AI agents use close_issue to create or update resources in Git MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Git MCP Server environment.
Closing an issue modifies its state reversibly—the issue remains in the repository and can be reopened. This is a data modification (Write) rather than destructive deletion. Severity is medium because an AI agent misusing this could close critical issues improperly, disrupting workflows, but the action is not irreversible and does not cause data loss or financial harm.
From the tool's definition Tool name 'close_issue' and description 'Close an issue' indicate modification of issue state/metadata. This is a write operation that changes issue status but does not delete data or cause financial impact.
Documented attack patterns abuse exactly the kind of access close_issue gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Git MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for close_issue:
{
"version": "1",
"default": "deny",
"tools": {
"close_issue": {
"limits": [
{
"counter": "close_issue_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}close_issue 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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Close an issue. It is categorised as a Write tool in the Git MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Git MCP Server MCP server in PolicyLayer and add a rule for close_issue: 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 Server. Nothing to install.
close_issue 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 close_issue 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 close_issue. 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.
close_issue is provided by the Git MCP Server MCP server (yumeminami/git_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Git MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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33 Git MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.