IFRS 17 Measurement Model Classifier — OpenChainGraph compute node (compliance_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: art-178-ifrs17-csm-rollforward-validator. Open at: https://ainumbers.c...
AI agents call classify_ifrs17_measurement_model to retrieve information from Ainumbers Mcp Apps without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
compute | string | — | Compute mode (v0.4 Compute Binding). "auto" (default) = server for gpu:false nodes with registered kernels; "server" = force server-side; "browser" = always ret |
parent_hashes | array | — | execution_hash values from upstream ChainGraph AP2 artifacts to chain from (sets chain.parent_hashes in the export). |
parent_tool_ids | array | — | tool_id values matching parent_hashes, in the same order. |
policy_parameters | object | — | Input parameters for this tool's decision function. For gpu:false nodes with a registered kernel, these are computed server-side when compute is "auto" or "serv |
Parameters from the server's own tool schema.
This tool is a deterministic classifier that reads insurance contract input parameters and outputs a classification of the applicable IFRS 17 measurement model (GMM, PAA, or VFA). It produces an AP2 artifact with an execution hash for provenance, but this is a local/in-browser computation with no data egress, no PII, and no write/delete/financial side effects.
From the tool's definition Runs deterministically in-browser; zero PII, zero egress. Read-only, no auth, zero PII. 'Classifier' — classifies/reads input data to determine IFRS 17 measurement model.
Attacks that exploit this kind of access
IFRS 17 Measurement Model Classifier — OpenChainGraph compute node (compliance_mandate). Runs deterministically in-browser; zero PII, zero egress. Exports an AP2 artifact with execution_hash for chain provenance. Output feeds: art-178-ifrs17-csm-rollforward-validator. Open at: https://ainumbers.co/chaingraph/art-177-ifrs17-measurement-model-classifier.html. It is categorised as a Read tool in the Ainumbers Mcp Apps MCP Server, which means it retrieves data without modifying state.
classify_ifrs17_measurement_model accepts 4 parameters: compute, parent_hashes, parent_tool_ids, policy_parameters. The full parameter table on this page comes from the server's own tool schema.
Register the Ainumbers Mcp Apps MCP server in PolicyLayer and add a rule for classify_ifrs17_measurement_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 Ainumbers Mcp Apps. Nothing to install.
classify_ifrs17_measurement_model is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the classify_ifrs17_measurement_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.
Set action: deny in the PolicyLayer policy for classify_ifrs17_measurement_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.
classify_ifrs17_measurement_model is provided by the Ainumbers Mcp Apps MCP server (postoaklabs/ainumbers-mcp-apps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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