Crossbeam+dbt

Bring Crossbeam and dbt together in your AI tools

Crossbeam surfaces which partners share your accounts and where partner deals are opening and closing. dbt answers with governed metrics from your Semantic Layer, the numbers your data team already stands behind. One prompt, not two tools.

Run your first AI workflow across both tools

Start with a prompt that brings Crossbeam and dbt into the same conversation. Crossbeam brings the full partner picture: overlaps, performance, deal activity. dbt brings governed metrics from your Semantic Layer: revenue, retention, and usage measured one way, everywhere.

Account intelligence
CrossbeamPartner

Get trusted numbers on any shared account

Crossbeam shows which partners share the account, ranked by partner score, plus recent partner deals opened or closed won there. dbt queries your Semantic Layer for that account's governed metrics, so revenue and usage mean the same thing they do on your exec dashboard.

Example prompt
"Which partners share [Account] in Crossbeam, and what do our dbt Semantic Layer metrics show for [Account]'s revenue and usage this year?"
Pipeline generation
CrossbeamPartner

Build a partner-sourced target list ranked by governed metrics

Crossbeam finds the prospects that overlap a partner's customer list, segment by segment. dbt lists the metrics and dimensions your data team defined and ranks those accounts against them, so reps prioritize with numbers the whole company trusts.

Example prompt
"Pull our prospects that are [Partner] customers from Crossbeam, then rank them by [metric] from our dbt Semantic Layer."
Deal acceleration
CrossbeamPartner

Find slipping metrics and bring the right partner in

dbt queries your Semantic Layer for open opportunities where a governed usage or engagement metric is trending down. Crossbeam recommends partners on those accounts with recent wins, long-term relationships, or contacts you are missing.

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

Check partner attribution against your governed revenue metrics

Crossbeam reports each partner's overlap counts, open deals, win rate, and attributed revenue. dbt returns partner-sourced revenue and retention metrics from your Semantic Layer, so you confirm which partnerships move the number using the same definitions your finance team does.

Example prompt
"List our top 10 partners by attribution in Crossbeam, then query [partner-sourced revenue metric] and [retention metric] from our dbt Semantic Layer for those shared accounts."
Co-sell execution
CrossbeamPartner

Prep a co-sell push with contacts and metric history

Crossbeam returns the partner-shared contacts at the account, ranked by role signals like decision maker, economic buyer, and executive sponsor. dbt fills in your side of the story with the account's governed metrics, sliced by the dimensions your data team defined.

Example prompt
"Before my co-sell call on [Account] with [Partner], pull the partner-shared contacts from Crossbeam and query [Account]'s key metrics from our dbt Semantic Layer."

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
dbt

dbt

MCP

Governed metrics from your Semantic Layer: one definition of revenue, retention, and usage.

  • Query governed metrics from the dbt Semantic Layer, grouped and filtered by dimensions and entities your data team defined
  • List available metrics, dimensions, and saved queries, so you know what is answerable before you ask
  • Execute SQL on the dbt platform, or generate it from natural language with text_to_sql
  • Discover models, sources, lineage, model health, and exposures from dbt's metadata
  • dbt-hosted remote server over HTTP for data consumption, with OAuth or token 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

dbt

in the same prompt

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

dbt

. Product names are the property of their owners.