recent_alerts
Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:tr...
This record as markdown: /tools/io-github-pipeworx-io-linear/recent-alerts.md
What recent_alerts does on Linear
AI agents call recent_alerts to retrieve information from Linear without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
type | string | — | Optional — filter to one subscription type. |
limit | number | — | Max events to return (1-200, default 50). |
since | string | — | Optional ISO timestamp — return events fired_at >= this time. |
mark_read | boolean | — | Flag the returned events read in the same call (default false). |
unread_only | boolean | — | Return only events where read_at is null (default false). |
Parameters from the server's own tool schema.
Why recent_alerts is rated Low
The primary action is retrieving/reading alert events from a feed. The mark_read:true flag is a minor state mutation (flagging items as read), but this is a reversible, low-impact side effect ancillary to the read operation. The tool does not create, modify, delete, or execute anything of consequence. Severity is low because misuse would only expose alert feed data.
From the tool's definition 'Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed' and 'the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards'
Attacks that exploit this kind of access
The rule that runs recent_alerts 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 recent_alerts, this is the rule to start with:
recent_alerts is read-only, so it stays allowed. 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 recent_alerts call is checked against it from then on.
Questions about recent_alerts
Pull fired events from your subscription feed. Returns the most recent alerts the evaluator has written to your persisted feed — each carries source, citation_uri (pipeworx:// when available), and the raw event payload. Filter by type (e.g. "sec_8k") and/or since (ISO timestamp). Set mark_read:true to flag returned events read so the next call only shows newer ones. Polls work fine; the same feed is also at GET registry.pipeworx.io/alerts.json for scripts and dashboards. It is categorised as a Read tool in the Linear MCP Server, which means it retrieves data without modifying state.
recent_alerts accepts 5 parameters: type, limit, since, mark_read, unread_only. 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 recent_alerts: 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.
recent_alerts is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the recent_alerts 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 recent_alerts. 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.
recent_alerts is provided by the Linear MCP server (https://gateway.pipeworx.io/linear/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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