AI agents use linear_addToFavorites 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.
This tool creates or modifies user preference data (favorite status) without side effects beyond the Linear system itself. It is reversible, affects only metadata/preferences, and has minimal blast radius if misused by an AI agent. Classified as Write rather than Read because it modifies state, and lower severity due to the benign nature of the operation (adding favorites carries minimal risk).
From the tool's definition Tool name 'linear_addToFavorites' and description indicate it adds/modifies user preferences by marking an entity as a favorite. This is a reversible state change (can be unfavorited) with no data deletion or external execution.
Documented attack patterns abuse exactly the kind of access linear_addToFavorites gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Linear, and nothing reaches the server without passing your rules. This is the rule we recommend for linear_addToFavorites:
{
"version": "1",
"default": "deny",
"tools": {
"linear_addToFavorites": {
"limits": [
{
"counter": "linear_addtofavorites_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}linear_addToFavorites 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.
Free to start. No card required.
Add an entity to the current user\. 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.
Register the Linear MCP server in PolicyLayer and add a rule for linear_addToFavorites: 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.
linear_addToFavorites 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 linear_addToFavorites 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 linear_addToFavorites. 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.
linear_addToFavorites is provided by the Linear MCP server (tacticlaunch/mcp-linear). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 182 Linear tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
182 Linear tools catalogued and risk-classified — across an index of 42,500+ MCP servers.