pyATS MCP Server
Cisco pyATS and Genie already know how to talk to a network — parsing show commands, pushing configuration, learning feature state, running declarative tests. What they didn't have was a way for an AI agent to drive any of it directly. This server closes that gap: it wraps pyATS/Genie as a set of structured, guarded MCP tools that an agent like Claude can call against a real testbed, over the Model Context Protocol's current Streamable HTTP transport.
Point an agent at it and it can look up a device, run and parse a show command, apply configuration with a rollback point, learn and diff a feature's state before and after a change, fan a command out across a fleet — one thread pool or one process per device — run a declarative Blitz or Robot Framework test, or call a device's REST/RESTCONF API directly. Every risky path is guarded before it reaches a device, and every call lands in an in-memory audit log the agent can review mid-session.
At a glance
- Transport — Streamable HTTP (
mcp>=2.3.0), stateful or stateless, chosen with one environment variable. STDIO is gone. - 26 tools across discovery, show commands, configuration, Genie learn/diff, Genie Clean, declarative testing (Blitz, Robot Framework, AEtest), generic REST/RESTCONF, and Cisco XPresso.
- Two ways to fan out a command across many devices — a shared thread pool for everyday use, or one OS process per device (
pyats.async_.pcall) when you want real isolation at scale. - Guardrails, not honor systems — dangerous commands are blocked before they reach a device, Genie Clean can never run a stage that reboots or reimages one, and destructive actions require an exact confirmation phrase.
- Nothing hard-coded — every credential and device detail lives in
.env, pulled intotestbed.yamlat runtime via%ENV{}substitution.






