This record as markdown: /tools/io-github-portel-dev-ncp/execute.md
What execute does on Ncp
AI agents invoke execute to trigger actions in Ncp. 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 execute is rated High
The tool explicitly executes commands via GitLab API, which can perform arbitrary operations (create projects, modify repositories, delete resources, trigger pipelines, etc.). While the actual destructiveness depends on the specific command arguments, the capacity to execute arbitrary GitLab API commands makes this an Execute-category risk.
From the tool's definition Tool name is 'execute' and description states 'Execute gitlab-api-v4 command', indicating it runs external commands against a GitLab API without restrictions on what operations are performed.
Attacks that exploit this kind of access
The rule that runs execute safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ncp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For execute, this is the rule to start with:
execute 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 Ncp, apply this rule, and every execute call is checked against it from then on.
Questions about execute
Execute gitlab-api-v4 command. It is categorised as a Execute tool in the Ncp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ncp MCP server in PolicyLayer and add a rule for execute: 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 Ncp. Nothing to install.
execute 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 execute 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 execute. 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.
execute is provided by the Ncp MCP server (@portel/ncp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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