update_pull_request

Update an existing pull request in a GitHub repository.

SERVERGitHub SOURCEoci:ghcr.io/github/github-mcp-server:1.3.0

Medium RISK CLASS

Category Write

Parameters 100 required

Recommended Rate-limitedsee the rule below

Registry record Grade D, identity verified Pull the record →

This record as markdown: /tools/github/update-pull-request.md

WHAT IT DOES

What update_pull_request does on GitHub

AI agents use update_pull_request 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.

Parameter	Type	Required	Description
`base`	string	—	New base branch name
`body`	string	—	New description
`repo`	string	—	Repository name
`draft`	boolean	—	Mark pull request as draft (true) or ready for review (false)
`owner`	string	—	Repository owner
`state`	string	—	New state
`title`	string	—	New title
`reviewers`	array	—	GitHub usernames to request reviews from
`pullNumber`	number	—	Pull request number to update
`maintainer_can_modify`	boolean	—	Allow maintainer edits

Parameters from the server's own tool schema.

RISK

Why update_pull_request is rated Medium

This tool modifies existing pull request resources reversibly. Updates to PR properties (title, body, labels, assignees, etc.) are characteristic of Write operations—they change state but don't permanently delete or destroy data, and don't execute code or move money.

From the tool's definition Tool name 'update_pull_request' and description 'Update an existing pull request in a GitHub repository' indicate modification of existing data (pull request metadata, title, description, etc.).

Risk signalsAccepts raw HTML/template content (body) · High parameter count (10 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs update_pull_request 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 update_pull_request, this is the rule to start with:

update_pull_request Rate-limited

update_pull_request 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "update_pull_request": {
      "limits": [
        {
          "counter": "update_pull_request_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GitHub, apply this rule, and every update_pull_request call is checked against it from then on.

FAQ

Questions about update_pull_request

What does the update_pull_request tool do? +

Update an existing pull request in a GitHub repository. 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.

What parameters does update_pull_request accept? +

update_pull_request accepts 10 parameters: base, body, repo, draft, owner, state, title, reviewers, pullNumber, maintainer_can_modify. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on update_pull_request? +

Register the GitHub MCP server in PolicyLayer and add a rule for update_pull_request: 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.

What risk level is update_pull_request? +

update_pull_request is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit update_pull_request? +

Yes. Add a rate_limit block to the update_pull_request 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.

How do I block update_pull_request completely? +

Set action: deny in the PolicyLayer policy for update_pull_request. 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.

What MCP server provides update_pull_request? +

update_pull_request is provided by the GitHub MCP server (oci:ghcr.io/github/github-mcp-server:1.3.0). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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