deep_research
ActiveTool of wikipedia
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 1234 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 4,748 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. Expect 15-60s.
Parameters schema
{
"type": "object",
"required": [
"question"
],
"properties": {
"depth": {
"enum": [
"quick",
"standard",
"thorough"
],
"type": "string",
"description": "How many facets to research in parallel: quick=3, standard=5 (default), thorough=8 (paid plans)."
},
"question": {
"type": "string",
"description": "The research question, in natural language. Broad/multi-part is fine — decomposition is the point."
}
}
}Parent server
wikipedia
https://github.com/pipeworx-io/mcp-wikipedia
2/7 registries