# deep_research

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).

Agent View of the PolicyLayer registry record for `deep_research`. HTML page: https://policylayer.com/tools/io-github-pipeworx-io-linear/deep-research

## Facts

- Tool: `deep_research`
- Server: Linear (`https://gateway.pipeworx.io/linear/mcp`) — https://policylayer.com/tools/io-github-pipeworx-io-linear.md
- Homepage: https://github.com/pipeworx-io/mcp-linear
- Risk category: Read (Low risk)
- Registry record: grade F, identity unverified
- Server auth posture: open
- Server CORS policy: *
- Server rate-limited: yes
- Parameters: 2 (1 required)
- Recommended policy verdict: Allowed

## Parameters

| Parameter | Type | Required | Description |
| --- | --- | --- | --- |
| `depth` | string | no | 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.

## Example call (MCP tools/call, JSON-RPC 2.0)

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "deep_research",
    "arguments": {
      "question": "<question>"
    }
  }
}
```

## 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.

## Use case

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.

## Recommended policy (PolicyLayer)

Verdict: **Allowed**. Enforced by the PolicyLayer MCP gateway (https://policylayer.com/mcp-gateway) before a call reaches Linear:

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

## Other tools on Linear (35)

- `forget` — Destructive — https://policylayer.com/tools/io-github-pipeworx-io-linear/forget.md
- `generate_llms_txt` — Execute — https://policylayer.com/tools/io-github-pipeworx-io-linear/generate-llms-txt.md
- `polymarket_edges` — Financial — https://policylayer.com/tools/io-github-pipeworx-io-linear/polymarket-edges.md
- `polymarket_fill_risk` — Financial — https://policylayer.com/tools/io-github-pipeworx-io-linear/polymarket-fill-risk.md
- `ai_visibility_check` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/ai-visibility-check.md
- `ask_pipeworx` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/ask-pipeworx.md
- `ask_pipeworx_beta` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/ask-pipeworx-beta.md
- `ask_pipeworx_grounded` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/ask-pipeworx-grounded.md
- `bet_research` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/bet-research.md
- `compare_entities` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/compare-entities.md
- `discover_tools` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/discover-tools.md
- `entity_profile` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/entity-profile.md
- `linear_get_issue` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/linear-get-issue.md
- `linear_list_issues` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/linear-list-issues.md
- `linear_list_teams` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/linear-list-teams.md
- `linear_search` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/linear-search.md
- `list_subscriptions` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/list-subscriptions.md
- `pipeworx_trending` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/pipeworx-trending.md
- `polymarket_arbitrage` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/polymarket-arbitrage.md
- `polymarket_edge_tracker` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/polymarket-edge-tracker.md
- `polymarket_kalshi_spread` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/polymarket-kalshi-spread.md
- `recall` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/recall.md
- `recent_alerts` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/recent-alerts.md
- `recent_changes` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/recent-changes.md
- `resolve_entity` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/resolve-entity.md
- `scan_competitor_ai_presence` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/scan-competitor-ai-presence.md
- `scan_dependency` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/scan-dependency.md
- `search_within` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/search-within.md
- `suggest_questions` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/suggest-questions.md
- `validate_claim` — Read — https://policylayer.com/tools/io-github-pipeworx-io-linear/validate-claim.md
- …and 5 more: https://policylayer.com/tools/io-github-pipeworx-io-linear.md

## For agents

This record is a snapshot. Live verdicts and the full registry:

- Check every server in your MCP config at once: `npx -y policylayer stack`
- Vet a server before you add it: install the mcp-precheck skill — `npx skills add https://policylayer.com` (skill text: https://policylayer.com/skill.md)
- Query the registry over MCP: endpoint `https://api.policylayer.com/mcp` — tools `check_mcp_server`, `check_mcp_stack`, `check_tool`, `search_registry`, `get_change_events`

---

Source: the PolicyLayer MCP registry — one continuously verified record per MCP server. Full record: https://policylayer.com/registry?q=io-github-pipeworx-io-linear · API: https://policylayer.com/registry/api · Policy library: https://policylayer.com/policies/io-github-pipeworx-io-linear