Crossbeam+Fivetran Agent Context

Bring Crossbeam and Fivetran together in your AI tools

Crossbeam surfaces which partners share your accounts and where partner deals are opening and closing. Fivetran answers from your context layer: governed warehouse data, business concepts, and the metric definitions your data team certified. One prompt, not two tools.

Run your first AI workflow across both tools

Start with a prompt that brings Crossbeam and Fivetran into the same conversation. Crossbeam brings the full partner picture: overlaps, performance, deal activity. Fivetran brings your context layer: the warehouse tables, business concepts, and certified metrics your company already trusts.

Account intelligence
CrossbeamPartner

Get the partner and warehouse view of any account

Crossbeam ranks the partners on the account by partner score, win rate, and attributed revenue, and shows recent partner deals opened or closed won there. Fivetran runs an AISQL query on your context layer to return the revenue and usage your warehouse holds on that account.

Example prompt
"Rank the partners on [Account] by partner score in Crossbeam, then query our context layer for [Account]'s revenue and product usage this year."
Pipeline generation
CrossbeamPartner

Build a target list your own metrics back up

Crossbeam finds the prospects you share with a partner, filtered by segment: customers, open opportunities, prospects. Fivetran ranks that list with AISQL against the fit and usage tables in your warehouse catalog, so reps start where your own numbers point.

Example prompt
"Pull our prospects that are [Partner] customers from Crossbeam, then rank them by [metric] from the tables in our warehouse catalog."
Deal acceleration
CrossbeamPartner

Catch a usage drop and bring the right partner in

Fivetran queries your warehouse for open deals where usage has slipped, using the metric definitions in your context layer. Crossbeam recommends partners on those accounts backed by signals like recent wins, long-term relationships, and missing contacts.

Example prompt
"Query our context layer for open opportunities where [usage metric] fell this quarter, then ask Crossbeam which partners have recent wins at those accounts."
Ecosystem building
CrossbeamPartner

Confirm partner impact with certified metrics

Crossbeam reports each partner's overlap counts, open deals, win rate, and attributed revenue. Fivetran checks the same accounts against the business concepts and metrics your data team defined, so partner revenue claims match the numbers your company runs on.

Example prompt
"List our top 10 partners by attribution in Crossbeam, then compare their shared accounts against our [revenue metric] as defined in our context layer."
Co-sell execution
CrossbeamPartner

Prep a co-sell conversation with contacts and history

Crossbeam returns the partner-shared contacts at the account, ranked by role signals like decision maker, economic buyer, and executive sponsor. Fivetran's source search pulls the account's recent history from connected systems like Salesforce and Zendesk to round out your side of the story.

Example prompt
"Before my co-sell call on [Account] with [Partner], pull the partner-shared contacts from Crossbeam and search our connected sources for recent activity on the account."

What each MCP server does before you pair them

Crossbeam

Crossbeam MCP

Your partner relationships and deal activity.

  • Every account a specific partner has a relationship with, and how strong it is
  • Whether a partner recently opened, closed, or won a deal on an account
  • Contacts a partner has shared, ranked by role: decision maker, economic buyer, executive sponsor, and more
  • Partners who fit your ecosystem based on shared accounts
  • Read-only: nothing here writes back to your CRM or to Crossbeam
Fivetran Agent Context

Fivetran Agent Context

MCP

Your context layer: governed warehouse data, business concepts, and certified metric definitions on demand.

  • Run AISQL queries on your warehouse catalog, with semantic_relevance for meaning-based search over columns
  • Search catalog tables by business intent and discover the business concepts and metrics your data team defined
  • Deep dive on any table: metadata, columns, and human-authored schema instructions
  • Search connected source systems like Salesforce, Notion, Zendesk, and Jira
  • Public Preview, hosted by Fivetran, with user accounts or system keys for authentication

Works with your stack

Crossbeam plugs into the AI tools and GTM systems your team already runs: query it from any MCP client, or sync ecosystem data straight into your stack.

Gemini

Bring Crossbeam ecosystem data into Gemini over MCP.

Perplexity

Answer account questions with Crossbeam data in Perplexity.

HubSpot

Enrich HubSpot records with partner overlap and signals.

Sync co-sell overlap onto your Salesforce accounts.

Crossbeam
Slack

Get partner and deal signals delivered in Slack.

Snowflake

Pipe Crossbeam ecosystem data into Snowflake.

Cursor

Pull partner and account context into Cursor.

Mistral

Feed your partner ecosystem graph to Mistral agents.

Connect any MCP-compatible AI tool

Using another AI tool or custom solution that supports MCP connections? Our documentation walks through custom connector setup.

Read documentation

Crossbeam MCP is currently in early access for customers on Supernode and Enterprise plans.

Talk to our team

Frequently asked questions

Crossbeam MCP is in Limited Availability and is enabled by default for customers on Supernode and Enterprise plans. Connect it at mcp.crossbeam.com/mcp using OAuth with your Crossbeam credentials, and SAML SSO is supported. Not on one of those plans? Talk to our team.
There are native connectors for Claude, ChatGPT, and Glean, plus documented setups for Gong Agent Studio and custom connections like n8n, Microsoft Copilot, and LibreChat. Claude, ChatGPT, and Glean also support the partner tool's connector, so both servers run in one chat with no bridging work.
No. Crossbeam MCP is read-only: it reads ecosystem intelligence and returns it to your AI client. It can generate a shareable list link so you can jump into the UI, but no documented tool changes data in Crossbeam.
Use MCP when a person or an agent is asking questions in natural language and needs ecosystem context in the moment. Use the REST API for programmatic reads on your own schedule, and Webhooks when you want Crossbeam to push events to you as they happen. Most teams end up using more than one.
Your overlaps with one partner or across the whole ecosystem, a unified view of a single account with population membership and owner, partner health metrics like overlap counts, open deals, win rate and recency, ranked partner recommendations on an open opportunity, and recent ecosystem activity including partner deals opened, closed won, and greenfield signals. Access is scoped to your own Crossbeam permissions.
No. In supported clients it's a connector plus an OAuth login, with no code, no API keys, and no local install. The partner tool is added the same way, from your client's connector settings.
AI Chat lives inside Crossbeam and answers questions about your ecosystem there. MCP brings that same intelligence into the AI tool you already work in, alongside your other connectors. That's what makes pairings like this one possible in a single prompt.

Run Crossbeam and

Fivetran Agent Context

in the same prompt

Crossbeam MCP is currently in early access for customers on Supernode and Enterprise plans. Crossbeam is not affiliated with

Fivetran Agent Context

. Product names are the property of their owners.