AI agents use update_repository to create or update resources in MCP Code Analysis Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your MCP Code Analysis Server environment.
This tool modifies repository metadata without permanently destroying data or executing arbitrary code. The change is reversible—metadata can be updated again or reverted. While it affects repository state, the impact is limited to metadata rather than code execution or financial operations.
From the tool's definition Tool name is 'update_repository' and description states it 'Update repository metadata'. The verb 'update' indicates modification of existing data in a reversible manner.
Documented attack patterns abuse exactly the kind of access update_repository gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Code Analysis Server, and nothing reaches the server without passing your rules. This is the rule we recommend for update_repository:
{
"version": "1",
"default": "deny",
"tools": {
"update_repository": {
"limits": [
{
"counter": "update_repository_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_repository 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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Update repository metadata. It is categorised as a Write tool in the MCP Code Analysis Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MCP Code Analysis Server MCP server in PolicyLayer and add a rule for update_repository: 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 MCP Code Analysis Server. Nothing to install.
update_repository 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 update_repository 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 update_repository. 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.
update_repository is provided by the MCP Code Analysis Server MCP server (johannhartmann/mcpcodeanalysis). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Code Analysis 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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44 MCP Code Analysis Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.