Record a point-in-time inventory of the user's project under a workspace. Remote MCP cannot see the filesystem, so YOU (the AI) collect this inventory with your own Read/Glob/Grep tools before calling this. Persist it so future setup, bootstrap, drift detection, and onboarding flows have structur...
Risk signalsAccepts file system path (file_tree[].path) · Accepts raw HTML/template content (sampled_contents[].content) · High parameter count (25 properties)
Part of the Pathrule server.
Free to start. No card required.
AI agents call pathrule_take_snapshot to retrieve information from Pathrule 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 pathrule_take_snapshot 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.
{
"version": "1",
"default": "deny",
"tools": {
"pathrule_take_snapshot": {}
}
}See the full Pathrule policy for all 30 tools.
These attack patterns abuse exactly the kind of access pathrule_take_snapshot gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Record a point-in-time inventory of the user's project under a workspace. Remote MCP cannot see the filesystem, so YOU (the AI) collect this inventory with your own Read/Glob/Grep tools before calling this. Persist it so future setup, bootstrap, drift detection, and onboarding flows have structured evidence to reason over. Required: workspace_id. Strongly recommended: project_name, file_count, file_tree (cap at ~5000 entries — summarise deeper paths), file_extensions_summary, top_level_dirs, sampled_contents for README, package.json / pyproject.toml / Cargo.toml, CLAUDE.md, AGENTS.md, main config files (truncate each to ~4KB). Optional: git_head / branch / git_log_summary if you can read them, ai_notes for free-form observations.. It is categorised as a Read tool in the Pathrule MCP Server, which means it retrieves data without modifying state.
Register the Pathrule MCP server in PolicyLayer and add a rule for pathrule_take_snapshot: 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 Pathrule. Nothing to install.
pathrule_take_snapshot 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 pathrule_take_snapshot 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 pathrule_take_snapshot. 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.
pathrule_take_snapshot is provided by the Pathrule MCP server (https://mcp.pathrule.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 30 Pathrule tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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