vision.solve_calibration_board
Recover metric OpenCV cameras from an authoritative measured chessboard.
This record as markdown: /tools/visionmcp/vision.solve-calibration-board.md
What vision.solve_calibration_board does on Visionmcp
AI agents invoke vision.solve_calibration_board to trigger actions in Visionmcp. 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.
Why vision.solve_calibration_board is rated High
The tool runs a calibration algorithm to derive and store camera parameters from a chessboard image. This is more than a read (it computes and likely writes calibration results), but not destructive or financial. It falls under Execute because it triggers an external computation process whose effects depend on the input board measurements.
From the tool's definition "Recover metric OpenCV cameras from an authoritative measured chessboard" — performs camera calibration computation (recovering camera parameters) from input data, which is a non-trivial execution of a calibration algorithm with side effects on internal…
Attacks that exploit this kind of access
The rule that runs vision.solve_calibration_board safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Visionmcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For vision.solve_calibration_board, this is the rule to start with:
vision.solve_calibration_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.
The button opens the PolicyLayer dashboard: create your workspace, connect Visionmcp, apply this rule, and every vision.solve_calibration_board call is checked against it from then on.
Questions about vision.solve_calibration_board
Recover metric OpenCV cameras from an authoritative measured chessboard. It is categorised as a Execute tool in the Visionmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Vision MCP server in PolicyLayer and add a rule for vision.solve_calibration_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 Visionmcp. Nothing to install.
vision.solve_calibration_board is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the vision.solve_calibration_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.
Set action: deny in the PolicyLayer policy for vision.solve_calibration_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.
vision.solve_calibration_board is provided by the Vision MCP server (joshuahickscorp/visionmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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