As agentic workflows move from novelty to daily infrastructure, we are starting to face a massive, silent efficiency drain: probabilistic command execution failure (and it’s expensive).
When you let an LLM agent free-run in a terminal, its primary failure state isn’t just generating bad code—it’s the compounding retry loop that follows. An agent guesses a command, hits a missing dependency or invalid syntax, receives the stderr stream, and then burns 2,000+ tokens of context on a second inference call to “guess” a fix. This significantly compounds in the worst way if it’s your favorite heavyweight LLM model—the ones that consume massive tokens for real. If it fails three times in a row, you’ve just paid a steep premium in compute costs and latency for absolute zero progress.
We built Check to introduce a cold, deterministic circuit breaker into this loop.
Instead of letting the LLM raw-execute commands, our Model Context Protocol server (check-mcp) forces the agent to pass its intended bash string through a preflight validation layer first.
How it works:
- Generation: Cursor Agent generates a shell command.
- Routing: The agent automatically routes the command string to the
checktool before hitting your terminal environment. - Deterministic Evaluation: Check evaluates the environment and command deterministically, returning one of two signals:
RUNNABLEorINVALID(accompanied by an explicit reason). - Circuit Breaking: If the response is invalid, the loop terminates immediately before you waste inference tokens running broken code.
We’ve open-sourced the connector, and it fits straight into your local mcp.json file:
{
"mcpServers": {
"check-mcp": {
"command": "npx",
"args": ["@golproductions/check-mcp"],
"env": {
"GOL_CLIENT_ID": "YOUR_CLIENT_ID"
}
}
}
}