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Integrations

One card per source category, data flows in from anywhere.

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Accounting CRM HR and Payroll Payments Data

The Agentic Layer

The governed foundation — platform capabilities.

Unified Data Business Logic & Modeling AI Agents & Automation Security & Controls

Surfaces

The layer powers every surface — finance works wherever work happens.

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Cube web Excel & Google Sheets AI Assistants via MCP Slack & Teams PowerPoint & Google Slides BI Tools
Product Updates

Reporting & Analysis

Business performance tracking, variance, and analytical insight.

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Variance Analysis Ad-Hoc Reporting Executive Reporting

Planning & Modeling

A comprehensive look at forward-looking corporate financial strategy.

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Revenue Cash Flow Scenario Planning Headcount Vendor/Expense Annual Budgeting

Consolidation & Close

The entire financial close and data management cycle, at a high level.

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Data Consolidation Financial Close Data Governance & Audit

Industries

Purpose-built for how each sector runs finance.

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Software Business Services Healthcare Retail Financial Services Manufacturing Nonprofits Real Estate Multi-Location
For AI assistants

Cube MCP Server: every AI assistant, one governed source of financial truth.

Connect Claude, ChatGPT, Copilot, and Gemini to Cube in under a minute. Every answer is governed, permissioned, and traceable.

Get a demoTry it free
Your source systems
ERP & GL
CRM
HRIS & payroll
Data warehouse
A glass prism connecting AI assistants to Cube
Unify every source
Apply business logic
Enforce permissions
Audit-ready AI
MCP Server · governed context
Your AI assistants · read & write back
Claude ClaudeAnthropic
ChatGPT ChatGPTOpenAI
Copilot CopilotMicrosoft
Gemini GeminiGoogle
More assistantsAny MCP client
Write back from AI
See it work
Trust your AI’s answer, every time.
1Flows in from every system
ERP · GLQ3 operating expenses$1,214,380
CRMQ3 open pipeline$8.4M
HRISEngineering headcount142
WarehouseCloud usage, Sept$96,210
2Cube governs it
Mapped to your chart of accounts
Consolidated across entities
Your formulas and versions applied
User permissions enforced
Q3 opex vs. budget
+$86K
3Claude, connected to Cube
Why is Q3 opex over budget? Add the six new engineers to the reforecast.
Q3 opex is $86K over budget. 71% comes from six engineering hires that started a month early; cloud usage explains most of the rest. Traced to 14 GL transactions.
Written back to CubeQ3 Reforecast v4 · Engineering +6 · awaiting your approval
One governed model

Every source unified, mapped, and rolled up before any AI sees it.

Your business logic

Your chart of accounts, formulas, and versions. Not generic patterns.

Your permissions

Each user’s AI sees only what that user is allowed to see.

Trace to the source

Every answer drills back to the transaction, ready for the board.

Write back from your AI

Update forecasts and assumptions right from Claude or ChatGPT, with approvals and audit trail.

You’re not choosing between Cube and AI. Cube is what makes AI trustworthy for finance.
Connect your AI assistant
The problem

You live in your AI assistant. Your numbers still need a login.

Your assistant already reaches the rest of the stack through MCP. Finance is the holdout, so the work stops while someone goes and fetches a number.

A disconnected glass cable representing AI tools cut off from finance data
Problem 1
Your other tools already connect to AI

The CRM, the docs, the warehouse are all one prompt away. The finance question is the one that breaks the flow.

Scattered glass fragments representing copy-paste between spreadsheets
Problem 2
Pasting finance data into AI chats

Screenshots and CSV exports go into the chat, and the assistant answers from last Tuesday’s numbers.

A cracked glass panel representing unreliable AI answers
Problem 3
Pasted numbers are ungoverned

No permissions, no lineage, no audit trail. AI can be 80% right, and in finance that is 100% wrong.

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We asked Claude for our numbers. Only Claude + Cube got every one right.

We asked Claude 531 finance questions with exported spreadsheets, then again connected to Cube. On files, it got 65.7% right. In finance, 65% right is 100% wrong.

Read the full AI Accuracy study
Claude + exported files
65.7%
of figures correct
Claude + Cube
100%
of figures correct, every run
Pre-registered study · 2026
The Finance AI accuracy study
Glass report cover for the Cube accuracy study
Current-month actuals
Claude + exported files78.7%
Claude + Cube100%
Budget
Claude + exported files73.9%
Claude + Cube100%
Forecast
Claude + exported files44.4%
Claude + Cube100%
Why Cube

The MCP server for finance, not another connector.

Generic connectors return rows. Cube returns decision-ready answers from a governed financial model, with permissions and lineage enforced on every query.

A generic AI chat window without governed data
The alternative
Generic database or ERP MCPs

Hands your assistant raw tables. It doesn’t know what gross margin means in your model, which forecast version is current, or who can see exec comp.

Tangled glass connectors representing raw API connections
The alternative
Building AI on raw ERP APIs

Means rebuilding permissions, metric definitions, and audit logging yourself, then maintaining all three as your business changes.

A glass cube connecting AI assistants to one governed source
Cube MCP Server
Governed answers, out of the box

Your business logic, roll-ups, and permissions applied before the assistant sees a number. Every figure traces to the transaction.

Try it freeGet a demo

Make every AI tool in the company finance-literate.

Connect your assistant to a governed Cube model and drill every answer to the source.

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Common questions

Everything you need to know about the Cube MCP Server.

What is an MCP server for finance?

An MCP server for finance is a Model Context Protocol server that gives AI assistants governed access to your financial model, with permissions and transaction lineage enforced on every query. The answer comes from the same governed model Cube delivers everywhere your team works.

Which AI assistants work with the Cube MCP Server?

The Cube MCP Server works with Claude, ChatGPT, Copilot, Gemini, and any MCP-compatible assistant. The connection is OAuth-secured and takes under a minute, with no exports and no developer resources.

What is the best MCP server for financial data?

The best MCP server for financial data gives AI assistants governed, calculated numbers rather than raw ledger rows, respects each user’s permissions, and logs every read and write. The Cube MCP Server connects Claude, ChatGPT, Copilot, and Gemini to Cube’s governed financial context, so answers match the board deck and approved changes write back to Cube.

How do you connect Claude or ChatGPT to financial data securely?

Connect the assistant through an MCP server that enforces the same access controls, audit trail, and business rules as your finance system, instead of pasting exports into a chat. With Cube, users sign in with their own permissions, the assistant only sees what they can see, and every action is recorded in Cube’s SOC 1 and SOC 2 Type II audited platform. 

Can an AI assistant change my numbers?

Only if you allow it. Write-back requires a dedicated permission, Use MCP (Write), granted by your admins. Every change lands in the audit trail with before and after values.

Does the assistant see data the user can’t?

No. Access follows each user’s Cube permissions, down to the cell. An assistant acting for a VP sees that VP’s cost center; one acting for the CFO sees everything.

How is this different from pasting data into ChatGPT?

Cube gives the assistant live, governed data instead of a pasted copy. Pasted data is a stale copy with no permissions or lineage. Through Cube, the assistant reads live from your governed model, and every figure traces to the source transaction.

Can we build our own agents on Cube?

Yes. Any agent framework that speaks MCP can query the governed model, and custom agents inherit the same access controls, audit trail, and lineage as Cube’s FP&Agents.

Who can use the Cube MCP Server today?

All Cube customers can use the Cube MCP Server; it’s generally available today. Your admins control who can connect an assistant and who holds write access.

Still have questions? See it on your own numbers.
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Start here

What is MCP in finance?

MCP (Model Context Protocol) is an open standard that lets AI assistants connect to business systems through a common interface. Instead of copying data into a chat window, an assistant such as Claude, ChatGPT, Copilot, or Gemini requests the data it needs from an MCP server, and the server decides what it can see and do.

In FP&A, that means an assistant can answer questions on actuals, budgets, and forecasts, or write updates back to the plan, using the same governed model the finance team works in. Permissions, business rules, and the audit trail all come from the source system, not the chat.

Connect

One standard connection

Connect every MCP-compatible assistant once, instead of building and maintaining a separate integration for each AI tool.

Govern

Permissions carry over

Each user sees only the entities, accounts, and versions their Cube role allows, in every assistant.

Calculate

Figures of record

Answers come from Cube’s calculated model and business rules, so every assistant returns the same number.

Write back

Edits with approval

Assistants can propose plan and forecast updates that flow back to Cube for finance to review, with every change logged.

Why MCP matters for FP&A

AI assistants are already in use across most finance teams, often on exported spreadsheets that are out of date the moment they are downloaded and carry no permissions. MCP gives those assistants a governed path to live financial data. Finance keeps one source of truth, and the rest of the business gets answers in the tools they already use.

How to use MCP in FP&A

Rolling out MCP works best when the data foundation is already in place. A typical sequence:

  1. 1.
    Unify your financial data. Connect the GL, CRM, HRIS, and billing systems into one governed Cube model.
  2. 2.
    Set roles and permissions. Decide who can see which entities, departments, and plan versions.
  3. 3.
    Connect your assistants. Point Claude, ChatGPT, Copilot, Gemini, or another MCP client at the Cube MCP Server.
  4. 4.
    Start with read-only questions. Variance explanations, budget-to-actual checks, and KPI lookups are easy to verify.
  5. 5.
    Turn on write back. Let assistants submit forecast and plan changes for finance review and approval.

Key terms

MCP (Model Context Protocol)
An open protocol that standardizes how AI assistants request data and take actions in external systems.
MCP server
The service that exposes a system’s data and actions to AI assistants and enforces what each user can access.
MCP client
The AI assistant or app that connects to an MCP server, such as Claude, ChatGPT, Copilot, or Gemini.
Write back
An assistant sending an update, like a revised forecast, back into the source system rather than only reading from it.
Governed data
Financial data that is reconciled, calculated with agreed business rules, and protected by role-based permissions.
Audit trail
A log of every query, edit, and approval, showing who did what and when.

Spreadsheet uploads vs. MCP connected to Cube

Uploading files to AI Cube MCP Server
Freshness Stale the moment it is exported Live data synced from source systems
Permissions Anyone with the file sees everything Cube roles applied to every answer
Consistency Each assistant may calculate differently Same figure of record in every assistant
Write back Manual copy and paste Proposed changes flow to Cube for approval
Audit trail None Every query and edit logged
Setup Repeated for every file and tool Connect each assistant once