Lists check/status results for a pull request. Returns structured data with check names, states, URLs, and summary counts (passed, failed, pending). When watch=true, polls internally until all checks complete (or timeout).
AI agents call pr-checks to retrieve information from Python without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries the status of pull request checks. It performs no create, modify, delete, or code execution operations. Even with polling, it only reads existing check results. This is a pure Read category tool with minimal risk — an agent using it could only gather information about PR status, not affect it.
From the tool's definition Tool 'Lists check/status results' and 'Returns structured data with check names, states, URLs, and summary counts' — these are query/retrieval operations with no modification of data.
Attacks that exploit this kind of access
Lists check/status results for a pull request. Returns structured data with check names, states, URLs, and summary counts (passed, failed, pending). When watch=true, polls internally until all checks complete (or timeout). It is categorised as a Read tool in the Python MCP Server, which means it retrieves data without modifying state.
Register the Python MCP server in PolicyLayer and add a rule for pr-checks: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Python. Nothing to install.
pr-checks is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the pr-checks rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for pr-checks. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
pr-checks is provided by the Python MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
pr-checks is one line of Python's registry record.
The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.
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