Execute a deployed DataGen workflow with custom inputs. Use this to run pre-built workflows (like data processing pipelines, web scrapers, or automation scripts) that have been deployed as API endpoints. This starts an asynchronous execution - you'll get a run ID that you can monitor...
Part of the DataGen MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use submitDeploymentRun to create or modify resources in DataGen. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call submitDeploymentRun repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach DataGen.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
submitDeploymentRun:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full DataGen policy for all 20 tools.
Agents calling write-class tools like submitDeploymentRun have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
Execute a deployed DataGen workflow with custom inputs. Use this to run pre-built workflows (like data processing pipelines, web scrapers, or automation scripts) that have been deployed as API endpoints. This starts an asynchronous execution - you'll get a run ID that you can monitor with 'checkRunStatus'. **Typical workflow:** 1. Use `validateDeploymentConnection` tool to validate the deployment and get the missing MCP or Secrets. 2. Use this tool to start a deployment 3. Get a run_uuid in response 4. Use `checkRunStatus` to monitor progress 5. Retrieve results when complete **Use cases:** Run data pipelines, execute scrapers, trigger automations, process files. **Error handling:** If found any missing MCP or Secrets, try to run validate deployment connection tool to validate the deployment and get the missing MCP or Secrets.. It is categorised as a Write tool in the DataGen MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for submitDeploymentRun. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the DataGen MCP server.
submitDeploymentRun is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the submitDeploymentRun rule in your Intercept 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 Intercept policy for submitDeploymentRun. 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.
submitDeploymentRun is provided by the DataGen MCP server (kuoyusheng/datagendev). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept