quickbooks-mcp-server
Provides read/write access to QuickBooks Online accounting data, including tools for managing invoices, payments, purchases, journal entries, transfers, customers, accounts, and reports, plus reconciliation tools for detecting bank feed gaps and duplicate transactions.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@quickbooks-mcp-serverScan for duplicate transactions in last month's bank feed"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
quickbooks-mcp-server
A single-file MCP server that gives Claude full read/write access to QuickBooks Online, plus reconciliation tools that find the things a human scrolling a register won't.
$ qbo_health_check
transport ...... stdio (Claude Desktop, Claude Code, claude.ai)
api ............ QuickBooks Online v3
tools .......... 22
version ........ 2.0.0
deploy ......... local, or HTTP on a Raspberry Pi behind TailscaleWhy this exists
Bookkeeping questions are almost never one query. "Did we double-pay that vendor?" means listing purchases, grouping by amount and date proximity, checking against the bank feed, and then looking at whether the duplicate was later voided. That's a loop, and loops are what an agent is for.
The design bet: give the model a small set of composable tools and let it do the
reasoning, rather than shipping one giant reconcile() that encodes my judgment about
what a discrepancy means.
That bet is why v2.0.0 has 22 tools, down from 45 in v1.0.0. The first version had a
tool for every question I'd ever asked. It turned out most of those were the model
composing two primitives — so the primitives stayed and the compounds were deleted. See
CHANGELOG.md for the migration map.
Related MCP server: penni-mcp
Tools
$ qbo --list-tools
read
qbo_company_info qbo_get_preferences qbo_health_check
qbo_list_accounts qbo_list_customers qbo_get_customer
qbo_list_bills qbo_list_deposits qbo_get_entity
qbo_get_invoice qbo_get_transaction qbo_get_transfer
qbo_get_journal_entry qbo_get_report qbo_account_register
write
qbo_create_invoice qbo_create_payment qbo_create_purchase
qbo_delete_journal_entry qbo_delete_purchase qbo_delete_transfer
qbo_batch_delete
reconciliation
qbo_detect_bank_feed_gaps find dates where the feed silently stopped
qbo_find_duplicate_transactions near-match scan across amount + date window
qbo_duplicate_scan_by_account the same, scoped to one account
qbo_analyze_reconciliation month-end variance with the arithmetic shownThe reconciliation tools are the ones worth stealing. Bank feed gaps are the failure mode nobody catches — the feed stops for four days, transactions never arrive, and the books balance perfectly against an incomplete picture. Nothing errors. You find it in March when the year-end doesn't tie.
Install
$ git clone https://github.com/rjpaganini/quickbooks-mcp-server
$ cd quickbooks-mcp-server
$ pip install -r requirements.txt
$ cp .env.example .env # then fill in your QBO app credentialsRegister an app at developer.intuit.com to get a client ID and secret. You will need:
QB_REALM_ID your company id
QB_CLIENT_ID from the Intuit developer app
QB_CLIENT_SECRET from the Intuit developer app
QB_REFRESH_TOKEN from the OAuth playground
QB_ACCESS_TOKEN refreshed automatically once seeded
QB_SANDBOX true while testing — set false deliberatelyThen point your MCP client at it:
{
"mcpServers": {
"quickbooks": {
"command": "python",
"args": ["/absolute/path/to/server.py"]
}
}
}Safety
This server can delete things in live accounting data. That is not a hypothetical —
qbo_batch_delete exists because cleaning up a bad import by hand is miserable.
Read SECURITY.md before pointing it at a real company file. The short
version: start in sandbox, keep QB_SANDBOX=true until you've watched it work, and treat
the write and delete tools as you'd treat rm with a wildcard.
$ pytest # unit tests, no network
$ pytest -m live # smoke tests against a live sandbox companyNotes
Single file on purpose.
server.pyis large, but the whole thing is greppable and there's no import graph to hold in your head.Also runs as an HTTP service on a Raspberry Pi via
deploy-to-pi.sh, which is how I reach it from claude.ai on a phone over Tailscale.No credentials, company data, or financial records are in this repository.
License
MIT.
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Maintenance
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