git_checkout
A execute tool on the GitHub MCP server.
This record as markdown: /tools/io-github-aifity-omnigit-mcp/git-checkout.md
What git_checkout does on GitHub
AI agents invoke git_checkout to trigger actions in GitHub. 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.
Why git_checkout is rated High
Git checkout switches branches or restores working tree files, which is an operation that triggers external git operations and can alter repository state. The description is minimal/uninformative, but the tool name clearly references a git operation that changes the working tree or branch context. This could affect code being built/deployed, making it high severity if misused by an AI agent.
From the tool's definition Tool name 'git_checkout' and description 'Git checkout'
Attacks that exploit this kind of access
The rule that runs git_checkout safely
PolicyLayer is an MCP gateway: it sits between your AI agents and GitHub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For git_checkout, this is the rule to start with:
git_checkout stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect GitHub, apply this rule, and every git_checkout call is checked against it from then on.
Questions about git_checkout
git_checkout is a execute tool on the GitHub MCP server. It is categorised as a Execute tool in the GitHub MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the GitHub MCP server in PolicyLayer and add a rule for git_checkout: 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 GitHub. Nothing to install.
git_checkout 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 git_checkout 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 git_checkout. 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.
git_checkout is provided by the GitHub MCP server (oci:ghcr.io/aifity/omnigit-mcp:0.5.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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