create_pr_with_content
AI agents use create_pr_with_content to create or update resources in GitHub MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GitHub MCP Server environment.
Creating a pull request is a reversible write operation that modifies repository state by introducing new proposed changes. While PRs can be closed/deleted, the primary action is to create new data structures. This is less severe than destructive operations (which cannot be undone) but more impactful than simple data retrieval.
From the tool's definition Tool name 'create_pr_with_content' indicates creation of pull requests with specified content. Sibling tools like 'create_issues' and 'create_milestone' are also write operations. The description is empty, limiting precision.
Attacks that exploit this kind of access
create_pr_with_content. It is categorised as a Write tool in the GitHub MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GitHub MCP Server MCP server in PolicyLayer and add a rule for create_pr_with_content: 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 MCP Server. Nothing to install.
create_pr_with_content 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 create_pr_with_content 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 create_pr_with_content. 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.
create_pr_with_content is provided by the GitHub MCP Server MCP server (rriesco/github-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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