This record as markdown: /tools/linear/update-project.md
What update_project does on Linear
AI agents use update_project to create or update resources in Linear, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Linear environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
id | string | — | The ID of the project to update |
name | string | — | The new name of the project |
leadId | string | — | The UUID of the user to set as project lead |
summary | string | — | A concise plaintext summary of the project (max 255 chars) |
labelIds | array | — | Array of label UUIDs to set on the project |
startDate | string | — | The start date of the project in ISO format |
targetDate | string | — | The target date of the project in ISO format |
description | string | — | The full project description in Markdown format |
Parameters from the server's own tool schema.
Why update_project is rated Medium
This tool modifies an existing project rather than creating or deleting it. The change is reversible since updates can be undone through subsequent modifications. The severity is medium because unintended project updates could disrupt team workflows, visibility, or project settings, but the changes themselves are not irreversible.
From the tool's definition Tool name is 'update_project' and description states 'Update an existing Linear project' - both indicate modification of existing data (project configuration, settings, metadata, etc.).
Attacks that exploit this kind of access
The rule that runs update_project safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Linear, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For update_project, this is the rule to start with:
update_project 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 Linear, apply this rule, and every update_project call is checked against it from then on.
Questions about update_project
Update an existing Linear project. It is categorised as a Write tool in the Linear MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
update_project accepts 8 parameters: id, name, leadId, summary, labelIds, startDate, targetDate, description. The full parameter table on this page comes from the server's own tool schema.
Register the Linear MCP server in PolicyLayer and add a rule for update_project: 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 Linear. Nothing to install.
update_project 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_project 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_project. 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_project is provided by the Linear MCP server (@linear-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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