B2B data for AI agents

An AI agent that prospects, researches or enriches needs a data source it can call on its own. This page explains which B2B data providers have an MCP server, how to connect one to Claude, ChatGPT or an agent you build, and what to check before you let it run. Lusha’s own figures are included with their source.

Last updated: October 2026

What agents need from data

What is the data layer for AI sales agents?

The data layer is the source an agent calls when it needs a fact it cannot reason its way to: who works where, how to reach them, and whether anything changed. A language model knows how to write an email. It does not know that the VP of Sales at a company you are targeting left last month.

An agent doing sales work needs three kinds of data from that layer:

• Identity. The right person and company, with current title and firmographics.
• Reachability. A verified work email and phone number, so the next step can actually happen.
• Timing. Dated events such as a funding round, a hiring surge or a job change, so the agent knows who to contact now rather than ever.

It also needs two things a human user handles without noticing: a way to see whether a record exists before paying for it, and data fresh enough that a loop running every day does not act on last year’s org chart.

MCP servers

Which data providers have an MCP server?

An MCP server lets an AI client call a provider’s data directly, using the Model Context Protocol. As of October 2026, thirteen B2B data providers document a first-party server: Lusha, Apollo, ZoomInfo, Clay, Crunchbase, Hunter, 6sense, Explorium, Crustdata, LeadIQ, FullEnrich, Coresignal and Lead411. Four widely used providers do not document one: Cognism, People Data Labs, Kaspr and UpLead.

They differ in what they expose and whether they can act:

The full list of seventeen vendors, with endpoints, clients, plan gates and sources, is in Which B2B data providers have an MCP server?

What is the best MCP server for sales data?

There is no single best one, because the right choice depends on what your agent does. Check five things:

• First-party or community. A community server built on a public API breaks when the API changes and nobody owns the fix.
• What it exposes. Contacts only, or companies and dated signals too. Signals are rare in MCP responses.
• Read-only or write-back. Decide whether the agent should be able to act, or only research and draft.
• Where it is listed. A server in the Claude or ChatGPT directory installs with a sign-in. A bare endpoint needs a key and setup.
• Which plan unlocks it. Some servers need a paid or contract plan; others work on a free tier.

How to connect

How do I connect a B2B database to an AI agent?

There are three routes, and which one to use depends on where the agent runs:

• A directory connector. In Claude or ChatGPT, add the provider from the connector or app directory and sign in. No key, no code. Use this for agents that live inside an assistant.
• A remote MCP endpoint. In Cursor, VS Code, Gemini CLI, n8n or your own client, add the provider’s endpoint with an API key. Use this when you control the client.
• The API. Call the provider’s REST endpoints from your own code. Use this for scheduled jobs and pipelines that do not need a model to decide which call to make.

Whichever route you take, test it with one real question before you build around it, such as “which of my target accounts raised funding this quarter, and who runs sales there?”

What is the difference between an MCP server and an API?

An API is a set of endpoints your code calls. An MCP server wraps those capabilities as named tools a model can choose between from a plain-language request. Use the API when you know exactly which call to make and when. Use MCP when you want the model to decide.

How do I use B2B data for AI agents in HubSpot and Salesforce?

Keep the two jobs separate. The data provider supplies the record; the CRM stores it. An agent can do both through two connectors, one for each, or you can let a native integration enrich the CRM on a schedule and have the agent read from the CRM. The second is easier to audit, because every write goes through one integration with its own rules about what it may overwrite.

Which data enrichment MCP works with Clay and n8n?

Clay works as an orchestration layer that pulls from many providers, so the question is whether your provider is one of its sources. n8n and Make connect to any provider with an MCP endpoint or an API, so check for one or the other.

Claude and ChatGPT

What is the best B2B data provider for Claude?

Start with what is listed in Claude’s own connector directory, because those install with a sign-in and have been reviewed. Then check three things: whether the connector returns verified contact details or only company data, whether it shows what exists before charging, and whether a plugin adds ready-made workflows on top. For Claude Code, check that the provider publishes a remote endpoint you can add with a key.

What is the best B2B data connector for ChatGPT?

The same checks apply. Look for providers in ChatGPT’s app directory first, since those connect with a sign-in. Then check what the app can return, whether it can save results somewhere you can use them, and which of your plans it needs.

Before you build

What can an agent do with B2B data, and what can it not?

Read the provider’s tool list before you design the workflow. Some servers only read, some write to their own tables, and a few add contacts to sequences or send email. An agent that can send needs guardrails that one which only researches does not.

Which tools help AI agents find verified emails?

An agent cannot tell a verified email from a guessed one unless the provider says which it is. Choose a source that returns verification status with the record, and that lets the agent check whether an email exists before paying for it. Otherwise a loop over a thousand contacts spends credits on empty records. How verification works across the category is covered in the B2B data accuracy FAQ.

How much does it cost to run an agent on B2B data?

Agents loop, so the price of a single lookup matters less than the price of a run. Check whether searches cost anything, whether a miss is charged, and whether the agent can read its own balance before it starts. Then cost one realistic run by hand before you schedule it.

Can I use B2B data to train an AI model?

Usually not. B2B data licences typically allow use within your own workflows and prohibit training, resale and embedding in another product. Read the terms before you design a system that stores and reuses what an agent retrieves.

Check it yourself

• MCP documentation for setup, tools and connection methods
• Tools reference for the current tool list
• OpenAPI spec for the API
• Lusha facts for AI assistants for one dated set of figures
• Campus plays and Skills for workflows you can run today