High Risk →

run_benchmark

Execute benchmark tasks for AI evaluation

Runs compute-intensive benchmarks

Part of the Project Management AI Analysis MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.

pm-mcp-servers Execute Risk 3/5

AI agents invoke run_benchmark to trigger processes or run actions in Project Management AI Analysis. 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.

run_benchmark can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. Intercept 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.

project-management-ai-analysis.yaml
tools:
  run_benchmark:
    rules:
      - action: allow
        rate_limit:
          max: 10
          window: 60
        validate:
          required_args: true

See the full Project Management AI Analysis policy for all 16 tools.

Tool Name run_benchmark
Category Execute
Risk Level High

View all 16 tools →

Agents calling execute-class tools like run_benchmark have been implicated in these attack patterns. Read the full case and prevention policy for each:

Browse the full MCP Attack Database →

Other tools in the Execute risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.

run_benchmark is one of the high-risk operations in Project Management AI Analysis. For the full severity-focused view — only the high-risk tools with their recommended policies — see the breakdown for this server, or browse all high-risk tools across every MCP server.

What does the run_benchmark tool do? +

Execute benchmark tasks for AI evaluation. It is categorised as a Execute tool in the Project Management AI Analysis MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_benchmark? +

Add a rule in your Intercept YAML policy under the tools section for run_benchmark. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Project Management AI Analysis MCP server.

What risk level is run_benchmark? +

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

Can I rate-limit run_benchmark? +

Yes. Add a rate_limit block to the run_benchmark 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.

How do I block run_benchmark completely? +

Set action: deny in the Intercept policy for run_benchmark. 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 run_benchmark? +

run_benchmark is provided by the Project Management AI Analysis MCP server (pm-mcp-servers). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policies on Project Management AI Analysis

Open source. One binary. Zero dependencies.

npx -y @policylayer/intercept
github.com/policylayer/intercept →
// GET IN TOUCH

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