AI agents call list_pipeline_runs to retrieve information from Azure DevOps MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read-only operation by listing/retrieving pipeline run data. It has no side effects, does not execute code, does not create or modify resources, and does not delete anything. The blast radius of misuse is minimal—an agent could retrieve unwanted information about pipeline history but cannot harm systems or data.
From the tool's definition Tool name 'list_pipeline_runs' and description 'List recent runs for a pipeline' indicate a query operation that retrieves pipeline execution history without modifying or triggering any state changes.
Documented attack patterns abuse exactly the kind of access list_pipeline_runs gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Azure DevOps MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_pipeline_runs:
{
"version": "1",
"default": "deny",
"tools": {
"list_pipeline_runs": {}
}
}list_pipeline_runs is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List recent runs for a pipeline. It is categorised as a Read tool in the Azure DevOps MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Azure DevOps MCP Server MCP server in PolicyLayer and add a rule for list_pipeline_runs: 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 MCP Server. Nothing to install.
list_pipeline_runs is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the list_pipeline_runs 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 list_pipeline_runs. 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.
list_pipeline_runs is provided by the Azure DevOps MCP Server MCP server (tiberriver256/mcp-server-azure-devops). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 42 Azure DevOps MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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42 Azure DevOps MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.