Medium Risk

manage_agent_workflows

Add, remove, or replace the workflows assigned to an agent without passing the full agent config. - operation 'add': append workflowIds to the existing list (no-op for IDs already present) - operation 'remove': remove specific workflowIds from the list - operation 'set': replace the entire list w...

Risk signalsBulk/mass operation — affects multiple targets

Part of the Agentled server.

manage_agent_workflows can modify Agentled data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

SECURE AGENTLED →

Free to start. No card required.

AI agents use manage_agent_workflows to create or modify resources in Agentled. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call manage_agent_workflows repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Agentled.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "manage_agent_workflows": {
      "limits": [
        {
          "counter": "manage_agent_workflows_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Agentled policy for all 119 tools.

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

ENFORCE ON MY AGENTLED →

View all 119 tools →

These attack patterns abuse exactly the kind of access manage_agent_workflows 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 manage_agent_workflows only ever does what you allow.

SECURE AGENTLED →

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

What does the manage_agent_workflows tool do? +

Add, remove, or replace the workflows assigned to an agent without passing the full agent config. - operation 'add': append workflowIds to the existing list (no-op for IDs already present) - operation 'remove': remove specific workflowIds from the list - operation 'set': replace the entire list with the given workflowIds Use 'set' with an empty array to clear all assigned workflows.. It is categorised as a Write tool in the Agentled MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on manage_agent_workflows? +

Register the Agentled MCP server in PolicyLayer and add a rule for manage_agent_workflows: 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 Agentled. Nothing to install.

What risk level is manage_agent_workflows? +

manage_agent_workflows is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit manage_agent_workflows? +

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

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

manage_agent_workflows is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agentled tool call.

Deterministic rules across all 119 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.