"A resource for conducting deep research" matching MCP tools:

• fetch

  OneQAZ Trading Intelligence

  Purpose: ChatGPT-connector-standard document fetch by id from `search` results. Namespaces: `tool:{name}` returns the tool's full documentation and how to call it; `resource:{uri}` returns the resource's live data (core resources resolved server-side — also the bridge for clients without MCP resource support, e.g. Gemini); `signal:{market}:{symbol}` returns the symbol's latest combined research signal. Triggers: ChatGPT connectors / Deep Research call this after `search`. Clients without MCP resource support can call it directly with a known resource id, e.g. fetch("resource:market://global/summary"). When to call: whenever the full content behind a search result id is needed. Prerequisites: a valid id — from `search` results or a known namespace id. Next steps: for tool docs, call the named tool via tools/call; for signals, get_signal_detail / explain_decision for deeper evidence. Caveats: uncovered resource uris return description-only text (no fabricated data). `text` is a JSON document for resource/signal ids. Output: {id, title, text, url, metadata, disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: id: document id — "tool:{name}", "resource:{uri}", or "signal:{market}:{symbol}" (market: crypto / kr_stock / us_stock) Disclaimer: Information only, not investment advice.

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• search

  DC Member API

  GET /search — Cross-resource omni-search Cross-resource search across profiles, rooms, messages (incl. private DMs + group DMs you're in), events, and chapters in one round trip. Returns the top-N matches per resource, grouped by resource. Use this when you don't yet know which resource carries the answer — agents typically call this first, then drill into a specific `GET /search/<resource>` for more depth on a single bucket. There's no page param: when you hit the per-resource limit and want more, switch to the per-resource endpoint for that one. The events slice has a baked-in forward-looking default (events ending in the last 30 days or later, and currently enabled) — this matches the in-app "Search across DC" surface. Use `GET /search/events` directly to look further back in time. **Query syntax (`q=`):** plain words match with prefix + typo tolerance. Wrap a phrase in double quotes to require an exact ordered match — e.g. `q="remote work"`. AND/OR/NOT/parentheses are NOT parsed in `q=` — use the structured filter params below for boolean composition.

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• search

  OneQAZ Trading Intelligence

  Purpose: ChatGPT-connector-standard discovery search over OneQAZ's live surface — tools, resources, and the latest strong combined signals across crypto / kr_stock / us_stock. Returns result ids consumable by the `fetch` tool. Triggers: ChatGPT connectors and Deep Research call this automatically for any user query routed to OneQAZ ("bitcoin signal", "prediction accuracy", "korean stocks today", ...). Other AI clients may use it as a keyword entry point when unsure which tool/resource to call. When to call: first step of connector-style discovery. MCP-native clients can instead browse tools/list + resources/list directly. Prerequisites: none. Next steps: pass any result id to `fetch` for the full document. Caveats: corpus is rebuilt at most every 10 minutes (tool/resource catalog + top-20 strong signals per market). Empty results list means no match. Output: {results: [{id, title, url}], disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Args: query: free-text search string (English/Korean, symbols like BTC/AAPL) Disclaimer: Information only, not investment advice.

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• la_query

  Data La

  Run a raw SoQL query against any Los Angeles open-data resource (data.lacity.org) by its Socrata id (8-char like "2nrs-mtv8"). Full SoQL: where/select/group/order/limit/offset. Use la_datasets to find a resource id, or la_recent for the common ones.

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• search

  UseMyContext.ai

  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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• find_methodology

  OpenArx

  Find methodology approaches for a specific research task. Returns structured method-level results (not raw chunks): method name, key idea, dataset used, performance metric. Filters by task domain, dataset, metric. Built on LLM-classified contentType=methodology chunks combined with benchmark results JOIN. Use this instead of `search` when you want HOW researchers approach a problem rather than 10 papers about it. Note: surfaces any chunk classified as methodology, including ones where the task is mentioned only as a toy example. Filter by category (e.g. cs.CV for image tasks) to narrow scope. This searches EXISTING papers for methods others have published (literature search) — it is NOT a guide for conducting your own research: for a step-by-step scientific method tailored to your own research question, start with the `methodist` door.

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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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• convert_to_terraform

  Control Plane

  Convert a Control Plane resource manifest (YAML or JSON) into the equivalent Terraform (HCL). The manifest is first DRY-RUN VALIDATED against the API (no resource is created) — if it fails validation you get the error instead of HCL, so the returned Terraform always corresponds to a schema-valid resource. Pass `gvc` when the kind is GVC-scoped (workload, identity, volumeset). Set `generateImports` to also return ready-to-run `terraform import` commands. To convert an EXISTING resource instead of a manifest, use export_terraform.

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• search

  Dados Abertos Senado BR MCP

  Searches the Brazilian Federal Senate open data (senators in office and active committees of the Senate and the National Congress) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched). This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools `search` and `fetch`. Pass one of the returned ids to `fetch` to read the document. For direct questions and for data (values, series, rankings) prefer the `senado_*` tools, which return the actual data with provenance — this is a catalog index, not a data query. Query: natural language or keywords, Portuguese or English; accents and case are ignored. Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

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• search

  UNESCO UIS — Education, Science & Culture Statistics (provenance-first)

  Searches the UNESCO UIS statistics (≈5,000 indicators: education — enrolment, completion, literacy, teachers, spending, SDG 4 —, science/R&D (SDG 9.5), culture (SDG 11.4) and demographic context) catalog and returns up to 10 matching documents as { id, title, url }, ordered by relevance (an empty list means nothing matched). This tool exists for the OpenAI Deep Research contract: ChatGPT deep research, company knowledge and research workflows over the Responses API require exactly the tools `search` and `fetch`. Pass one of the returned ids to `fetch` to read the document. For direct questions and for data (values, series, rankings) prefer the `uis_*` tools, which return the actual data with provenance — this is a catalog index, not a data query. Query: natural language or keywords, Portuguese or English; accents and case are ignored. Behavior: read-only and idempotent — the catalog comes from the public source and is cached in memory.

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• verify_references

  Stipple — Document Verification & Extraction

  Fact-check a document's REFERENCES and CLAIMS — built for AI-generated reports whose citations must be checked before they're trusted. USE THIS WHEN someone shares a report, article, whitepaper, or deep-research export (or a link to one) and asks: is this accurate / legit? are these citations real? fact-check this. did the AI make this up? Also use it proactively before relying on any AI-written document. Provide the document ONE way: `url` (a public http(s) link to a PDF or web page — fetched server-side, the cheapest call: no need to download or encode anything), `text` (pasted markdown/plain prose), OR `bytes_b64` (a base64 PDF; URLs are read from the PDF's link annotations, so they're exact). Default (fast): provenance (is it a ChatGPT deep-research export?), citation resolution (live / archived / dead, papers matched against arXiv/Crossref to catch 'real ID, wrong paper'), and internal MATH (recompute the doc's own arithmetic). Set `deep=true` to also fetch each cited source and judge whether it SUPPORTS or CONTRADICTS the claim (slower, ~a minute). Returns a trust summary, per-item tables, and a shareable `permalink` to the public fact-check record. HONEST BOUNDARY: this reports verification COVERAGE, not truth — 'supported' means evidence-backed (not necessarily true) and 'unsupported' means no evidence found (not necessarily false). It tells a reviewer WHERE to look; it does not bless the document, and it never affects the fraud risk band. Costs 2 credit(s) per call (5 in deep mode).

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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 — Verified Economic Statistics

  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.ai

  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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• elevenlabs_unshare_resource_endpoint

  ElevenLabs

  Unshare Workspace Resource. Removes any existing role on a workspace resource from a user, group, or workspace (service account) API key. To target a user or service account, pass only the user email; the user must be in your workspace. To target a group, pass only the group id. To target a workspace (service account) API key, pass the api key id; the resource will be unshared from the service account associated with that key. You must have admin access to the resource to unshare it. You cannot remove permissions from the user who created the resource. Bulk support: accepts resource_ids, group_ids, workspace_api_key_ids for batched execution.

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• simulation.recover_resource

  Cloud World Model

  Recover one reversible failed resource in a temporary anonymous demo simulation. Lower traffic to a serviceable level first, then provide resourceId or resourceName from simulation.create, simulation.step, or simulation.metrics. This deactivates applicable instance_down/database_overload failures for only the selected resource and returns recoveryProgress with parked, cooling_down, or healthy state plus cooldown counters. It cannot restore an instance_kill because that failure permanently removes the resource. The likely next tool is simulation.step; keep stepping and inspect the targeted resource until recoveryProgress.state is healthy. Pass simulationId from simulation.create when using a fresh MCP session; a preserved session may omit it. Authenticate with an API key to unlock all 61 tools and unlimited simulations.

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• search

  DC Hub — Data Center & Power Intelligence

  Search DC Hub for relevant records (OpenAI Deep Research / ChatGPT connector format). Returns a list of matching data-center facilities as {id, title, url}; pass an id to the `fetch` tool for the record, or open the url to cite the live facility page. For structured queries (by MW, operator, status, market) use search_facilities directly.

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• info_marketsnapshot_batch_market_snapshot

  Gate Info MCP

  Batch quotes up to 20 symbols; partial misses OK. One symbol→get_market_snapshot. Deep trend→markettrend_get_kline. Breadth→get_market_overview. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.

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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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• cincinnati_query

  Data Cincinnati

  Run a raw SoQL query against any Cincinnati open-data resource (data.cincinnati-oh.gov) by its Socrata id (8-char like "k59e-2pvf"). Full SoQL: where/select/group/order/limit/offset. Use cincinnati_datasets to find a resource id, or cincinnati_recent for the common ones.

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