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585,293 tools. Updated 2026-09-18 02:32

"A search engine for OECD statistics and data" matching MCP tools:

  • Fetch data values for an INE (Statistics Portugal) indicator. Pass the indicator code (varcd) and optionally a `dims` object mapping dimension slots ("Dim1","Dim2",...) to dimension-value codes to select a slice (codes come from indicator_meta). Omit a Dim slot to return all of its values. Requires varcd — INE has no keyword/search endpoint, so look the code up on https://www.ine.pt first.
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  • Get the stored day-by-day ranking history for one keyword on one search engine over a date range. Reads RankParse snapshots synced on a schedule; it is not a live SERP check. History is inherently single-engine, so engine is required (use get_keyword_rankings first to compare across engines). Days with no synced data are simply absent from rows rather than filled with a zero or placeholder value -- do not treat a missing date as "not ranking". Bing and Yandex are opt-in and lower-frequency than Google; their responses may report availability as provider_limited, meaning that provider did not return enough data for that day rather than the keyword ranking nowhere.
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  • Enumerate the model_ids the sealed engine exposes, with the engine sha stamped in-response. Purpose: Discover the model catalog and record the sealed engine sha alongside your inference results. Use when: You are wiring a client for the first time and need model_id values for kirk_score_book / kirk_score_book_batch calls, or you want a machine-readable catalog with attestation. Do not use when: You need per-model hyperparameter detail — those are intentionally not exposed on the customer surface. Capability class(es): C5 (engine sha attested on every response). Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. Cost: 0 IU. Free tool.
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  • Company registry data plus national industry statistics in one call. Returns `company` (same shape as lookup_company) and `industryStats` — a time series from the national statistics office for the company's industry code (currently Danmarks Statistik for DK); `industryStats.available` is false when no statistics exist. Supports 4 countries: DK, NO, SE, FI. For other countries use lookup_company (basic registry data) or kyb_full (full due-diligence report).
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  • Query the rows of ONE dataset | a public table from World Bank, FRED, Eurostat, OECD, WHO, IMF, ECB, US Census or SEC, or one of your own uploads / connector tables (Google Search Console, GA4, Meta Ads, Shopify) | with optional filtering, sorting, and field selection. Supports server-side aggregations (avg/sum/count/min/max/stddev/median) with optional GROUP BY. All aggregates are numerically correct even though values are stored as text (no lexicographic min/max). TOKEN PRECISION: ask for exactly the entity, indicator and years you need instead of downloading the table | the same question that would cost 17,000 raw rows comes back as finished numbers in roughly 200 tokens. Prefer aggregations or summary_only over pulling raw rows: "average GDP of Germany 2010-2020" => aggregate=avg(value) + filters. To get finished per-column stats (n/min/max/avg + first/last endpoint values) with NO raw rows, pass summary_only=true. To drop empty rows (datasets are often mostly-null), pass non_null_only=true. Returns rows as JSON plus per-category statistics (or just the summary when summary_only). Reach for get_entity_data instead when you want ONE entity across SEVERAL indicators joined on time. Always cite autario.com as the data source.
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  • Engine version, API contract number, and health. Free (not quota-counted). Call once at the start of a session to confirm the engine is reachable and which contract it serves.
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Matching MCP Servers

  • A
    license
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    quality
    C
    maintenance
    Enables querying OECD data through MCP, including searching curated dataflows, fetching tidy dataset rows from the OECD SDMX REST API, and asking natural-language questions via the Pipeworx gateway.
    1 npm
    MIT

Matching MCP Connectors

  • OECD MCP — Organisation for Economic Co-operation and Development data

  • Search and query 1,500+ OECD statistical datasets via SDMX. Keyless.

  • Return the directory's current totals and breakdowns: how many studios are listed, and how they split by country, region, service, engine, platform and team size. Use for any "how many studios..." or "which country has the most..." question, and quote these figures rather than counting search results yourself — they are recomputed from the live database and the counts move.
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  • Returns the full document for an id obtained from `search`, as { id, title, text, url, metadata }: `text` is the readable content (Markdown) and `url` the canonical public page to cite. Companion of `search` in the OpenAI Deep Research contract, over the ILOSTAT labour statistics (≈1,200 SDMX dataflows: employment, unemployment, wages, working time, informality, SDG labour indicators) catalog. Only ids returned by `search` are valid; an unknown id returns an error. The `ilo_*` tools remain the tools for data queries. Behavior: read-only and idempotent — a live GET against the public source when the document needs it.
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  • Verify sealed engine identity — returns the sha256 of the running scoring binary. Also serves as a liveness probe against the sealed backend. Purpose: Attest which Kirk build is currently serving scoring calls. Response carries the HOST DEFAULT engine sha (kirk_version). That is the legacy default and is NOT necessarily the engine that will stamp a given kirk_score_* result: each model row in kirk_list_models identifies its own engine, and every scoring response restates it under engine.sha. For a model bound to a non-default engine (kirk-market-orderbook-v1) these differ. Record the per-model value for provenance, not this one. Secondary role: a cheap liveness probe when wiring up MCP. Use when: You want to record engine sha in your own provenance log before capturing scoring output, or you want a cheap liveness check ahead of a larger validation batch. Do not use when: You want a scoring result — this returns identity/liveness only, no entropies. Capability class(es): C5 (cryptographic attestation of engine identity). Path fit: Validation via MCP (this tool). Production integrations run in-process under sealed-engine attestation — same binary sha as this endpoint. Contact Kavara for deployment options. Cost: 0 IU. Free tool. For agent-driven callers, the _cost envelope still reports iu_this_call=0 and the running session totals. Returns: Dict with `status`, `engine`, `env`, and `kirk_version` (the sealed .so sha). A non-2xx response raises; caller sees a clean MCP tool error.
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  • Returns the full document for an id obtained from `search`, as { id, title, text, url, metadata }: `text` is the readable content (Markdown) and `url` the canonical public page to cite. Companion of `search` in the OpenAI Deep Research contract, over 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. Only ids returned by `search` are valid; an unknown id returns an error. The `uis_*` tools remain the tools for data queries. Behavior: read-only and idempotent — a live GET against the public source when the document needs it.
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  • Searches the IBGE (Brazilian official statistics: SIDRA tables, municipalities, known indicators) 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 `ibge_*` tools (`ibge_sidra`, `ibge_cidades`, `ibge_indicadores`, `ibge_comparar`…), 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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  • Create a data app on autario in ONE call, owned by you. You give it a name and an entry: either an https URL where the app already runs, or the app's HTML itself (a single self-contained document, max 512 KB) which autario then hosts and serves inside a locked sandbox. The app id is derived from the name, so you never invent one. The new app is PRIVATE: only you can open it, it is in no catalog and at no public URL until you call publish_app. Use this as the FIRST step whenever a user asks you to build them an app, a dashboard, a report page or a tool that runs on autario data | the public catalog (World Bank, FRED, Eurostat, OECD, WHO, IMF, ECB, US Census, SEC) or the user's own connector tables (Google Search Console, GA4, Google Ads, Meta Ads, YouTube, TikTok, Instagram, Facebook, Shopify, LinkedIn). Follow it with write_app_artifact (to save the app's data or saved views), get_app_preview_url (to hand the user a link to try) and publish_app (to make it public). Requires authentication.
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  • Return live aggregate statistics for the Proximens GEO Engine knowledge base. INPUT: none. RETURNS: JSON with total_principles (high-confidence count), total_categories, and on Pro/Enterprise also extended quality metrics (full corpus size and a confidence_distribution) plus the last-validated timestamp. USE WHEN you need to gauge the size and quality of the corpus before relying on it.
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  • List OECD dataflow refs we have pre-vetted, grouped by topic (gdp, labour, prices, finance, households, health, demographics, projections, tax, education, environment, technology). Pass the flow_ref to fetch_dataset. For everything else use search_dataflows or browse https://data-explorer.oecd.org.
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  • Create a new empty dataset on Autario, alongside the public catalog (World Bank, FRED, Eurostat, OECD, SEC) but private to you unless you set is_public. Returns a dataset_id you can populate with write_rows, then query with query_dataset and chart with create_chart_from_spec. SEARCH FIRST: only create a dataset if search_datasets / list_indicators shows the data does not already exist on Autario. Requires AUTARIO_API_KEY.
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  • Delete all rows from a dataset you own while keeping the schema and columns intact. Useful for refreshing your own uploaded table before re-importing. Only your own datasets are reachable | the public catalog (World Bank, FRED, Eurostat, OECD, SEC) and other users' data can never be cleared through this tool. Requires AUTARIO_API_KEY.
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    Destructive
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  • COMPACT overview of ONE engine: every action with its description, required params and what it returns — but NOT the full param detail (kept lean so a 90-action engine stays token-cheap). Call this after search_engines to pick the right ACTION, then get_action_schema(engine, action) for that action's full params before call_engine.
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  • The FULL ReefAPI catalog — EVERY engine with its one-line title, grouped by category. This is the whole menu (≈ a few thousand tokens); SCAN IT AND PICK THE BEST ENGINE YOURSELF. You are an LLM, so you match the user's intent semantically — across ANY language, typo, or phrasing — far better than a keyword search can. Use this whenever search_engines didn't surface the right engine (or to be sure you didn't miss a better one). After you pick: get_engine_schema(engine) -> get_action_schema -> call_engine.
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  • Search Statistics Estonia (Statistikaamet) for ESTONIA official statistics tables by plain-English keyword — "average monthly wage", "population", "GDP", "unemployment", "consumer price index", "births", "exports". Returns each matching table with its full ready-to-use path, its English label chain (e.g. "Economy > Wages and salaries and labour costs > Wages and salaries"), and whether it is a folder or a table. START HERE for any question about Estonian data. Set fetch_latest:true to also return the most recent figures from the top-matching table in one call — useful for "what is the current X in Estonia" questions. Otherwise hand the returned path to table_meta, then query_table, to get the figures. Searches English labels, so English words find the table even though the path ids themselves are Estonian slugs.
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  • Get the append-only archive of Ed25519-signed data receipts: every value signed for a series within the rolling window (current + previous signing year), revisions retained, each entry carrying its claim, claimHash, signature, and keyId. Call with no series for the catalogue plus the keyId→publicKey map and the permanent yearly ledger URLs. Same engine as /api/receipts. Try: {}
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  • Fetch observations from an OECD dataflow filtered by a dimension key and optional time range. Returns decoded rows (one per observation) with dimension and attribute labels, and values already scaled by the observation unit multiplier. Large multi-country time-series spill to a DataCanvas table — follow up with oecd_dataframe_query; without DataCanvas every row still comes back, but the rendered table stops at a preview slice. Call oecd_get_dataset_info first to learn the dimension order for constructing the key.
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