Mostly Right

Full-text search over every public dataset on Mostly Right. No account needed. Example: {"query": "hourly airport weather observations", "limit": 10}. Returns {datasets: [{id, slug, title, summary, topics, publisher, published_at, canonical_url}], next_cursor}. publisher is the ACCOUNT that published the dataset here, never the organisation that publishes the data it was built from — those are named on the dataset page as its sources. Pass next_cursor back as `cursor` for the next page; a null next_cursor means there are no more. Omit `query` to list the most recently published datasets. Follow up with get_dataset(slug) for tables and schemas.

One dataset's overview: title, summary, topics, publisher, publication and update dates, canonical page URL, star and table counts, and every table with its id, title, license, immutable version_id, column count, column names and the capabilities the publisher enabled. Here and everywhere in this tool, publisher means the ACCOUNT that published the dataset — not the organisation the data was gathered from, which is a source's own publisher. Example: {"slug": "kden-metar-hourly"}. Column types, descriptions, units and published profiles are NOT here — call get_table_schema for one table when you need them. Use the returned table `id` (a UUID) with get_table_schema, sample_rows and query_table. Cite the dataset by canonical_url and the table by version_id.

The tables in one dataset, without the full column schemas — the cheap call when you only need table ids and titles. Example: {"dataset_slug": "kden-metar-hourly"}. Returns {dataset_slug, tables: [{id, slug, title, license, version_id, capabilities}]}. Use get_dataset instead when you also want columns.

One table's columns (name, type, and any published profile such as null counts, distinct counts or ranges), its immutable version_id, and its capabilities: whether anonymous sampling, keyed querying and Parquet download are enabled. Example: {"table_id": "0f2f6bfa-4a63-4f75-9a0b-1a7d9c5b2e10"}. Read this before writing a query_table call: the column names it lists are the only ones the query grammar accepts.

The publisher's materialized preview of a table — real rows, no account, no query cost. 20 rows by default, 100 at most, and they are always the same rows: this is a sample for understanding shape and values, NOT a query. Example: {"table_id": "0f2f6bfa-4a63-4f75-9a0b-1a7d9c5b2e10", "limit": 20}. Returns {table, columns, rows, row_count, total_row_count, sample_truncated} — total_row_count is how many rows the whole table holds, which is usually far more than the sample. To filter, sort, aggregate or read beyond the sample, use query_table, which needs a workspace key.

The exact URL, HTTP method and header for downloading one table's current immutable Parquet snapshot, plus whether the publisher enabled it. Example: {"table_id": "0f2f6bfa-4a63-4f75-9a0b-1a7d9c5b2e10"}. Bytes are never streamed through MCP: this returns the request to make yourself. Downloading needs an mr_use_ workspace key; the result includes how to get one. Prefer this over paging a whole table through query_table.

What this server does anonymously, what needs an account, the two API key classes and what each unlocks, the OAuth option, the signup URL, and the numbered steps from 'no account' to 'querying rows'. Optionally pass {"dataset_slug": "kden-metar-hourly"} to get the link to that dataset's page, which is where a key is minted. Call this whenever a tool refuses for want of authentication, or before telling a user they need to sign up.

Search every public dataset on Mostly Right and return up to 20 matches as {results: [{id, title, url}]}, where `id` is the dataset slug and `url` its canonical page. No account needed. Example: {"query": "hourly airport weather observations"}. Pass a result's `id` straight to fetch for the full dataset document. This is the plain search-and-fetch pair; search_datasets is the richer, paged version with topics, publishers and summaries.

The full public document for one dataset as Markdown: summary, facts, access instructions, and every table with its columns, types, descriptions and units. No account needed. Example: {"id": "kden-metar-hourly"} — the `id` is a slug from search, and a canonical dataset URL works too. Returns {id, title, text, url, metadata: {slug, publisher, published_at, table_count, topics}}. publisher is the account that published the dataset, not the source it was gathered from. Cite the dataset by `url`. For machine-readable table ids and schemas, call get_dataset and get_table_schema instead.

A bounded, structured query over one table's current version. NO SQL: send columns, filters, order_by, aggregates and limit as JSON. Example: {"table_id": "0f2f...", "columns": ["observed_at", "air_temp_f"], "filters": [{"column": "air_temp_f", "operator": "gte", "value": 80}], "order_by": [{"column": "observed_at", "direction": "desc"}], "limit": 50}. Ceilings: 20 columns, 8 filters, 2 sort keys, 4 aggregates, 10000 rows a page (25 when limit is omitted), 8 MiB of JSON. Every page answers with next_cursor; send it back as cursor (same columns, filters and order_by) for the next page until it is null, and you have read the whole table on one immutable version. Operators: eq, neq, in, gt, gte, lt, lte, is_null, is_not_null. Requires an mr_use_ workspace key (Authorization: Bearer) or an OAu

Search a sealed snapshot of public data sources for feeds that might answer a question — the first move when you need a source and do not already know one. Example: {"question": "county unemployment rate monthly", "limit": 10, "format": "csv"}. READ THIS BEFORE YOU TRUST A RESULT. The snapshot indexes ONE provider, Data.gov, and only part of it: about 22,000 records were catalogued out of the ~550,000 Data.gov lists, and only about a thousand of those record which data formats they publish. So a miss is NOT evidence that no such source exists — go and look yourself — and a hit is a lead to open and read, never a source anyone has verified. Returns {status, question, requirement, generation, candidates, work}. `generation` says which sealed snapshot answered and when it was published; cite