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 1213 STRUCTURED data sources (SEC filings, FRED/BLS economi...
AI agents call deep_research to retrieve information from Mcp Themeparks without modifying anything — 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, standard=5 (default), thorough=8 (paid plans). |
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.
This is a data retrieval and aggregation tool. It searches structured databases (SEC filings, economic data, FDA records, patents, etc.) and returns research findings without modifying any underlying data. The ability to require authentication and mention 'depth' levels does not change the fundamental read-only nature of research queries. No side effects, financial transactions, or code execution are involved.
From the tool's definition Tool performs 'multi-source research across...1213 STRUCTURED data sources' and 'returns a findings packet: verbatim evidence + confidence + source + fetched_at'. Decomposes questions and routes them to retrieve data in parallel.
Attacks that exploit this kind of access
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 1213 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 4,676 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. It is categorised as a Read tool in the Mcp Themeparks MCP Server, which means it retrieves data without modifying state.
deep_research accepts 2 parameters: depth, question. Required: question. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Themeparks 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 Mcp Themeparks. Nothing to install.
deep_research 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 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.
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.
deep_research is provided by the Mcp Themeparks MCP server (pipeworx-io/mcp-themeparks). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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