The Context MCP

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How it works

Context API in three steps.

One sentence framing the simplicity and speed of the workflow.

Unify your revenue data into one layer.

Loop reads CRM, call transcripts, emails,calendars, Slack messages, and more to trace thepath each deal takes. Alongside your salesprocess, territories, operating rules, and reppatterns. All joined to the revenue outcome.

Add the judgment a context graphcan't create.

A private ML model trained on your outcomes attributes the impact that champions, compellingevents, comparable cohorts, and deal trajectoriesall create. Not just the relationships they hold, likea Notion or Glean.

Deliver that context to your agents andreps in one MCP call.

Any agent that speaks MCP pulls the sameenriched context — no DIY servers to keep alive— and it stays put when you swap models orvendors.

Customer outcomes

Teams that ship Context API see compounding results.

—70%

token reduction

3.5x

Close rate, ml-promoted

-7d

cycle compression

"We finally have a straight line from an agent's action to the deal it moved. That conversation with our CRO went very differently this quarter."

GTM AI Lead

Defensestorm

How it compares

Fluint vs. Context Graphs &
Search. Why resolving context
isn't enough.

A graph carries your context. Fluint's model gives it judgment. Resolving relationships is table stakes. Predicting and compounding isn't.

What matters

Fluint Recommended

Context graphs & search

e.g. glean, notion ai

Revenue judgement

Deal dimensions with revenue impact isolated & labeled

Map connections

Improves over time

Yes, closed loop retrains on the outcome

Re-curated when relationships change

Carries process & rules

Yes, into every workflow

Varies, mostly entities

Delivery & upkeep

One MCP call, fully managed

MCP, with DIY inputs to maintain

Model-agnostic

Yes, outlives any one model

Usually

Questions about AI
for RevOps.

Fundamentals

What is AI for RevOps?

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How do I measure whether AI agents impact revenue?

Is my revenue data private?

Context & Cost

How does a context layer reduce AI token spend?

What is MCP and why does it matter for revenue teams

Can I buy a fully managed AI sales agent instead of building one?

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