a three-node AgentDB cluster where learned patterns sync across peers in under 1ms, then run hybrid searches that filter research papers by year, category, and citation count while ranking by semantic similarity. ## Quick Start Set up an AgentDB adapter with QUIC synchronization enabled across three peer nodes 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 and providing syncPort and syncPeers in the adapter configuration. Patterns replicate across all peers with sub-millisecond latency using multiplexed UDP streams with TLS 1.3 encryption.

How to combine vector search with metadata filters in AgentDB?

Pass a filters object alongside the query embedding in retrieveWithReasoning, using 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 needing fast computation. Custom weighted distance functions are also supported.

Why is QUIC sync not working between AgentDB nodes?

QUIC sync commonly fails when firewalls block UDP traffic on the sync port. Allow UDP port 4433, verify peers are reachable via ping, and enable debug logging with DEBUG=agentdb:quic to diagnose connection issues.

How do I avoid redundant results in vector search?

Enable Maximal Marginal Relevance by setting useMMR to true and tuning mmrLambda between 0 and 1. A value of 0.5 balances relevance and diversity, while higher values prioritize diverse, non-redundant results.

Can AgentDB shard data across multiple databases?

Yes, create separate adapter instances with distinct dbPath values per domain and route queries using a shard-key function. This supports horizontal scaling by distributing patterns across domain-specific database files.