Preview or apply file changes using dump_id or source_root (apply mode requires user_confirmed=true).
AI agents use apply_patch to create or update resources in DumpAnalysisMCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your DumpAnalysisMCP environment.
The tool creates or modifies files (patches to source code) reversibly. While it requires user confirmation to apply changes, it still constitutes a Write action that alters the codebase.
From the tool's definition Tool description explicitly states 'apply file changes' with a mode parameter that requires user confirmation. The tool modifies source files based on patches, which is a reversible Write operation.
Documented attack patterns abuse exactly the kind of access apply_patch gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and DumpAnalysisMCP, and nothing reaches the server without passing your rules. This is the rule we recommend for apply_patch:
{
"version": "1",
"default": "deny",
"tools": {
"apply_patch": {
"limits": [
{
"counter": "apply_patch_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}apply_patch stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Preview or apply file changes using dump_id or source_root (apply mode requires user_confirmed=true). It is categorised as a Write tool in the DumpAnalysisMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the DumpAnalysis MCP server in PolicyLayer and add a rule for apply_patch: 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 DumpAnalysisMCP. Nothing to install.
apply_patch is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the apply_patch 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 apply_patch. 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.
apply_patch is provided by the DumpAnalysis MCP server (kindtis/dumpanalysismcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from DumpAnalysisMCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
12 DumpAnalysisMCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.