I built Synapse AI: An open-source, DAG-based orchestrator for AI agents.

Hey Everyone,

For the past three months, I’ve been building an open-source orchestration platform for AI agents called Synapse AI.

I started this because I found existing frameworks (like LangChain or AutoGen) either too bloated or too unpredictable for production workflows. Letting agents freely "chat" with each other often leads to infinite loops, high API costs, and debugging nightmares. I wanted strict, predictable control.

The Architecture: Instead of conversational routing, Synapse AI relies on a Directed Acyclic Graph (DAG) architecture. You define the work, strictly control the hand-offs between agents, and get a completed task on the other side.

Under the Hood:

• Tool Agnostic: Build custom tools from scratch (Python/webhooks) or instantly plug in existing Model Context Protocol (MCP) servers.
• Local-First Emphasis: Full native support for Ollama so you can run routing and tasks entirely locally. (It also supports Gemini, Claude, and OpenAI for the heavy lifting).
• CLI Integration: Just shipped a community-requested feature to connect Claude Code, Gemini CLI, Codex CLI, and GitHub Copilot CLI directly to your agents.
• Frictionless Setup: A 1-step installation process across macOS, Windows, and Linux.

What I'm looking for: I am currently maintaining this solo and rolling it out for an early pilot phase. I would love for this community to take a look under the hood. Specifically:

1. Code Review: I’d love brutal feedback on the DAG implementation and overall architecture.
2. Contributors & Collaborators: If you find the project worthwhile, I am actively looking for people to team up with! Whether it's adding new LLM providers, fixing UI quirks, or improving the 1-step installer, PRs are incredibly welcome.

Repo: https://github.com/naveenraj-17/synapse-ai

If you bump into any bugs, please drop an issue so I can patch it. Would love to hear your thoughts!