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kungfu
by kungfu-systems
Keep the same work moving across models and execution surfaces
C++
Updated Sep 4, 2026
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Summary
Routes live work across multiple model backends and execution surfaces so the same task can continue seamlessly between Codex, Claude, OpenCode, and local runners. Maintains task context and state rather than performing a one-time handoff, enabling continuous execution across heterogeneous agents and runtimes. Distinctive C++ runtime focused on low-latency transfer of work and preserving in-flight state during backend switching. A2A Protocol Pattern
Why It Matters
As agents delegate and failover between providers, preserving the task's context is essential for trustworthy outcomes and reliable evaluations. Kungfu makes it possible to observe the same work as it moves across models and execution surfaces, which helps surface agent failure modes and compare behavior deterministically. That continuity is a practical foundation for building agent track records and continuous A2A evaluation pipelines. Model Context Protocol (MCP)
When to Use
Teams that need resilient multi-backend agent execution and want to maintain task context while switching between model providers or local executors. Memory Agent Registry Pattern
How It's Used
- Route a long-running task between cloud LLMs and a local executor without losing context
- Build failover strategies that move work to another provider when an agent fails
- Compare how the same task executes across different model backends for A2A evaluation
- Maintain continuous task traces to support agent track records and post-hoc analysis
Works With
openaianthropichuggingface
Topics
agentagent-frameworkagent-memoryagent-orchestration
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Keywords
multi-agent orchestrationagent delegationagent reliabilitymulti-agent trust