"A server for finding financial data" matching MCP tools:

• deep_research

  Taginfo

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Singstat Sg

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Tavily

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Warframe

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Youtube

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Paperswithcode

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Postscript

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Carbon Intensity Uk

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Weatherapi

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Exoplanet Archive

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Overheid Nl

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• ping

  Nordic Financial MCP

  Connectivity check that confirms the Nordic MCP server process is responding. Use this at the start of a session to verify the server is reachable before making other calls. Do not use as a proxy for database health — the server can respond while the Qdrant vector database is temporarily unavailable. To confirm data availability, call search_filings directly. Returns: A greeting string: "Hello {name}! Nordic MCP server is running."

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• deep_research

  Datamuse

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Metabolights

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Jersey Opendata

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Internet Archive

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  nouel

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• deep_research

  Datacite

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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• deep_research

  Tfl

  Grounded multi-source research in ONE call. Decomposes your question into focused sub-questions, routes each to the right one of 3,745 tools across 884 authoritative sources IN PARALLEL, and extracts a grounded answer per facet — verbatim evidence, confidence, source, fetched_at, and a stable pipeworx:// citation on every finding, with explicit gaps[] for facets the data couldn't answer (never invented). Returns a structured findings packet you can synthesize for your user; the facts arrive pre-verified. Use for broad or multi-part questions ("compare X and Y's exposure to Z", "research the regulatory + financial + market picture for ACME"); use ask_pipeworx for single lookups — it's one LLM call instead of many. Requires a Pipeworx account (sign in via GitHub at https://pipeworx.io/signup); depth:"thorough" requires a paid plan. Expect 15-60s.

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