Tag: #agent-orchestration
11 packages • ⭐ 301 total stars
Declarative Agent Orchestration. Ship while you sleep.
AINL helps turn AI from "a smart conversation" into "a structured worker." It is designed for teams building AI workflows that need multiple steps, state and memory, tool use, repeatable execution, v
Agent ensembles to design, generate, and select the best code for every task.
Self-hosted orchestration layer for autonomous AI agent teams. Shared memory, heartbeat scheduling, vault-first secrets, and cross-model peer review — one command to deploy.
JSON Agents - A universal JSON-native standard for describing AI agents, their capabilities, tools, runtimes, and governance in a portable, framework-agnostic format. Based on RFC 8259, JSON Schema 2
A data-driven, cryptographically signed, registry-backed AI operating system, with capability-scoped execution and graph-executable workflows — living inside your projects, running through a recursive
Build and run local AI agents with multi-model support, modular skills, secure controls, and multi-channel access for personal automation tasks.
Enable any language model with permanent, searchable memory using a lightweight middleware for on-demand retrieval and continuous learning.
The open-source framework that makes AI agents proactive, self-learning, and autonomous. Multi-project tracking, full logging pipeline, message discipline, and memory review system.
The open framework for extensible & grounded AI agent orchestration.
A self-evolving AI Agent Team — agents that rewrite their own operating manual.