Update an existing issue in a GitHub repository
AI agents use update_issue to create or update resources in Server Github — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Server Github environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
body | string | — | |
repo | string | Yes | |
owner | string | Yes | |
state | string | — | |
title | string | — | |
labels | array | — | |
assignees | array | — | |
milestone | number | — | |
issue_number | number | Yes |
Parameters from the server's own tool schema.
Updating an issue (title, description, labels, state, etc.) is a Write operation—it modifies existing data reversibly. It is not Destructive (no deletion/permanent removal), not Execute (no arbitrary code or external operations triggered), not Financial.
From the tool's definition Tool name 'update_issue' and description 'Update an existing issue in a GitHub repository' indicate modification of existing data. This is a reversible change operation that creates or modifies data without deletion.
Risk signalsAccepts raw HTML/template content (body)
Attacks that exploit this kind of access
Update an existing issue in a GitHub repository. It is categorised as a Write tool in the Server Github MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_issue accepts 9 parameters: body, repo, owner, state, title, labels, assignees, milestone, issue_number. Required: repo, owner, issue_number. The full parameter table on this page comes from the server's own tool schema.
Register the Server Github MCP server in PolicyLayer and add a rule for update_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 Server Github. Nothing to install.
update_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 update_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 update_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.
update_issue is provided by the Server Github MCP server (@iflow-mcp/server-github). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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