trigger_agent_deploy
Trigger the GitHub Actions deploy workflow for an owned agent repo.
This record as markdown: /tools/io-github-proagentstore-platform/trigger-agent-deploy.md
What trigger_agent_deploy does on ProAgentStore
AI agents invoke trigger_agent_deploy to trigger actions in ProAgentStore. 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 trigger_agent_deploy is rated High
This tool executes a deployment workflow, which runs external operations (GitHub Actions) whose effects depend on the agent repo and workflow configuration. Deployments are Execute-category because they trigger code execution and infrastructure changes. Severity is high because a malicious deployment could compromise services, modify production systems, or inject malicious code into agents.
From the tool's definition Trigger the GitHub Actions deploy workflow — initiates an automated deployment process that executes code/infrastructure changes in a production or staging environment.
Attacks that exploit this kind of access
The rule that runs trigger_agent_deploy safely
PolicyLayer is an MCP gateway: it sits between your AI agents and ProAgentStore, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For trigger_agent_deploy, this is the rule to start with:
trigger_agent_deploy 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 ProAgentStore, apply this rule, and every trigger_agent_deploy call is checked against it from then on.
Questions about trigger_agent_deploy
Trigger the GitHub Actions deploy workflow for an owned agent repo. It is categorised as a Execute tool in the ProAgentStore MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the ProAgentStore MCP server in PolicyLayer and add a rule for trigger_agent_deploy: 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 ProAgentStore. Nothing to install.
trigger_agent_deploy 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 trigger_agent_deploy 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 trigger_agent_deploy. 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.
trigger_agent_deploy is provided by the ProAgentStore MCP server (https://mcp.proagentstore.online/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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