This record as markdown: /tools/agentics-ai-code-mcp/apply-patch.md
What apply_patch does on Code MCP Server
AI agents use apply_patch to create or update resources in Code MCP Server, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Code MCP Server environment.
Why apply_patch is rated Medium
Applying a patch is a reversible modification operation that creates or alters file contents based on patch directives. It falls under Write rather than Execute because the tool does not run code or trigger external operations — it applies structured file modifications.
From the tool's definition Tool description states 'Apply a patch file to the workspace' — this modifies files within the workspace by applying changes from a patch file.
Attacks that exploit this kind of access
The rule that runs apply_patch safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Code MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For apply_patch, this is the rule to start with:
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.
The button opens the PolicyLayer dashboard: create your workspace, connect Code MCP Server, apply this rule, and every apply_patch call is checked against it from then on.
Questions about apply_patch
Apply a patch file to the workspace. It is categorised as a Write tool in the Code MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Code MCP Server 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 Code MCP Server. 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 Code MCP Server MCP server (agentics-ai/code-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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