Codat Financial Data MCP. Query unified financial data from 30+ platforms.
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Codat Financial Data MCP Server connects your AI client to over 30 financial platforms. It standardizes data—from accounting (Xero, QuickBooks) to commerce (Shopify, Stripe) and banking—allowing your agent to query and aggregate invoices, orders, bank transactions, and company records using natural language.
What your AI agents can do
Check api health
Verifies the operational connection status of the Codat API.
Get data sync status
Checks the progress of data synchronization across your connected platforms.
List accounting customers
Lists customer records pulled from your connected accounting data.
Retrieves a directory of all linked company IDs and business entities from your connected accounts.
Verifies the current connection status of the Codat API service.
Checks the progress and status of data sync across different connected financial modules.
Pulls a list of customer records from your accounting platform data.
Gathers a list of standardized invoices across your connected accounting systems.
Retrieves a list of bank accounts linked to your accounting records.
Pulls transaction history directly from your connected bank feeds.
Gathers a list of sales orders from your connected e-commerce systems.
Retrieves payment transaction details from commerce platforms like Stripe or Square.
Shows which specific data links are active for a given company ID.
Displays a directory of all available accounting, commerce, and banking integrations.
Programmatically creates a new business entity record within your Codat account.
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Codat Financial Data MCP Server: 12 Tools for Financial Data Sync
These tools allow your AI agent to perform specific, programmatic actions: listing invoices, checking sync status, or creating new financial entities across connected systems.
019dd0d3check api health
Verifies the operational connection status of the Codat API.
019dd0d3get data sync status
Checks the progress of data synchronization across your connected platforms.
019dd0d3list accounting customers
Lists customer records pulled from your connected accounting data.
019dd0d3list accounting invoices
Retrieves a standardized list of invoices from your accounting system.
019dd0d3list banking transactions
Lists payment transactions pulled from your linked bank feeds.
019dd0d3list commerce orders
Lists order history from your connected e-commerce systems.
019dd0d3list commerce transactions
Lists payment transactions from your e-commerce commerce platforms.
019dd0d3list data connections
Lists the specific data connections currently active for a company ID.
019dd0d3list financial bank accounts
Lists all bank accounts linked through your accounting data.
019dd0d3list financial companies
Lists all business entities connected to your Codat account.
019dd0d3list supported integrations
Lists every accounting, commerce, and banking integration Codat supports.
019dd0d3register new financial entity
Creates and registers a new business entity within your Codat account.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Codat Financial Data, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
You're hooking your AI client up to Codat Financial Data. This lets your agent talk to over 30 financial platforms, standardizing everything from your accounting records (Xero, QuickBooks) to your e-commerce sales (Shopify, Stripe) and bank statements. You can use natural language to pull and combine invoices, orders, bank transactions, and company details.
list_data_connections shows you exactly which data links are active for a company ID.
check_api_health verifies the operational status of the Codat API connection.
get_data_sync_status checks the progress of data sync across all your connected financial modules.
list_financial_companies pulls a list of all business entities linked to your Codat account, and register_new_financial_entity lets your agent create a new one.
list_supported_integrations shows you every accounting, commerce, and banking integration Codat supports.
When it comes to accounting, list_accounting_customers gives you a list of customer records from your connected accounting platform, and list_accounting_invoices pulls a standardized list of invoices from your accounting system.
For banking, list_financial_bank_accounts retrieves all bank accounts linked through your accounting data, and list_banking_transactions pulls transaction history directly from your connected bank feeds.
Your agent handles e-commerce stuff with list_commerce_orders, gathering a list of sales orders from your connected e-commerce systems, and list_commerce_transactions retrieves payment transaction details from platforms like Stripe or Square.
How Codat Financial Data MCP Works
- 1 First, subscribe to the Codat server and retrieve your API Key from your Codat dashboard settings.
- 2 Next, initiate a query via your AI client, asking for specific financial data (e.g., 'Show me last month's invoices for Acme Corp').
- 3 The AI client executes the necessary tool calls, standardizes the data across all connected platforms, and returns the structured results to you.
The bottom line is that your AI client handles the complex, multi-source data mapping, so you just talk to it.
Who Is Codat Financial Data MCP For?
Financial Analysts, Underwriters, and Fintech Developers. If your job requires piecing together financial data from separate systems—like matching Shopify orders to QuickBooks invoices—this is for you. You need a single point of query, not a dozen dashboards.
Summarizes cross-platform accounting and commerce data quickly without leaving their primary workspace.
Automates the retrieval of financial history and credit data for business assessment using simple AI queries.
Instantly retrieves standardized financial records to prototype apps or build new data-intensive features using natural language commands.
What Changes When You Connect
- Standardized Data: Instead of pulling data manually from Xero, QuickBooks, and Stripe separately, you query a single standardized endpoint. This cuts down reconciliation time and gives you one clean view of cash flow.
- Full Lifecycle View: You get the whole picture. You can cross-reference
list_commerce_orders(what was sold) withlist_accounting_invoices(what was billed) andlist_banking_transactions(when the money hit the bank) in one conversation. - Entity Oversight: Need to know what companies are linked? Use
list_financial_companiesto get a master list of all business entities, which is crucial for multi-subsidiary reporting. - Operational Sync Check: Don't guess if your data is up to date. Use
get_data_sync_statusto confirm if accounting invoices or bank transactions are fully synced before running a critical report. - Build Out Infrastructure: For developers,
list_supported_integrationsprovides a directory of every possible integration, speeding up the prototyping of new financial data pipelines. - Direct Action: You can't just read data. You can use
register_new_financial_entityto programmatically create new companies, making the agent useful for full operational workflows.
Real-World Use Cases
Reconciling Sales Against Bank Statements
A company's CFO needs to know if the money from last month's sales actually hit the bank. They ask their agent to cross-reference list_commerce_transactions (sales payments) with list_banking_transactions (bank deposits). The agent runs both tools, compares the dates and amounts, and flags any discrepancies for manual review.
Assessing a New Client's Financial Health
An underwriter is vetting a new business. Instead of requesting 10 separate spreadsheets, they ask the agent to run list_financial_companies and list_data_connections for the client. The agent pulls the required financial history and provides a summary report, drastically cutting the assessment time from days to minutes.
Catching Billing Errors on Large Orders
The sales team needs to check if a massive order was billed correctly. They prompt the agent to list the list_commerce_orders and then immediately check the corresponding list_accounting_invoices. The agent compares the line items and alerts the user if the invoice amount doesn't match the order total.
Auditing Data Sources for Compliance
A compliance officer needs to verify all connected systems. They ask the agent to run list_supported_integrations and list_data_connections to get a complete audit trail of every connected platform and entity, ensuring nothing is missing.
The Tradeoffs
Treating data sources as silos
Manually logging into Shopify to get orders, then logging into Xero to get invoices, and finally downloading bank statements. This process takes hours and requires manual spreadsheet mapping to find the true financial picture.
→
Use your AI agent to run multiple tools in sequence. Start by calling list_commerce_orders and list_accounting_invoices, then ask the agent to compare the two results. It handles the cross-reference automatically.
Relying on single-platform reports
Accepting a single report from Stripe that only shows payment success. This report misses the actual bank settlement details or the initial billing record, leading to cash flow blind spots.
→
Always check the full cycle. Run list_commerce_transactions and immediately follow up with list_banking_transactions to see the final movement of funds.
Ignoring data freshness
Running a financial report based on data that hasn't synced since last week. The results are inaccurate because the data is stale, leading to bad operational decisions.
→
First, run get_data_sync_status to confirm all sources are up to date. If synchronization is incomplete, don't run the report until the status confirms readiness.
When It Fits, When It Doesn't
Use this server if you need to build a unified view of financial activity that spans multiple, disparate systems (e.g., connecting e-commerce, accounting, and banking). It's perfect for reconciliation, auditing, and deep financial analysis. Don't use it if you only need a simple list of invoices from one specific platform; use that platform's native API directly. If your goal is merely to store or transform data in a data lake, this is an orchestration layer, not a storage solution. If you only need to list available integrations, use list_supported_integrations; don't try to query live data without first verifying connectivity using check_api_health.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Codat. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 12 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Reconciling financial data shouldn't involve 5 different logins.
Today, getting a complete picture of cash flow means jumping through hoops. You check the e-commerce platform for orders, then log into the accounting software for invoices, and finally download bank statements. You spend time copying and pasting data points, cross-referencing dates, and hoping the IDs match up. It’s a manual process that guarantees errors.
With the Codat Financial Data MCP Server, you talk to your agent. You say, 'Show me the total revenue for Q2.' The agent handles the connection to Shopify, QuickBooks, and your bank. It runs the necessary tools (`list_commerce_orders`, `list_accounting_invoices`, `list_banking_transactions`) and spits out one clean, aggregated number. Period.
Codat Financial Data MCP Server: Querying Unified Financial Data
The major manual steps that vanish are the need to export CSVs from multiple dashboards and the subsequent hours spent in Excel cleaning and normalizing those sheets. You never have to manually map a Stripe transaction ID to a bank feed entry again.
This server doesn't just give you data; it coordinates the data retrieval from dozens of sources. It turns a multi-day, manual data pipeline into a single, instant conversation with your AI agent.
Common Questions About Codat Financial Data MCP
How do I use the list_accounting_invoices tool? +
You ask your agent to list standardized invoices. The agent takes care of the source platform, pulling records from Xero, QuickBooks, and others into one standardized format for you. You don't need to know which platform the invoice came from.
Is list_commerce_orders the same as list_accounting_invoices? +
No, they track different things. list_commerce_orders tracks what the customer bought on the website (the raw sale). list_accounting_invoices tracks what the business billed the customer for, which is the financial record.
What is the best way to check data sync status using get_data_sync_status? +
Simply ask your agent to check the status. It will report on the sync progress for specific modules—for example, telling you that invoices are fully synced but bank transactions are still processing.
Can I use list_financial_companies to check all my business entities? +
Yes. This tool retrieves a master directory of all linked companies, giving you the necessary IDs to scope your data queries across multiple subsidiaries.
How do I use list_financial_bank_accounts to find all my active bank connections? +
It lists all linked bank accounts from your accounting data. Your agent uses this to confirm which financial sources are available for reporting or cross-platform checks.
What is the difference between list_commerce_transactions and list_accounting_invoices? +
The two tools pull data from different sources. list_accounting_invoices pulls standardized invoices from accounting platforms, while list_commerce_transactions lists raw payment transactions from commerce systems.
Does list_data_connections help me manage my company's data sources? +
Yes, it lists active data links for a specific company ID. This lets you see exactly which platforms are connected and whether the data flow is established.
If I get an error using list_supported_integrations, what should I check first? +
First, verify your API Key in the Codat dashboard. If the key is correct, the error might indicate a temporary service outage or a required credential update on your end.
How do I find my Codat API Key? +
Log in to your Codat Dashboard, navigate to Settings > API Keys, and copy your unique access token.
Which accounting platforms are supported? +
Codat supports 30+ major platforms including Xero, QuickBooks (Online & Desktop), Sage, FreshBooks, and Dynamics 365.
Can I check data synchronization status via AI? +
Yes! The get_data_sync_status tool allows the agent to monitor the progress of data pulls and pushes for any linked company ID.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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