configure_board

Send a board-specific configuration command through BrainFlow's config_board (e.g. OpenBCI

SERVERPypi:labmcp Alicat SOURCEpypi:labmcp-alicat

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/lab-instrument-mcps/configure-board.md

WHAT IT DOES

What configure_board does on Pypi:labmcp Alicat

AI agents invoke configure_board to trigger actions in Pypi:labmcp Alicat. 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 configure_board is rated High

Executes hardware configuration commands on lab instrument boards with unpredictable effects.

From the tool's definition Send a board-specific configuration command through BrainFlow's config_board

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs configure_board safely

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

configure_board Rate-limited

configure_board 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": {
    "configure_board": {
      "limits": [
        {
          "counter": "configure_board_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 Pypi:labmcp Alicat, apply this rule, and every configure_board call is checked against it from then on.

FAQ

Questions about configure_board

What does the configure_board tool do? +

Send a board-specific configuration command through BrainFlow's config_board (e.g. OpenBCI. It is categorised as a Execute tool in the Pypi:labmcp Alicat MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on configure_board? +

Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for configure_board: 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 Pypi:labmcp Alicat. Nothing to install.

What risk level is configure_board? +

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

Can I rate-limit configure_board? +

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

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

configure_board is provided by the Pypi:labmcp Alicat MCP server (pypi:labmcp-alicat). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

KEEP EXPLORING

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