AI agents call count-matches to retrieve information from Ripgrep without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs a read-only search operation using ripgrep to count pattern matches across files. It retrieves information (match counts) without side effects, reversibility requirements, or code execution. This is a classic Read category tool—it queries data and reports results.
From the tool's definition Tool name 'count-matches' and description 'Count matches in files using ripgrep' indicate a query operation that retrieves aggregate data without modifying files or executing arbitrary code.
Attacks that exploit this kind of access
Count matches in files using ripgrep. It is categorised as a Read tool in the Ripgrep MCP Server, which means it retrieves data without modifying state.
Register the Ripgrep MCP server in PolicyLayer and add a rule for count-matches: 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 Ripgrep. Nothing to install.
count-matches 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 count-matches 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 count-matches. 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.
count-matches is provided by the Ripgrep MCP server (shk1447/ripgrep-mcp). 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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