Agent Orchestra
Description
Hands-on experiments with multi-agent orchestration: Claude + LangGraph on the Python side, a thin TypeScript MCP server on top. Goal is intuition for which pattern (sequential / parallel / supervisor / hierarchical) fits which problem.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
agent-orchestra
🚧 **Work in progress** — personal sandbox for exploring multi-agent orchestration patterns.
This repo is my personal playground where I'm experimenting with recent agent frameworks and orchestration patterns that have appeared in late 2025 / early 2026:
- Claude Agent SDK (Anthropic)
- LangGraph — stateful multi-agent workflows
- Model Context Protocol (MCP) — standard tool interface across agents
- Computer Use / browser agents — follow-up experiments planned
The goal is not to ship a product. The goal is to *understand the trade-offs* between different orchestration patterns (sequential chain, parallel fan-out/fan-in, supervisor, hierarchical) and to get comfortable with the tooling.
Status
| Area | Status | Last touched |
|---|---|---|
| Basic agents (Python) | ✅ Done | 2026-03-28 |
| LangGraph supervisor workflow | ✅ Done | 2026-04-02 |
| Sequential chain experiment | ✅ Done | 2026-04-05 |
| Parallel fan-out experiment | ✅ Done | 2026-04-08 |
| MCP server (TypeScript) | 🟡 In progress | 2026-04-11 |
| Hierarchical orchestration | 🟡 In progress | 2026-04-16 |
| Computer Use integration | ⬜ Planned | — |
| Benchmarks / evals | ⬜ Planned | — |
See [`docs/ROADMAP.md`](docs/ROADMAP.md) for details.
Layout
agent-orchestra/
├── python/ # Agents + LangGraph workflows
│ ├── agents/ # Individual role agents
│ ├── graphs/ # LangGraph workflow definitions
│ ├── tools/ # Tools exposed to agents
│ └── main.py
├── mcp-server/ # TypeScript MCP server exposing agents as MCP tools
├── experiments/ # Standalone experiments, one per pattern
└── docs/ # Notes, architecture, roadmapQuick start
# Python side
uv sync
cp .env.example .env # add your ANTHROPRelated Skills
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