Results for agentDB

Memory module - AgentDB unification, HNSW indexing, vector search, hybrid SQLite+AgentDB backend (ADR-009)

Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1

JavaScript SDK for AgentDB database service

Command-line interface for AgentDB database service

Memory module - AgentDB unification, HNSW indexing, vector search, hybrid SQLite+AgentDB backend (ADR-009)

AgentDB with optimized ONNX embeddings - 100% local, GPU-accelerated AI agent memory

Memory module - AgentDB unification, HNSW indexing, vector search, hybrid SQLite+AgentDB backend (ADR-009)

AgentDB v3 - Intelligent agentic vector database with RVF native format, RuVector-powered graph DB, Cypher queries, ACID persistence. 150x faster than SQLite with self-learning GNN, 6 cognitive memory patterns, semantic routing, COW branching, and compreh

AgentDB tells you when your agent stops behaving like itself. Causal lineage, time travel and behavioral baselines for any AI agent.

Model Context Protocol server for agentic robotics with AgentDB integration

AI-first embedded database for LLM agents. Library-first architecture with framework-agnostic tool definitions and MCP adapter.

Standalone MCP server with agentic-flow and agentdb integration

Enterprise-grade AI agent orchestration with WASM-powered ReasoningBank memory and AgentDB vector database (always uses latest agentic-flow)

Self-learning vector memory for AI agents — single-file .rvf cognitive container with HNSW search, episodic Reflexion memory, causal graph + Cypher, 9 RL algorithms, Thompson Sampling bandit, 41 MCP tools, hybrid (BM25 + dense) retrieval, GNN attention. 1

Production-grade E2B sandbox orchestration with agentic-flow swarms and AgentDB caching for distributed AI agent execution

AI agent coordination for Jujutsu VCS with quantum-ready architecture, QuantumDAG consensus, AgentDB learning, and zero-dependency deployment

DSPy.ts 2.0 - Advanced declarative AI framework with multi-agent orchestration, self-learning capabilities, and state-of-the-art optimizers. Powered by AgentDB, ReasoningBank, and Swarm architecture.

Core TypeScript library for autonomous cryptocurrency accounting with transaction management, compliance automation, fraud detection, and AgentDB-powered vector search for intelligent financial analysis

High-performance WebAssembly theorem prover with dependent types, hash-consing (150x faster), Ed25519 proof signatures, MCP support for Claude Code, AgentDB vector search, episodic memory, and ReasoningBank learning. Formal verification with cryptographic

A cli for working with agent database.

A cli for working with agent database.

OpenCode Flow - Advanced AI swarm coordination and orchestration for OpenCode. Features 64+ agents, SPARC methodology, AgentDB memory, and 100+ MCP tools.

MCP server for AgentDB - Search and contribute to the AI agent knowledge base

MCP proxy server for remote HTTP endpoints supporting JSON and Server-Sent Events