report_problem

SERVERLocal SOURCElocal-mcp

Medium RISK CLASS

Category Write

Parameters 80 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/com-local-mcp-local-mcp/report-problem.md

WHAT IT DOES

What report_problem does on Local

AI agents use report_problem to create or update resources in Local, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Local environment.

Parameter	Type	Required	Description
`confirm`	boolean	—	Must be true to submit the report. Without it, shows a preview.
`symptom`	string	—	Required for type=problem: what is broken, in your own words.
`expected`	string	—	What you or the user expected to happen.
`description`	string	—	Required for type=feature or integration: what the user wants.
`report_type`	string	—	'problem' (default) \| 'feature' \| 'integration'
`user_request`	string	—	What the user originally asked the AI to do.
`error_message`	string	—	For type=problem: verbatim error string from the failed tool.
`tool_attempted`	string	—	For type=problem: name of the LMCP tool that failed.

Parameters from the server's own tool schema.

RISK

Why report_problem is rated Medium

This tool writes/creates data (problem reports, feature requests) to an external service. While it collects only non-personal metadata (version, OS, permission status), it still commits data irreversibly. The requirement to show a preview and obtain user approval before setting confirm=true indicates awareness of the write operation's sensitivity.

From the tool's definition Tool description states it "Report[s] a problem, feature request, or integration request" which creates or submits data to the LMCP team. The tool modifies state by recording user reports in an external system.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs report_problem safely

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

report_problem Rate-limited

report_problem 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "report_problem": {
      "limits": [
        {
          "counter": "report_problem_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

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

FAQ

Questions about report_problem

What does the report_problem tool do? +

Report a problem, feature request, or integration request to the LMCP team. IMPORTANT: Do NOT call this tool automatically. ALWAYS ask the user first: "Would you like me to report this issue to the LMCP team?" Only call this tool if the user explicitly agrees. When called without confirm=true, returns a preview of the anonymous data that will be sent. Show this preview to the user and only set confirm=true after they approve. No personal data is included — only version, OS, and permission status. Use type='feature' when the user wants a new capability. Use type='integration' when the user wants to connect an unsupported app. It is categorised as a Write tool in the Local MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does report_problem accept? +

report_problem accepts 8 parameters: confirm, symptom, expected, description, report_type, user_request, error_message, tool_attempted. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on report_problem? +

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

What risk level is report_problem? +

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

Can I rate-limit report_problem? +

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

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

report_problem is provided by the Local MCP server (local-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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