deep_research

SERVERLinear SOURCEhttps://gateway.pipeworx.io/linear/mcp

Low RISK CLASS

Category Read

Parameters 21 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-pipeworx-io-linear/deep-research.md

WHAT IT DOES

What deep_research does on Linear

AI agents call deep_research 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
`depth`	string	—	How many facets to research in parallel: quick=3 (single hop), standard=5 (default; adds a gap-recovery hop that re-angles unanswered facets + a contradictions[
`question`	string	Yes	The research question, in natural language. Broad/multi-part is fine — decomposition is the point.

Parameters from the server's own tool schema.

RISK

Why deep_research is rated Low

Even though deep_research only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

deep_research Allowed

deep_research is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "deep_research": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

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

FAQ

Questions about deep_research

What does the deep_research tool do? +

ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1345 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,114 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a hop field and a citation_uri (record-level pipeworx:// when the source emits one, else source-level). "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s). It is categorised as a Read tool in the Linear MCP Server, which means it retrieves data without modifying state.

What parameters does deep_research accept? +

deep_research accepts 2 parameters: depth, question. Required: question. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on deep_research? +

Register the Linear MCP server in PolicyLayer and add a rule for deep_research: 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.

What risk level is deep_research? +

deep_research is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit deep_research? +

Yes. Add a rate_limit block to the deep_research 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 deep_research completely? +

Set action: deny in the PolicyLayer policy for deep_research. 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 deep_research? +

deep_research 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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