Is your finance operating model ready for the Context Era?
Get the guideYour finance data lives in Planful. Your team's questions increasingly start in Claude.
The Planful MCP Server for finance connects the two, with support for ChatGPT, Gemini, and Copilot on the way. Your AI tools can pull live Planful reports with the same permissions and security your team already has inside the platform.
Ask AI questions about your live Planful reports from Claude. Get answers in natural language without copying data out of the platform.
Planful data carries its financial structure: dimensions, hierarchies, plan versus actuals, and how your org built its plans.
Your AI only ever works with what you're already cleared to see. Dimension security, scenario security, and role-based access are always enforced before any data leaves Planful.
The MCP Server reads directly from Planful and keeps it as your governed source of truth: live, and always current with what's in the platform.
Copying numbers into a chat loses context the moment you paste. Building a custom pipeline for every AI tool becomes an engineering project you own forever. The Planful’s MCP Server gives your AI tools one governed way in. Your team authenticates with their Planful credentials, asks a question, and gets an answer drawn from the reports they are already authorized to see.
I think the biggest jump the MCP server will give us is the option to use some of the other tools we're already using today. With this locked-in data source, I don't have to worry about it making things up.
Put Planful's data to work securely in the tools you already use.
Pull a Planful budget alongside Snowflake actuals or Salesforce pipeline. Ask your AI to write variance commentary across both, in one conversation.
Ask, "Find my Q3 OpEx forecast and summarize where we're over plan." Your AI pulls the report you’re authorized to see and reasons over it in seconds.
Power users have prompts and workflows built in Claude already. The MCP Server points them at governed Planful reports instead of a stale export.
For deeper analysis, forecasting, and scenario modeling, Analyst and Planner Assistants run inside Planful with full context. The MCP Server widens the front door; the native assistants do the deep work.
The MCP Server enforces the access controls your team already relies on inside Planful. Authentication is OAuth-based, and access is read-only by design so that your AI tool only ever sees data that the user is already permitted to see in Planful. Your data is never used to train external models. The same governance you trust across Planful applies to every MCP request.

Today: Claude. Next: ChatGPT, Copilot, and Gemini. MCP is an open standard, so any AI client that supports it can connect. Your team keeps using the tool they already work in. The MCP Server is the connection, not another interface to learn.
No. Every connection is read-only. Your AI tool can pull and reason over Planful reports. It can't create, edit, or delete anything in Planful.
No. Dimension security, scenario security, and role-based access apply before any data reaches your AI tool. If you can't see a report in Planful, you can't see it through the MCP Server either.
Planful never uses your data to train its own AI. When you use the MCP Server, your data flows into your own AI workspace, governed by whatever enterprise agreement you already have with that provider.
Analyst and Planner Assistants do the deep work inside Planful: variance analysis, forecasting, scenario modeling, with full context. The MCP Server widens the front door, so your AI tool can ask a quick question and get an answer without opening Planful.






