Low Risk

kai_checkpoint

Record an AI code authorship checkpoint. Call this after editing files to track which code was AI-generated. Lightweight — writes a small JSON file, no DB needed.

Risk signalsAccepts file system path (file)

Part of the Kai server.

kai_checkpoint is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call kai_checkpoint to retrieve information from Kai without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though kai_checkpoint only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "kai_checkpoint": {}
  }
}

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Get this rule live on your own Kai server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access kai_checkpoint gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so kai_checkpoint only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the kai_checkpoint tool do? +

Record an AI code authorship checkpoint. Call this after editing files to track which code was AI-generated. Lightweight — writes a small JSON file, no DB needed.. It is categorised as a Read tool in the Kai MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on kai_checkpoint? +

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

What risk level is kai_checkpoint? +

kai_checkpoint is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit kai_checkpoint? +

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

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

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

Enforce policy on every Kai tool call.

Deterministic rules across all 18 Kai tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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