Canopy: Terminal Dashboard for Managing Multiple Claude Code Agents

Canopy is an open source terminal UI tool built to manage multiple AI coding agents running in parallel across git worktrees. The developer created it to solve the problem of tracking multiple Claude Code instances working on different features or bug fixes simultaneously.
Problem and Solution
The developer, a software engineer who uses Claude Code heavily in daily workflow, was running 3-5 agents across git worktrees. The challenge was keeping track of which agent finished, which was stuck needing input, and which errored. They found themselves constantly switching terminal panes and losing context, with one instance waiting 10 minutes for approval while they were reading another agent's output.
Key Features
- Single dashboard view of all worktrees and agents running in them
- At-a-glance agent state visibility: running, idle, waiting for input, done, or errored
- Jump into any session directly from the dashboard
- Send input to agents without fully switching to their session
- Manage worktrees from inside the tool
Technical Details
- Works with Claude Code, Codex, Aider, or any interactive CLI tool
- Built in Go using Bubble Tea for the terminal UI
- Uses tmux under the hood so each agent gets a proper interactive terminal session
- Open source with MIT license
Source Information
The tool is available at https://github.com/isacssw/canopy. The developer posted about it on Reddit asking other users how they manage multiple Claude Code instances in their workflows.
📖 Read the full source: r/ClaudeAI
👀 See Also

Why Deterministic Workflows Outperform AI-Driven Orchestration for Agent Systems
A developer with a year of experience building agent systems shares that AI-driven orchestration failed reliably due to non-deterministic routing, compounding errors, cost explosion, and impossible debugging. Switching to deterministic workflows with code-based orchestration eliminated orchestration failures.

Manifest Adds Support for MiniMax Token Plans with M2.7 Model
Manifest, an open source routing layer for OpenClaw, now supports MiniMax token plans starting at $10/month. The new MiniMax M2.7 model is specifically trained for OpenClaw workflows and scores 62.7 on MM-ClawBench and 56.2 on SWE-Bench Pro.

Flash-MOE Benchmark on M5 Max: 12.99 tok/s with Qwen3.5-397B
A benchmark of the 397-billion-parameter Qwen3.5 model running locally on a MacBook Pro M5 Max with 128GB RAM achieved 12.99 tokens per second using 4-bit quantization and cache-io-split 4, three times faster than the original 48GB benchmark.

AIBrain adds persistent memory and self-improvement to Claude Code
AIBrain is a tool that gives Claude Code persistent memory between sessions with semantic search retrieval and self-improvement cycles. It includes 53 workflows, 44 skills, 9 MCP servers, and supports multi-agent mesh networking via Tailscale.