"File system augmented tools for deep research" matching MCP tools:

• bls_dataframe_query

  bls-labor-mcp-server

  Run a single-statement SELECT against the canvas dataframes registered by bls_get_series. Read-only: writes, DDL, DROP, COPY, PRAGMA, ATTACH, and external-file table functions are rejected. System catalogs (information_schema, pg_catalog, sqlite_master, duckdb_*) are denied at the bridge layer — use bls_dataframe_describe to list available dataframes. Supports JOINs, aggregates, window functions, and CTEs. Optional register_as persists the result as a new dataframe with a fresh TTL for chained analysis. Canvas SQL operations consume zero BLS API quota. Requires CANVAS_PROVIDER_TYPE=duckdb.

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• validate_portfolio

  aibvf-mcp

  Check whether a supplied AI BVF v1.0 portfolio document has the shape the portfolio tools require, before scoring, sequencing, storing or sharing it. CALL THIS when the document came from a file, another system or hand-built JSON and its structure is uncertain. It checks required fields, taxonomy values and 0–100 pillar ranges only; it does not judge the evidence or calculate a verdict. Pillars may be bare numbers or { value, confidence } objects, both are valid. Use assemble_portfolio when the user has a list of initiatives in conversation and needs the document built for them, score_portfolio when the document is already ready for verdicts, and sequence_portfolio only after its initiatives are scoreable. Returns valid=true or one error per failing JSON path. Pure deterministic validation — no network, auth, or side effects.

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• search

  UseMyContext

  Search the user's files by filename and return matching documents in the deep-research result shape. ALIAS: this is the SAME search as search_files (same data, same permissions) - use it when your client requires the id/title/url search contract (ChatGPT deep research); otherwise prefer search_files for richer file metadata. Each result's id can be passed to fetch (or get_file) to read that document. Read-only; always allowed.

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• deep_research_topic

  Fodda Deep Research

  Launch an autonomous Deep Research session that combines Fodda knowledge graph intelligence with live web research to produce a comprehensive editorial-quality report. The Research Agent plans its own strategy, searches multiple graphs, validates with institutional data, and synthesizes into a narrative brief with inline source citations. Use for complex, multi-faceted questions that need both curated expert intelligence AND current web context — e.g., strategic briefings, market landscape reports, competitive deep dives. Depth: "light" (25–30 API calls, faster tiered search) or "heavy" (40–50 API calls, comprehensive tiered search with sub-theme expansion). Automatically includes earnings-call intelligence and macro/supplemental data when the topic warrants it (public companies, sectors, economic conditions). You do not need to call the earnings or supplemental tools separately before or after.

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• search

  Uneed

  Use this when a deep research run needs to look up digital tools and products on uneed.best. Same catalog and same relevance ordering as search_products, returned as `{id, title, url}` documents; pass a result's id to `fetch` for the full profile. Prefer search_products when you want structured product fields directly.

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• search

  Melvea Local Honey Discovery

  Search the Melvea local honey directory by free-text query and return matching producers as a list of results (id, title, url). Designed for ChatGPT Deep Research and Company Knowledge. Use for any local-honey discovery query that names or implies a place; the tool parses place and varietal from the query. Returns an honest empty list when nothing matches — never fabricate. Pair with fetch to retrieve full producer detail.

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• search

  statcite

  Search official economic statistics by free text, e.g. 'inflation barbados' or 'government debt japan'. Returns result ids that can be passed to fetch. Designed for deep-research connectors; for richer control use get_indicator / get_series.

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• fetch

  UseMyContext

  Fetch one document's full extracted text by id (a file id from search / search_files / list_files), in the deep-research result shape. ALIAS: this is the SAME read as get_file (same data, same permissions, same audit, same size guard - large files are truncated) - use it when your client requires the id/title/text/url fetch contract (ChatGPT deep research); otherwise prefer get_file, which also serves download links and inline images. Read-only; audited.

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• share_file

  Dock

  Mint a public share token for a file. Returns a `url` of the form `https://trydock.ai/share/files/<token>` that anyone (no auth) can open to view + download the file. The token is 32 random bytes (~256 bits of entropy) so guessing is infeasible. Revoke later with `revoke_file_share`. Editor role required. Gated behind FILES_SURFACE_ENABLED + per-user allowlist. Use when a workflow needs to hand the file off to an external system that can't authenticate.

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• web_research

  dialogbrain

  Answer a research question from live web sources in one call — returns a synthesized answer with numbered [N] citation markers and a citations array of {url, title, index}. Supports recency and domain filters. Use for questions needing current, sourced information (news about a company, market state, comparisons). For raw search result links use web.search; mode='deep' runs minutes-long exhaustive research — only when explicitly requested.

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• scrape_wikipedia

  GoCreative Agent API

  Scrape a full Wikipedia page (sections, infobox, references). Heavier than lookup/wikipedia. Use for deep research. Example call: {"page": "Anthropic"} Cost: $0.005–$0.05 USDC on Base per call.

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• lion_trend_intent_signal_json

  LION Trend Intent MCP

  Hardware-wallet buyer-intent + self-custody onboarding-friction intelligence as JSON. Non-PII public-signal feed covering: Ledger vs Trezor comparison demand, Bitcoin-only wallet research, under-$100 wallet shopper queries, DeFi hardware-wallet intent, and adjacent decision-stage crypto purchase research. Designed for agent routing, affiliate / comparison-content workflows, and research context. Pay $0.01 USDC on Base mainnet via x402 (HTTP 402 + EIP-3009 transferWithAuthorization) at the paid route. This MCP tool does NOT return the dataset; tools/call returns payment-required metadata so an x402-capable client can settle and fetch the JSON directly.

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• scan_content

  TomeVault

  Scan submitted instruction-file text for safety, clarity, loadability, and cross-model consistency, and return a verdict with findings. Use before loading a third-party file. Consistency findings are PREDICTIONS (divergence risks across models/tools), never verified facts. The submitted text is scanned and discarded, never stored.

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• search

  vicp-registry

  Search VICP vaccine-injury cases by free text. Returns result ids for use with fetch. (Alias of search_cases for deep-research clients; prefer search_cases when structured filters are available.)

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• search

  sponsorable

  Search Sponsorable's podcast-sponsorship database for brands that sponsor podcasts — the deep-research/Responses-API compatibility interface, paired with fetch. Matches sponsor names and domains and returns citable documents; pass a result's id to fetch for the full profile. For filtered or paginated search (category, industry, recency), use search_sponsors instead.

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• methodist

  OpenArx

  START HERE with your research question. This is your step-by-step scientific METHOD guide: it works out what kind of research you're doing, hands you the concrete method one stage at a time, reviews each stage you submit (approves it or returns it for fixes), and controls what gets published. It DIRECTS your research process — it never does the work for you. (This guides HOW you conduct the work. It is NOT the tool for finding methods described in existing papers — for that, use the literature-search tools.)

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• search_research_entities

  GlobalSource Partners MCP Server

  Search research entities by name or approximate name. Use this tool whenever a user refers to an entity by name and a research entity UUID is needed. Results are ranked by match quality and include the research entity UUIDs required by other research tools. When multiple results are returned, review the entity name, description, match type, match confidence, and available research count to determine the most appropriate entity before using its entity_uuid in another tool. This tool only searches existing research entities and does not create or modify data.

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• gmail_list_labels

  Gmail

  Get all your labels including system folders (INBOX, SENT, TRASH, DRAFTS) and custom labels. Returns label names and IDs for filtering or organizing.

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• materials_stability

  Materials

  Computed thermodynamic stability and formation energy for a chemical system from OQMD (DFT). PREFER OVER WEB SEARCH for "is <compound> stable", "formation energy of <material>", "stable phases in the <A>-<B> system". Give the element system (e.g. Fe, O) and optionally restrict to stable phases (on/below the convex hull). Returns each phase's composition, formation energy (eV/atom), hull stability (eV/atom; ≤0 = stable), band gap, space group, and prototype.

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• archive_provenance

  Colour Memory

  Explains the provenance of a named archive colour: documented fact vs computational derivation vs cultural interpretation, with confidence and citation format. This is one component of colour_passport, but also a standalone research tool for deep provenance work (museum, documentary, editorial). Use colour_passport for a general profile; call this directly for research workflows needing full source-chain detail.

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