If your financial analysis in Claude or ChatGPT starts with an export from your accounting or planning software, this routine should feel familiar.
You pull the latest numbers, upload the file to the AI tool, and ask it to build a report or answer a question. When those numbers change, you have to repeat the process.
This approach may work for one-off requests, but preparing the data for AI to make sense of it eats into the time you have for analysis. Plus, it creates copies of sensitive financial information in your AI tools, where your finance software’s access rules don’t automatically apply.
With AI use spreading faster than company policies can keep up, finance leaders are feeling the pressure. In Deloitte’s Q2 2026 CFO Signals survey, 59% of CFOs said their biggest AI governance challenge was moving fast enough to adopt AI while keeping the risks under control.
An MCP (Model Context Protocol) connection helps with both problems. Your AI tool requests up-to-date data from your finance and accounting software, so you don’t have to export and upload files. The right connector also respects your existing permissions. Each user only gets access to the data they’re allowed to see.
In this guide, we’ll compare the main ways of getting financial data into AI tools, then walk you through connecting Claude and ChatGPT to Vena using our MCP connection. We also share real examples of how finance teams use Vena MCP across different workflows.
There are four common ways to get your financial data into an AI tool to support everyday work like building reports and dashboards or creating a deck for leadership.
The right choice depends on what you need to do, where you prefer to work and which AI tools your FP&A team already uses.
|
Option |
How it Works |
Pros |
Cons |
|
Upload a CSV or spreadsheet |
Export your numbers and upload the file to your AI tool. |
Quick to start with tools that support file uploads. Useful for one-off questions. |
You may need to clean up the file so the AI can interpret it correctly, which takes time. |
|
Use AI in Excel with connected data |
Work with AI in a workbook connected to your finance software through an add-in. |
Stay in Excel to analyze numbers, fix formulas and build models. Refresh the workbook when you need updated figures. |
Without a separate connection, the AI only works with the data available in the workbook. |
|
Connect through an MCP |
Let your AI tool request data from your finance software as you ask questions. |
Get current figures without repeated uploads. Connectors like Vena MCP also respect your existing permissions. |
Setup may need admin help. The data and actions available depend on the connector. |
|
Use AI built into your finance software |
Ask questions and run analysis inside your finance platform. |
Tools like Vena AI work with your financial data without a separate MCP connection. |
Available tasks, flexibility and setup requirements vary by platform. |
Each option has its place, but if your team already works in Claude or ChatGPT, an MCP removes the export step without moving you to a new tool.
An MCP is a shared set of rules that lets AI tools connect to other software and request data. Think of it as a universal plug.
Once your AI tool is connected to your FP&A software, for instance, you can ask a question like “How much did Sales spend on travel in April 2026?”.
The numbers come from your connected finance software, rather than a file you exported earlier that has now become outdated.
To show you how to connect your data to an AI tool via an MCP, we’ll use Vena’s MCP as an example. It lets your AI tools retrieve actuals, budgets, forecasts and transaction details from Vena for analysis.
You can ask questions in Claude or ChatGPT in your browser, or use Claude directly in Excel, PowerPoint or Word. Use these five steps to speed up analysis and advise business units with today’s numbers.
Before you start, make sure you have:
You don’t need access to every department’s or entity’s data. Your existing Vena permissions determine what Claude or ChatGPT can retrieve. For example, if you only have access to one entity’s data in Vena, that’s all the AI tool will pull and analyze.
If your organization uses single sign-on (SSO), you’ll need a separate Vena password or an application token to sign in through an MCP. If Force SSO is turned on the MCP connection won’t work, so ask your Vena admin about your options.
The MCP server URL tells your AI tool where to request your Vena data. A Vena admin can find it by following these steps:
Always use the URL shown on the Model Context Protocol page in your Vena account, as it’s specific to your Vena region. Using the wrong region’s URL is the most common reason your login works in Vena but fails through an MCP.
If your AI tool supports Skills, select Download Bundle on the same page to save the Skills Bundle. You’ll need it for Step 4 below.
After an admin sets up the connector, each user can sign in with their own Vena account. Then follow the instructions for your chosen AI tool.
Open Claude in your browser and select your profile icon. Go to Organization Settings > Connectors, then select Add > Custom > Web.
Give the connector a name and paste the URL from Step 2 into “Remote MCP server URL.” Leave Advanced settings empty and select Add.
Next, your Claude organization owner needs to allow Claude to reach Vena.
In Settings > Capabilities, turn on both of these options:
Under Domain allow list, choose the appropriate access level. Then enter *.vena.io under Additional Allowed Domains.
To connect your Vena account, open Customize > Connectors in Claude and select the + icon. Find the Vena connector, select Connect, and sign in with your Vena login details. Start a new chat and open Connectors to make sure Vena is active.
Open ChatGPT in your browser and go to Workspace Settings > Apps. Select Create, give the connector a name, and paste the URL from Step 2.
Under Authentication, select OAuth. Check the box next to “I understand and want to continue,” then select Create.
Next, go to Workspace settings > Apps > Drafts.
Find the Vena app and select Publish. If the app doesn’t appear, refresh the page. Review and authorize the app if prompted, then finish publishing.
After the connector is published, connect your own Vena account.
Start a new chat and select Add Files & More > More, then choose the Vena connector. When ChatGPT asks you to connect, sign in with your Vena login details.
To check that the connection works, ask Claude or ChatGPT to “List my Vena models.” You should see the models you’re allowed to access in Vena. If the settings in your AI tool look different than the steps above, check Vena’s setup guide for connecting external AI systems. The guide also covers how to connect Microsoft Copilot and Perplexity.
Your AI tool can pull numbers from Vena, but it needs to understand what those numbers mean for your business.
To give it that context in Claude, add the Skills Bundle you downloaded in Step 2. This bundle gives Claude ready-made instructions for everyday tasks, and Claude picks the right one on its own when you ask a question. If you haven’t added a skill before, Anthropic’s guide to using skills walks you through it.
Next, run Vena’s model onboarding skill on the model you use most. This helps Claude learn your business terms and calculation rules, such as how you define gross margin, when your fiscal year starts and which scenario to use by default.
Just ask Claude to “onboard our model” or “teach Claude our numbers.” Claude looks through the model, then asks you about the terms and rules it can’t figure out from the data alone.
Claude saves your answers as a skill, which reduces the need for repeated explanations and helps it answer future questions faster and more accurately.
If you’re using ChatGPT, explain your business definitions before asking for analysis. For example, specify when your fiscal year starts, which budget or forecast to use and how you calculate key metrics.
Before you share an AI-generated number with your CFO, check where it came from. Here are a few habits to build into your workflow to help ensure the accuracy of outputs.
Start with a question you already know the answer to. Compare the result with the figures in Vena before moving on to more involved analysis. If a number looks wrong, check what the AI requested. You can do this by expanding the tool activity at the top of a response, (which in the example below says “Used 3 tools”). This shows the request Claude sent to Vena and the data Vena returned.
Also, check the year, scenario and entity in that request. A wrong year or missing filter can explain an unexpected result, even when the source data is correct. Tell Claude what to change and ask again. If figures are missing, check whether your Vena permissions allow you to see them.
Once you’ve checked that the connection works and you trust the answers, use it for the work that usually eats up your week.
Here are five use cases to try.
A department lead enters the wrong number or forgets to update their forecast, and you only catch it during the monthly review.
Regular AI checks on live Vena data can help you spot unusual figures and missing updates before the forecast goes to leadership. Start with a prompt you can run daily, like “Compare the latest forecast with budget by department, and flag any unusual changes or forecasts that haven’t been updated.” If your AI tool supports scheduled tasks, you can set it to run automatically.
At InterMountain Management, the team runs scheduled data integrity checks across its models to catch problems that could otherwise take a week to notice.
During month-end close, department heads often want to know why their numbers moved. You can ask AI to do the digging instead of filtering reports until the driver shows up.
Say consulting expenses came in higher than planned. Open Claude and ask, “Using Vena MCP, compare December 2026 actual consulting expenses with plan and show which departments contributed most to the variance.”
The breakdown shows that Sales accounts for 63% of the overspend. You can then ask Claude to create a new tab with the analysis, charts showing each department’s contribution and a written summary. The tables and charts make it easier to see where the extra spending came from.
Following our last example, knowing Sales accounts for most of the overspend tells you where to look, but not which charges caused it. If your team keeps transaction-level data in Vena, you can ask Claude to retrieve those records.
You could continue the investigation by asking, “Using Vena MCP, show December 2026 consulting transactions for Sales, largest amounts first.”
Review the biggest charges, then ask follow-up questions like “Which vendors account for most of this spending?”. Naming the expense, department and period keeps the results focused on the number you’re trying to explain.
Preparing a leadership report means gathering numbers from various sources and showing your CFO or board how the business is doing.
Say your CFO needs to see which customers brought in the most revenue in 2026. Ask Claude to “Rank customers by 2026 actual revenue and show each customer’s share of the total.” Claude pulls the figures from Vena and breaks them down.
You can then ask Claude to turn those results into a PowerPoint deck or an interactive dashboard for your CFO or board. If you create a deck, review and refine it with Claude directly in PowerPoint. Then add your recommendations so leadership knows what needs attention and what to do next.
At Strongpoint Partners, the FP&A team uses the Vena MCP to prepare forecast dashboards for individual business units and present the results for leadership.
Building a planning template manually in Excel means laying out accounts and periods, adding data and formatting the workbook yourself. Claude in Excel can handle much of that work using a live connection to Vena through an MCP.
Ask Claude to “Create an operating expense model for my New York sales team, including my 2026 actuals and my 2027 plan,” and include Vena’s formatting skill in the prompt. Claude pulls your accounts and actuals from Vena and builds a template formatted like the ones your team already uses.
Then ask Claude to add variance columns and comments explaining the biggest changes. Review the template and adjust anything that doesn’t fit your business before sharing it with your team.
For more examples, see "4 Ways You Can Use Claude in Excel With Vena."
Connecting Claude or ChatGPT to Vena lets you work with current numbers while your Vena permissions control who can access the data.
You don’t need to change your whole process to get started.
If you’re already working inside Vena, Vena AI needs no MCP connector. Its agents analyze variances and trends, help build budgets and forecasts in Excel and let colleagues across the business ask for reports in plain language.
Still want to work inside Claude or ChatGPT? Connect those tools to your Vena data through an MCP.
Want to see how Vena connects to your AI tool before getting started? Take a self-guided tour of Vena MCP.
A Model Context Protocol (MCP) is an open standard that lets AI tools connect to other software. Think of it as a universal plug that gives tools like Claude and ChatGPT a consistent way to request data.
Your AI tool has its own policies for handling the data it receives, so review those with your IT or security team before connecting. Vena MCP respects your existing Vena permissions, so users can only retrieve data they’re allowed to access. Vena also encrypts data during storage and transfer, isolates each customer’s data, and undergoes SOC 1 and SOC 2 Type II audits. See Vena’s trust page for details.
Upload a file or connect Claude to live data. Explain your business definitions, then ask questions that specify the period, scenario and entity. Check the results against a trusted report before using them for analysis or reporting.
Vena MCP supports both analysis and governed write-back. From Excel, finance teams can use supported AI tools to update assumptions, adjust planning drivers and write forecast changes back to Vena, subject to established permissions, approvals and audit controls.