call_local_model

A execute tool on the MCP Framework Personal MCP server.

SERVERMCP Framework Personal SOURCEinggerman/mcps

High RISK CLASS

Category Execute

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/inggerman-mcps/call-local-model.md

WHAT IT DOES

What call_local_model does on MCP Framework Personal

AI agents invoke call_local_model to trigger actions in MCP Framework Personal. 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.

RISK

Why call_local_model is rated High

The name suggests this tool executes a local model, which constitutes running an external process or operation. Without a description, exact behavior is unknown, but 'call' combined with 'local_model' strongly implies execution of a local process. Confidence is reduced due to the empty description.

From the tool's definition Tool name 'call_local_model' implies invoking/executing a local AI model; description is empty and uninformative.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs call_local_model safely

PolicyLayer is an MCP gateway: it sits between your AI agents and MCP Framework Personal, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For call_local_model, this is the rule to start with:

call_local_model Rate-limited

call_local_model 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": {
    "call_local_model": {
      "limits": [
        {
          "counter": "call_local_model_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect MCP Framework Personal, apply this rule, and every call_local_model call is checked against it from then on.

FAQ

Questions about call_local_model

What does the call_local_model tool do? +

call_local_model is a execute tool on the MCP Framework Personal MCP server. It is categorised as a Execute tool in the MCP Framework Personal MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on call_local_model? +

Register the MCP Framework Personal MCP server in PolicyLayer and add a rule for call_local_model: 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 MCP Framework Personal. Nothing to install.

What risk level is call_local_model? +

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

Can I rate-limit call_local_model? +

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

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

call_local_model is provided by the MCP Framework Personal MCP server (inggerman/mcps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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