Clay

Clay

Agent-callable tools for Clay, the spreadsheet-style go-to-market data platform. This connector gets structured data into Clay tables and reads specific rows back out: create and update rows, find rows by field value, list a view's rows, and navigate the workspace → table → view → record hierarchy so you can resolve the identifiers those writes need. A workspace holds tables, a table holds rows of typed cells, and views define which columns are visible. Authentication is a single long-lived Clay API key.

Independent, unofficial connector for Clay. Not affiliated with, endorsed by, or sponsored by Clay. "Clay" is a trademark of its owner, used only to identify the service this connector works with.

When to use this

• Write to a Clay table — add a new row (createRecord) or change cells on an existing one (updateRecord), e.g. push a lead or enrichment result into a table.
• Look a row up — find rows by matching field values (findRecord) or page through a view (listRecords), e.g. to get a recordId before updating.
• Resolve ids and schema — navigate workspaces, tables, views, and members (listWorkspaces, listTables, getTable, listWorkspaceUsers, getCurrentUser) to discover the tableId, viewId, field ids, select-option ids, and user ids that writes and filters require.
• Not for — building tables/views/columns, running enrichments on demand, or bulk export; those aren't exposed here.

Setup

This is an agentskills.io skill.

If the connector has not been installed as a skill yet, install it first with npx skills add zapier/connectors --skill clay (or your harness's own skill-install mechanism), then continue here. Installing the skill copies these files, not dependencies. Before running the CLI, a local MCP server, or zapier-sdk auth commands, run npm install --omit=dev here once. Importing the published package as a dependency in your own project instead? That npm install already resolves everything — see references/use-as-sdk.md.

Want the actual repo source instead — to browse references/, run this connector's tests, or hack on it? See README.md for a scoped git clone.

The connector runs on Node.js 22.18+. Pick the reference that matches how you're running it, and load it before doing anything else:

Scripts

All scripts use the single clay connection. Cell and filter values are keyed by field id (f_…); discover valid field ids, types, and select-option ids with getTable, and user ids with listWorkspaceUsers.

Disambiguation & refusals

• Before updating a row looked up by name, confirm the match. findRecord / listRecords can return several rows that share a value (e.g. two records with the same company or person name). Count exact (case-insensitive) matches on the field you searched: exactly one → act on it, don't over-ask; two or more that tie → stop, list the candidates with a distinguishing field (another cell value or the record id), and ask which one before calling updateRecord. Never silently pick the first.
  • Always re-resolve the row with a fresh findRecord at update time — never reuse a recordId you created or saw earlier in the conversation. A row you added moments ago may no longer be unique (another row with the same value may have been added since), so a stale id hides the ambiguity. Search by the named value again, then apply the count rule above before writing.
• Don't fake unsupported operations. This connector cannot create or delete tables, views, or columns, run an enrichment on demand, or delete rows — there is no tool for those. If asked, say it's unsupported and stop; do not substitute a different tool (e.g. writing a new row in place of deleting one) and report it as done.

Auth

Every shape passes auth as one connection selector, not the secret — a [<resolver>:]<value> string. Every connector accepts zapier:<connection-id> (Zapier-managed auth — routes through Zapier's auth, retries, and governance layer); some also accept one or more direct-token resolvers (naming and count vary per connector) — check this connector's own resolvers rather than assuming. The <resolver>: prefix is optional; a bare value goes to the first resolver that claims it — a UUID-shaped bare value always claims zapier:. Each script declares the connections it needs and the resolvers each accepts. The exact syntax for passing a connection (and how to see this connector's resolver list) differs by shape — see the reference you loaded above.

Checking what's already configured first? Don't dump environment values to do it — env or env | grep <name> prints the value along with the name, leaking a live credential into the transcript if one is set. Check names only (env | cut -d= -f1 | grep -i <name>) or test a known name directly ([ -n "$VAR_NAME" ]).

Zapier-managed auth is not yet verified for Clay — prefer the direct token (env:<ENV_VAR>) until it is confirmed.

No connection yet? Pick one — and follow the reference's own flow to obtain it; never just ask the user for a connection id or token as if they already have one memorized:

Output format

Every script returns a { data, meta } envelope:

• data — the script's result (the shape its outputSchema declares; see the reference you loaded above for how to inspect a script's exact schema in your shape).
• meta.outputDataValidation — what validating data did:
  • { skipped: false, droppedPaths: null } — validated, nothing removed.
  • { skipped: false, droppedPaths: [...], instruction } — validated, but those paths were stripped from data: fields the script returned from the API that the outputSchema doesn't declare. If you need them, re-run with output validation skipped.
  • { skipped: true } — validation was bypassed; data is the raw, unchecked script output.

Reading dropped fields / skipOutputDataValidation. To receive the raw, unvalidated result, opt out of output validation (the exact syntax differs by shape — see the reference you loaded above). Input validation is never skipped.

Trimming the result / filterOutputData. To shrink a large result down to the fields you need, pass a jq expression that post-processes data (again, exact syntax per shape). The jq runs against data only, NOT the { data, meta } envelope, so write it rooted at data (run the script's --help — or your shape's equivalent — to see its output schema). The transformed value replaces data, meta is preserved, and the result is NOT re-validated against the output schema.

References

Load the matching reference file before working in that area: