Medium Risk

update_draft

Update a content draft.

How to control update_draft ↓

AI agents use update_draft to create or update resources in LinkedIn Intelligence MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your LinkedIn Intelligence MCP Server environment.

Medium Risk

This tool updates LinkedIn content drafts, which are preparatory artifacts that can be edited, deleted, or discarded before publication. The modification is reversible—drafts can be edited multiple times or reverted. While the server enables content scheduling and automation, the update_draft tool itself performs only draft modification, not publishing or irreversible actions.

From the tool's definition The tool 'update_draft' modifies an existing content draft, which is explicitly a reversible data modification operation. The description states it 'Update[s] a content draft,' consistent with Write category operations that create or modify data.

Documented attack patterns abuse exactly the kind of access update_draft gives an agent:

PolicyLayer is an MCP gateway — it sits between your AI agents and LinkedIn Intelligence MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_draft:

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

update_draft stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

  1. Create a free account and register LinkedIn Intelligence MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
LIMIT THIS TOOL →

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Go deeper

What does the update_draft tool do? +

Update a content draft. It is categorised as a Write tool in the LinkedIn Intelligence MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_draft? +

Register the LinkedIn Intelligence MCP Server MCP server in PolicyLayer and add a rule for update_draft: 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 LinkedIn Intelligence MCP Server. Nothing to install.

What risk level is update_draft? +

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

Can I rate-limit update_draft? +

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

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

update_draft is provided by the LinkedIn Intelligence MCP Server MCP server (southleft/linkedin-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every LinkedIn Intelligence MCP Server tool call.

Deterministic rules across all 87 LinkedIn Intelligence MCP Server tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

87 LinkedIn Intelligence MCP Server tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

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