workflow.run_evaluation · ContextForge MCP Gateway MCP

WHAT IT DOES

What workflow.run_evaluation does on ContextForge MCP Gateway

AI agents invoke workflow.run_evaluation to trigger actions in ContextForge MCP Gateway. 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 IT NEEDS A POLICY

Why workflow.run_evaluation needs a policy

This tool executes an evaluation suite, which involves running code or triggering operations that may have side effects on test data or external systems. Execution of arbitrary test suites could consume resources, modify test infrastructure state, or produce outputs depending on the supplied arguments.

From the tool's definition Tool name includes 'run_evaluation' and description states 'Execute evaluation suite on test data' — the word 'Execute' and the action of running an evaluation suite clearly indicate this tool triggers external operations whose effects depend on arguments…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

workflow.run_evaluation Rate-limited

workflow.run_evaluation 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "workflow.run_evaluation": {
      "limits": [
        {
          "counter": "workflow.run_evaluation_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches ContextForge MCP Gateway, so you can run agents against it safely.

FAQ

Questions about workflow.run_evaluation

What does the workflow.run_evaluation tool do? +

Execute evaluation suite on test data with parallel or sequential execution. It is categorised as a Execute tool in the ContextForge MCP Gateway MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on workflow.run_evaluation? +

Register the ContextForge MCP Gateway MCP server in PolicyLayer and add a rule for workflow.run_evaluation: 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 ContextForge MCP Gateway. Nothing to install.

What risk level is workflow.run_evaluation? +

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

Can I rate-limit workflow.run_evaluation? +

Yes. Add a rate_limit block to the workflow.run_evaluation 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 workflow.run_evaluation completely? +

Set action: deny in the PolicyLayer policy for workflow.run_evaluation. 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 workflow.run_evaluation? +

workflow.run_evaluation is provided by the ContextForge MCP Gateway MCP server (jrmatherly/mcp-context-forge). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.