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mcp_ado_pipelines_update_build_stage

Update a build stage (cancel, retry, or run)

Risk signalsCan trigger pipeline execution

Part of the Azure DevOps server.

mcp_ado_pipelines_update_build_stage can trigger actions in Azure DevOps, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke mcp_ado_pipelines_update_build_stage to trigger processes or run actions in Azure DevOps. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

mcp_ado_pipelines_update_build_stage can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "mcp_ado_pipelines_update_build_stage": {
      "limits": [
        {
          "counter": "mcp_ado_pipelines_update_build_stage_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Azure DevOps policy for all 84 tools.

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These attack patterns abuse exactly the kind of access mcp_ado_pipelines_update_build_stage gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so mcp_ado_pipelines_update_build_stage only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the mcp_ado_pipelines_update_build_stage tool do? +

Update a build stage (cancel, retry, or run). It is categorised as a Execute tool in the Azure DevOps MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on mcp_ado_pipelines_update_build_stage? +

Register the Azure DevOps MCP server in PolicyLayer and add a rule for mcp_ado_pipelines_update_build_stage: 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 Azure DevOps. Nothing to install.

What risk level is mcp_ado_pipelines_update_build_stage? +

mcp_ado_pipelines_update_build_stage is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit mcp_ado_pipelines_update_build_stage? +

Yes. Add a rate_limit block to the mcp_ado_pipelines_update_build_stage 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.

How do I block mcp_ado_pipelines_update_build_stage completely? +

Set action: deny in the PolicyLayer policy for mcp_ado_pipelines_update_build_stage. 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.

What MCP server provides mcp_ado_pipelines_update_build_stage? +

mcp_ado_pipelines_update_build_stage is provided by the Azure DevOps MCP server (@@azure-devops/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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