pytest
Runs pytest and returns structured test results (passed, failed, errors, skipped, failures).
This record as markdown: /tools/io-github-dave-london-pare-test/pytest.md
What pytest does on Test
AI agents invoke pytest to trigger actions in Test. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why pytest is rated High
This tool executes pytest, a test runner that runs arbitrary Python code on the host system. An AI agent could misuse this to trigger execution of malicious test code or cause unintended side effects. The blast radius is high because running tests can execute arbitrary Python code, access the filesystem, network, and system resources.
From the tool's definition 'Runs pytest' — directly executes a test framework process on the system
Attacks that exploit this kind of access
The rule that runs pytest safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Test, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For pytest, this is the rule to start with:
pytest stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Test, apply this rule, and every pytest call is checked against it from then on.
Questions about pytest
Runs pytest and returns structured test results (passed, failed, errors, skipped, failures). It is categorised as a Execute tool in the Test MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Test MCP server in PolicyLayer and add a rule for pytest: 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 Test. Nothing to install.
pytest is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the pytest 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 pytest. 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.
pytest is provided by the Test MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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