Cascade-resolution routing for concurrent multi-agent writes, exposed as an MCP server.
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# cascade-mcp [](https://pypi.org/project/cascade-mcp/) [](https://pypi.org/project/cascade-mcp/) [](https://github.com/clemente-turrubiates/cascade-mcp/actions/workflows/ci.yml) [](LICENSE) A **write-conflict resolver** with a tunable staleness predicate and a self-detectable leak canary. Not an orchestration framework. It decides, per conflict, whether a write **wins**, **forks** to a human, or must be **recomputed**, plus an MCP server that exposes the router as tools and a stress-test suite that proves the behavior can't be cherry-picked. > **Anti-Hype Warning.** This is a precision tool for a narrow problem, not a > general-purpose orchestration framework. It is **not** for: > - Task/graph orchestration (use LangGraph, Temporal, Airflow) > - Agent conversation management (use AutoGen, CrewAI) > - Tool-use routing (that's the agent loop's job) > - Resource orchestration / load balancing > > It **is** for one thing: resolving concurrent writes to a shared store when > writes are expensive to redo, fields have genuine semantic tolerance, and > you want the conflict decision to be observable. If your problem reduces to > that, this is a clean, tested primitive for it. If it doesn't, use something > else — you'll be happier. > **Status: research harness + MCP demo, not production.** Good for > coordinating a local swarm of agents in a single session where losing state > on restart is acceptable. Persistence, auth, and multi-process serialization > come next — see [Current limitations & roadmap](#current-limitations--roadmap). ## Thesis **cascade is the cheap arm, not a correctness mechanism.** Correctness lives in the router. The router's correctness reduces to **tolerance-estimate integri…
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