Low Risk

code_review

Review code using Claude AI. Returns bugs, improvements, and best practice suggestions.

Risk signalsAccepts freeform code/query input (code)

Part of the SparkForge server.

code_review 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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Free to start. No card required.

AI agents call code_review to retrieve information from SparkForge 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 code_review 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": {
    "code_review": {}
  }
}

See the full SparkForge policy for all 33 tools.

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

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View all 33 tools →

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

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so code_review 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 code_review tool do? +

Review code using Claude AI. Returns bugs, improvements, and best practice suggestions.. It is categorised as a Read tool in the SparkForge MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on code_review? +

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

What risk level is code_review? +

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

Can I rate-limit code_review? +

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

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

code_review is provided by the SparkForge MCP server (henry-ships/sparkforge). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every SparkForge tool call.

Deterministic rules across all 33 SparkForge tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

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

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