This record as markdown: /tools/io-github-dave-london-pare-test/install.md
What install does on Test
AI agents invoke install 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 install is rated High
The tool is named 'install' and the description begins with 'Runs', strongly suggesting it executes an installation process (e.g., npm install, pip install). Installing packages executes external commands and modifies system state, which classifies as Execute. The blast radius is high because arbitrary package installation can introduce malicious code or alter system dependencies.
From the tool's definition Tool name 'install' on a server that 'Runs' (description truncated) in a context with package management tools like 'add-package', 'ansible-galaxy', 'bazel'
Attacks that exploit this kind of access
The rule that runs install 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 install, this is the rule to start with:
install 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 install call is checked against it from then on.
Questions about install
Runs. 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 install: 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.
install 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 install 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 install. 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.
install 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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