Connect the Fincome MCP
Fincome's MCP server connects an AI assistant (Claude, Cursor…) to your financial KPIs. You ask your questions in natural language, and the agent fetches the figures directly from Fincome — no exports, no copy-pasting.
What is Fincome's MCP server?
MCP (Model Context Protocol) is an open standard that lets an AI assistant connect securely to a data source. Concretely, Fincome's MCP server gives an agent like Claude or Cursor read-only access to your financial KPIs: MRR, ARR, churn, revenue, LTV/CAC, etc.
The agent connects as one of your users and sees exactly the same data that this user can view in the dashboard — no more, no less.
What is it useful for, concretely?
The MCP server is useful whenever you want to get a figure or an analysis without going through the interface. A few typical use cases:
- Answering a one-off question without building a report: "How many new customers in May?", "What is my churn rate this quarter?"
- Preparing an investor meeting or a board: ask the agent to retrieve MRR, ARR, growth, and churn over the period, then format them.
- Breaking down a KPI by dimension: "What is my ARR by product?", "My churn by country this quarter."
- Crossing your analyses with other sources already connected to your assistant, in a single conversation thread.
The benefit: your Fincome figures become accessible where you already work with AI, in natural language.
How to install and test it (beta)
Step 1 — Add the connector in Claude
Go to Claude's connectors page, then add a custom connector with the following URL:
https://mcp.fincome.co/mcpStep 2 — Enable it in your conversation
Once added, enable the Fincome connector in the chat where you want to use it. It then becomes available to the assistant.
Step 3 — Connect your Fincome account
On first use, Claude redirects you to the Fincome login page (same credentials as the dashboard). You approve the access, and the agent receives a secure token, limited to your user and your company. That's it: you can ask your questions.
Managing several entities?
Each connection is linked to a single account (one user and one company). If you manage several separate entities, simply point each account to a different URL, for example:
https://mcp.fincome.co/mcp2
https://mcp.fincome.co/mcp3
Add one connection per entity this way, and authorize each one with the corresponding account.
What about Cursor or Claude Desktop?
It is also possible to configure it via an mcp.json file. For these cases, refer directly to the MCP server's technical documentation.
What you can ask the agent
The assistant automatically queries your KPIs based on your question. You have nothing to configure — just phrase your request in natural language.
You want… | Example question |
|---|---|
List the available metrics | "Which Fincome metrics can I view?" |
A time series of a KPI | "Show me my monthly MRR over the last 12 months." |
A KPI broken down by dimension | "What is my ARR by product?", "My churn by country this quarter." |
A combined analysis | "Compare my MRR for January and June, and explain the gap." |
Behind the scenes, the agent retrieves your metrics (MRR, ARR, churn, revenue, LTV/CAC…), filters them, breaks them down by dimension (including your custom dimensions), and chooses the time step (month, quarter, year).
Security and privacy
Security is at the heart of how the MCP server works:
- Read-only: the agent can view your data, but cannot modify anything in Fincome.
- Your permissions apply: the agent sees exactly what the connected user sees, according to their rights in the dashboard.
- OAuth 2.1 authentication: no password is transmitted to the assistant; access relies on a secure token, limited to your user and your company.
- Revocable at any time: from Settings → Connected AI assistants, you can view and delete each connection.
These guarantees add to the platform's compliance (SOC 2, GDPR, ISO 27001, European hosting).
What we produced in 10 minutes
To give you a concrete idea, here is a financial review datapack (due diligence style) built end to end via the Fincome MCP — on a demo account, in about ten minutes, without any export or SQL. Each time, it was enough to ask the question in natural language and ask the assistant to format the result:
- ARR breakdown by industry, account size, acquisition channel, and product.
- Recurring vs one-off and level of deferred revenue.
- Collection by status and unpaid rate.
- Average basket (ARPA) and LTV over 12 rolling months, overall and by segment.
- Growth breakdown (new / reactivation / expansion / contraction / churn).
- Acquisition by sales rep, upsell & NRR by CSM, and 24-month NRR cohorts.
- A summary scorecard of SaaS KPIs (ARR, YoY growth, NRR, GRR, quick ratio, churn, recurring share…).
Everything was assembled directly into a spreadsheet and a presentation from the agent's answers.
FAQ and common errors
Which assistants are compatible?
All clients that support the MCP protocol, such as Claude (app and Desktop) and Cursor. The connection is made either via the connectors page (Claude), or via an mcp.json file (Cursor, Claude Desktop).
Can the agent modify my data?
No. Access is strictly read-only. The assistant can query your metrics and your views, but cannot create, modify, or delete anything in Fincome.
Does the agent see all my company's data?
It sees exactly what the connected user sees, according to their Fincome permissions. If a user does not have access to certain data in the dashboard, the agent will not have access to it either.
How to connect several companies at the same time?
Each connection is linked to one user and one company. To connect several, assign each one its own URL (…/mcp, …/mcp2, … up to …/mcp10) and authorize each account separately.
How to revoke an access?
In the dashboard, go to Settings → Connected AI assistants. You will find all the active connections there and can delete them with one click.
Are my credentials shared with the assistant?
No. The connection goes through OAuth 2.1: you authenticate on the Fincome page, and the assistant only receives a secure, revocable token, never your password.
Do the returned dates really match my request?
Date ranges are inclusive by whole period. For example, from 2024-05-01 to 2024-05-31 returns the month of May; from 2024-05-01 to 2024-06-01 returns May and June. Specify your period in your question to remove any ambiguity.
Updated on: 03/07/2026
Thank you!
