Update a Linear saved view (API: updateCustomView). Provide id plus at least one other field to change.
AI agents use linear_updateSavedView 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 modifies an existing resource (a saved view/custom view) without deleting it. Updates to saved views—such as changing filters, sorting, or display settings—are reversible changes that affect data state but do not destroy information. This qualifies as Write rather than Destructive.
From the tool's definition Tool description states 'Update a Linear saved view' and accepts 'id plus at least one other field to change', indicating modification of existing data (saved view configurations).
Documented attack patterns abuse exactly the kind of access linear_updateSavedView 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_updateSavedView:
{
"version": "1",
"default": "deny",
"tools": {
"linear_updateSavedView": {
"limits": [
{
"counter": "linear_updatesavedview_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}linear_updateSavedView 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.
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Update a Linear saved view (API: updateCustomView). Provide id plus at least one other field to change. 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_updateSavedView: 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_updateSavedView 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_updateSavedView 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_updateSavedView. 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_updateSavedView 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.