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run_research_campaign

Run a multi-persona research campaign to gather diverse perspectives

Part of the Signal Relay server.

run_research_campaign can trigger actions in Signal Relay, 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 run_research_campaign to trigger processes or run actions in Signal Relay. 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_research_campaign 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": {
    "run_research_campaign": {
      "limits": [
        {
          "counter": "run_research_campaign_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Signal Relay policy for all 30 tools.

Get this rule live on your own Signal Relay server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access run_research_campaign 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 run_research_campaign 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 run_research_campaign tool do? +

Run a multi-persona research campaign to gather diverse perspectives. It is categorised as a Execute tool in the Signal Relay 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_research_campaign? +

Register the Signal Relay MCP server in PolicyLayer and add a rule for run_research_campaign: 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 Signal Relay. Nothing to install.

What risk level is run_research_campaign? +

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

Can I rate-limit run_research_campaign? +

Yes. Add a rate_limit block to the run_research_campaign 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 run_research_campaign completely? +

Set action: deny in the PolicyLayer policy for run_research_campaign. 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_research_campaign? +

run_research_campaign is provided by the Signal Relay MCP server (SocioLogicAI/signal-relay). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Signal Relay tool call.

Deterministic rules across all 30 Signal Relay tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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