The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Dataset Join & Merge listing page.
Join two lists of JSON rows on a shared key, like a SQL join or a spreadsheet VLOOKUP, in a single tool call. Hand it a main list and a lookup list, name the key, pick a join type, and it hands back one combined list plus an exact account of how many rows matched on each side and why the rest did not.
Built for AI agents. No install, no API key, no signup. Connect by URL and call it.
Free to use while in early access.
left keeps every left row and adds the matching right fields (the VLOOKUP and enrichment case, and the default). inner keeps only the overlap. right keeps every right row. full keeps everything from both sides. leftAnti returns left rows with no match on the right ("which of these leads are not in the CRM yet?"). rightAnti is the reverse. union stacks both lists, no key needed.123 matches "123", so " Ana@Example.com" from a scraper finds "ana@example.com" in a billing export. Set keyMatching to exact for strict matching.email on the left, contact_email on the right. Composite keys work too: ["firstName", "lastName"].right_status), keep the left value, or overwrite with the right value.multipleMatches: "all" returns one row per matching pair; "first" uses only the first matching right row, so each left row appears once.It is honest about what it could not match. Every row is tagged _joinStatus (matched, left_only, right_only) and _matchCount, and the summary reports match rates plus warnings for rows missing the key, duplicate keys on the right and key fields that exist on no row at all (usually a typo).
| Tool | What it does |
|---|---|
list_capabilities | Lists every join type, matching mode, conflict strategy and duplicate-key mode, the fields added to each row, and the row limits. Processes no data. |
join_rows | Joins leftRows and rightRows on the key fields you name and returns the joined rows plus a summary. |
Claude Code
Claude Desktop / claude.ai: Settings, Connectors, Add custom connector, paste the URL above.
Cursor, Windsurf, VS Code and other MCP clients
Four scraped leads on the left, three billing records on the right. The emails differ in case and spacing, and the key has a different name on each side:
Every lead comes back, the two customers enriched with their plan, and both status fields kept:
Change joinType to leftAnti and the same call returns only Cara and Dev, the leads with no billing record.
leftRows and rightRows together. For a left, inner or leftAnti join on bigger lists, split leftRows across several calls and send the same rightRows with each.multipleMatches set to all) can return more rows than went in. That call is refused with the predicted row count and what to change, never cut short: multipleMatches: "first" always fits.Anything over a limit returns a clear message rather than failing silently.
Your rows are processed in memory and never stored. To see which tools get used, each call records the tool name, row counts, whether it succeeded, the client name your app reports, the country and a one-way hashed caller ID. Your data, your arguments and your IP address are never kept in that log.
The same engine runs on the Apify Store as Dataset Join & Merge, which also reads Apify datasets, CSV, Excel and JSON files and Google Sheets by URL on either side, handles up to 100,000 rows per side, exports the result as CSV or Excel, appends it to a named dataset that builds up across runs, and can POST it to a webhook.
Built by Nero Labs.