Connect your AI Agents to Clay in minutes

What is a Clay MCP?

It's an MCP server that lets your agents access data and functionality from Clay via tools. Your agents can invoke these tools to enrich a company or contact record, run a waterfall against multiple data providers, build a prospect list from structured search filters, kick off a batch enrichment routine, and more.

Clay offers an official MCP server, but you can also use one from a third-party platform, like Merge Agent Handler.

How can I use the Clay MCP server?

The use cases naturally depend on the agent you've built, but here are a few common ones:

• Automated lead enrichment: a new lead lands in Salesforce, and your agent triggers a Clay routine to enrich the record with firmographic and contact data, then writes the results back to the CRM field by field

• Waterfall cost monitoring: your agent checks the status of an in-flight enrichment waterfall, flags any provider that's burning credits without returning matches, and reports the outcome so ops can adjust the provider order

• Slack-triggered prospecting: a rep asks Claude in Slack to build a list of fintech accounts under 200 employees, and your agent runs a Clay search, pages through the results, and drops the matches into a table

• GTM data cross-referencing: your agent queries multiple Clay tables to reconcile enrichment results against a target account list before it hands qualified leads off to a scoring workflow

What are popular tools for Clay's MCP server?

Here are some of the most commonly used tools:

• execute_routine: runs a Clay routine against 1-100 items asynchronously. Useful for agents that need to kick off a multi-step enrichment or waterfall workflow without sitting in the Clay UI waiting on it

• create_search: builds a people or company search from structured filters like title, industry, or headcount. Use this when an agent needs to turn a plain-language request into a defined search against Clay's data

• run_search: executes a search created with create_search and pages through the matching records. Call this when an agent needs the actual list of people or companies back, not just a search definition

• query_tables: runs a structured query across up to five Clay tables on Enterprise workspaces. Good for workflows that need to cross-reference enrichment results stored across multiple tables before acting on them

• start_batch_run: kicks off a batch routine run against an uploaded JSONL file of input rows. Helpful when an agent needs to enrich or process a large list in one call instead of row by row

• get_routine_run: fetches the progress and results of a routine execution. Useful for agents that need to poll whether an enrichment job finished before consuming its output

What makes Merge Agent Handler's Clay MCP server better than alternative Clay MCP servers?

There are several reasons to use Merge Agent Handler's Clay MCP server over building or using an alternative:

• Enterprise-grade security and DLP: Merge Agent Handler includes built-in data loss prevention controls that let you block or redact sensitive fields before they reach an agent. For Clay, this means you can prevent enrichment API keys, contact emails and phone numbers, and company financial data from being exposed even when the agent has broad read access

• Managed authentication and credentials: Merge stores and refreshes Clay credentials on your behalf. You never expose raw API keys or OAuth tokens to an agent or manage token rotation manually

• Real-time observability and audit trail: every tool call made against Clay is logged with timestamp, tool name, input parameters, and response metadata. You can audit exactly what an agent read or wrote without instrumenting anything yourself

• Tool Packs and controlled access: bundle specific Clay tools with tools from other connectors into a single MCP endpoint, scoped to a specific use case. An agent gets exactly the tools it needs, nothing more

How can I start using Merge Agent Handler's Clay MCP server?

You can take the following steps:

1. Create or log into your Merge Agent Handler account.

2. Install the Merge CLI by running pipx install merge-api, then run merge configure to link the CLI to your Merge account and merge login to authenticate your session.

3. Register the Agent Handler MCP server with Claude Code by running claude mcp add --transport http agent-handler https://ah-api.merge.dev/mcp, then open Claude Code and run /mcp to confirm agent-handler appears with a connected status.

4. Select agent-handler from the MCP list. This opens a browser window where you select which integrations to authenticate. Choose Clay and complete the auth flow. Merge stores and manages the credentials going forward.

5. Open a Claude Code session and start querying Clay data directly. The first time you use a Clay tool, a Magic Link may appear to complete connector authentication.

If you want to connect Merge Agent Handler's Clay MCP with internal or customer-facing agentic products, you can follow the steps in our docs.

Can employees use Merge Agent Handler to connect their AI tools to Clay?

Yes, Agent Handler for Employees lets your employees connect Claude, ChatGPT, Microsoft Copilot, Cursor, and other MCP-compatible AI tools to Clay without bypassing IT governance.

IT can provision access by role or group via SCIM. A revenue operations analyst, for example, gets Clay access to run enrichment waterfalls, Salesforce to update account records, and Slack to notify the sales team; while a demand generation manager gets Clay access to build targeted prospect lists, HubSpot to sync campaign segments, and Google Sheets to track list coverage.

Every tool call an employee's AI makes to Clay is also inspected against your DLP rules and logged to a searchable audit trail, giving security teams full visibility into what data was accessed and by whom.