Production Code Scaffolds
11 tested, standalone engineering scaffolds and architectural blueprints demonstrating core AI engineering patterns — from multi-server MCP routing and LangGraph supervisors to Deep Agents composite backends and Docker GPU serving.
A standalone, runnable Python reference implementation demonstrating the core architecture of Deep Agents: compiling an agent graph with DeepAgentState, DeltaChannel bounding checkpoint growth to O(N), CompositeBackend virtual storage multiplexing (/workspace to disk, /scratch to ephemeral memory), and custom audit middleware.
- •Python 3.10+
- •uv or pip
- •Anthropic API Key (ANTHROPIC_API_KEY)
uv pip install -e . && python src/main.pyA production-grade multi-server Model Context Protocol (MCP) client scaffold that concurrently orchestrates tools, resources, and prompt templates across multiple independent MCP servers over stdio and SSE transports.
- •Python 3.10+
- •pip or uv
- •Model Context Protocol SDK
pip install -e . && python src/main.pyClean Python reference scaffold demonstrating the core architectural patterns of ByteDance DeerFlow 2.0: LangGraph Pregel lead supervisor, declarative SKILL.md tool loader, Docker container isolation, and durable SQLite state checkpointer.
- •Python 3.10+
- •Docker Engine running
- •pip install -r requirements.txt
python -m pip install -r requirements.txt && python main.pyAutonomous software engineering agent runtime inspired by SWE-bench and OpenHands. Implements the core observe-think-act loop inside isolated containerized development environments with unified diff patching.
- •Python 3.10+
- •Docker Engine running
- •Git installed
python src/main.pyReference implementation of the supervisor multi-agent architecture in LangGraph. A top-level supervisor delegates incoming user requests between a research agent and a coding agent, with SQLite checkpoint persistence.
- •Python 3.10+
- •pip / uv
- •OpenAI or Gemini API Key
pip install -r requirements.txt && python main.py