star_repository
A write tool on the GitHub MCP server.
This record as markdown: /tools/io-github-aifity-omnigit-mcp/star-repository.md
What star_repository does on GitHub
AI agents use star_repository to create or update resources in GitHub, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GitHub environment.
Why star_repository is rated Medium
Starring a GitHub repository is a reversible write operation that simply marks a repository as starred for the authenticated user. It has no destructive or financial implications, and can be easily undone by unstarring. The blast radius of misuse is very low.
From the tool's definition 'Star repository' - starring a repository is a reversible write action (can be unstarred) with minimal blast radius
Attacks that exploit this kind of access
The rule that runs star_repository 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 star_repository, this is the rule to start with:
star_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.
The button opens the PolicyLayer dashboard: create your workspace, connect GitHub, apply this rule, and every star_repository call is checked against it from then on.
Questions about star_repository
star_repository is a write tool on the GitHub MCP server. It is categorised as a Write tool in the GitHub MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the GitHub MCP server in PolicyLayer and add a rule for star_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 GitHub. Nothing to install.
star_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 star_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 star_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.
star_repository 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.
More on GitHub, and thousands of servers like it.
This server
Across the catalogue