Push changes to remote repository.
AI agents invoke push_changes to trigger actions in Git MCP Assistant Tool. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
Pushing changes to a remote repository triggers an external operation that modifies the state of a remote system. While not locally destructive, a push can overwrite remote history (especially with force-push), expose sensitive code, or corrupt shared branches.
From the tool's definition Push changes to remote repository
Attacks that exploit this kind of access
Push changes to remote repository. It is categorised as a Execute tool in the Git MCP Assistant Tool MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Git MCP Assistant Tool MCP server in PolicyLayer and add a rule for push_changes: 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 Git MCP Assistant Tool. Nothing to install.
push_changes is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the push_changes 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 push_changes. 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.
push_changes is provided by the Git MCP Assistant Tool MCP server (kamiwaza-drew/tool-git). 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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