Kocoro-lab/Shannon

Health v2 · maintenance only

Adoption not part of the score

2216 stars · 352 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Shannon is a production-oriented multi-agent orchestration framework written in Go (with Rust components) that coordinates AI agent swarms with execution strategies, token budget controls, and human approval workflows. It ships with Temporal-based durable workflows, WASI sandboxing, and built-in observability via event streaming, Prometheus metrics, and OpenTelemetry tracing.

Use cases

• orchestrate multiple AI agents on complex tasks
• run LLM agents in production with cost controls
• debug agent executions step by step
• enforce token budgets and model fallbacks for agent tasks
• sandbox agent code execution securely
• add human approval gates to automated agent workflows
• avoid vendor lock-in across OpenAI, Anthropic, and local models
• monitor and trace agent systems with Prometheus and OpenTelemetry

When to choose

• you need production-grade multi-agent orchestration with reliability guarantees
• cost control via hard token budgets is a requirement
• you want durable, replayable agent workflows with time-travel debugging
• security matters: sandboxed execution, OPA policies, multi-tenant isolation
• you want provider-agnostic LLM support including local models via Ollama

When to avoid

• you only need a simple single-agent chatbot or prompt pipeline
• you want a lightweight Python-native agent library rather than a Docker-based service stack
• your team cannot operate infrastructure like Temporal, Docker Compose, and observability tooling
• you need a minimal embedded SDK inside an existing app rather than a standalone orchestration platform

Facets

framework · maturity active

agent-framework workflow-automation monitoring tracing llm-inference security api-framework large-language-models artificial-intelligence developer-tools self-hosted go rust windows self-hosted cross-platform multi-agent-orchestration temporal-workflows token-budgeting human-in-the-loop wasi-sandboxing time-travel-debugging llm-provider-agnostic observability ai-agents automation docker linux macos

Member repositories

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markdown · JSON · MCP: product_card(name="Kocoro-lab/Shannon")