israeli-bank-connector

Israeli Bank Connector

Instructions

Step 1: Identify Connected Banks

Check which MCP server is available and what accounts are connected:

• israeli-bank-mcp: direct scraper integration
• il-bank-mcp: Docker-based with persistent analysis
• If no MCP: guide the user through a CSV or Excel export from the bank website

Neither MCP is installable with npx. israeli-bank-mcp is not published to npm and declares no bin, so any instruction to run npx israeli-bank-mcp is wrong and will fail. The real shapes, taken from each repository:

Node 22 or newer is required for the MCP servers, and Python 3.9 or newer for the bundled script. israeli-bank-scrapers declares engines.node >= 22.22.2. On an older Node the install or the run fails before any bank is ever contacted, and the error will not mention the bank. Check node --version first when a user reports that nothing works at all.

israeli-bank-mcp exposes two tools and one resource, and that is the whole surface: fetch-transactions, two-factor-auth, and the banks://list resource that reports which credential fields each bank needs. Everything in Steps 3 to 5 below is work the agent does on the returned data. Do not expect the server to categorize, total, or export anything.

Step 2: Retrieve Transactions

Fetch transaction data for the requested period:

• Default: Current month
• Supported: Up to 12 months history (bank-dependent)
• Include: Bank accounts AND credit card transactions

Step 3: Categorize and Analyze

Apply Israeli-specific categorization:

Do not report money moved into savings as spending. A pension contribution, keren hishtalmut deposit or gemel transfer is the user's own money changing pocket, not an expense. The script reports three figures for this reason: Total Spending (excluding savings), Into Savings, and Total Outflow (the two combined). Quoting the outflow figure as "you spent X" overstates spending by whatever the user is putting away, which for a typical Israeli salary deduction is a substantial share.

Categorisation is keyword matching, so review it before presenting it as fact. The script matches merchant descriptions against Hebrew and English keyword patterns, guarded on both scripts so a pattern matches a whole token rather than a fragment: Hebrew-letter lookbehind so פז does not fire inside פזגז, and Latin-letter guards on both sides so hot does not fire inside Hotel or PHOTO. Hebrew one-letter prefixes are handled by matching a de-prefixed copy of each token as well, which is why הפקדה לפנסיה reaches the savings rule; without that the guard blocks the most natural Hebrew phrasing and files a pension deposit as an insurance expense.

Misclassifications remain, and this is a CLASS of failure, not a fixed list. Any Hebrew merchant string that contains a pattern token as a real word will match it: a mall called קניון מגדל שלום matches the insurer מגדל, and מלון הוט matches the cable company הוט. Those two are named because they are common, not because they are the only ones. Show the user the category breakdown and invite corrections rather than asserting it is their spending, and never present a category total as a fact about the person without them having seen the rows behind it.

Money coming in is not netted off spending, and no net view is offered. Any positive amount, whether a refund, a reversal, a salary, a transfer in or a loan drawdown, is reported on its own Credits In line and excluded from every category total and every percentage. Nothing in the data distinguishes a refund from a salary, so a "net" figure built from that bucket subtracts the user's salary from a spending category and reports a negative total. If the user wants refunds netted, net the specific rows they point at, by hand. Check the sign convention of your source first: a feed that reports every line as positive produces an empty spending total.

Step 4: Present Insights

Provide:

1. Monthly spending summary by category
2. Top 10 merchants by spending
3. Month-over-month trends
4. Recurring charges identified
5. Unusual transactions flagged

Step 5: Export for Tax (if requested)

Format transactions for Israeli tax purposes:

• Separate business vs personal expenses
• Flag VAT-deductible purchases
• Export in format compatible with Israeli accounting software

Examples

Example 1: Monthly Spending Summary

User says: "Show me my spending breakdown for January" Result: Categorized breakdown with NIS amounts per category, top merchants, and comparison to December.

Example 2: Subscription Audit

User says: "What recurring payments am I making?" Result: List of detected recurring charges with amounts, frequency, and suggestion for potential savings.

Example 3: Tax Expense Export

User says: "Export my business expenses for my accountant" Result: Filtered and categorized business transactions with VAT amounts, ready for import into accounting software.

Bundled Resources

Scripts

• scripts/categorize_transactions.py, Categorizes Israeli bank transactions by spending category using Israeli-specific merchant pattern matching (Shufersal, Rami Levy, Rav-Kav, etc.). Accepts transaction JSON and outputs categorized spending summaries. Run: python3 scripts/categorize_transactions.py --example for a demo, or python3 scripts/categorize_transactions.py --json transactions.json for real data. Add --output-json for machine-readable output.

References

• references/spending-categories.md, Israeli spending category definitions with Hebrew terms and common merchant examples for each category (housing/diur, groceries/mazon, transportation/tahaburah, utilities/shartuim, etc.). Consult when customizing categorization rules or explaining categories to users.
• references/supported-banks.md, Full list of 14 banks (Hapoalim, Leumi, Discount, Mercantile, Mizrahi-Tefahot, FIBI, Otsar HaHayal, Pagi, Union, Yahav, Massad, OneZero, Behatsdaa, Beyahad Bishvilha) and 4 credit card companies (Visa Cal, Max, Isracard, Amex) from the israeli-bank-scrapers CompanyTypes enum, with BOI bank codes, library scraper IDs, and MCP server coverage notes. Consult when setting up bank connections or troubleshooting missing accounts.

Reference Links

Handling credentials and transaction data

This skill sits on top of a scraper that takes live Israeli bank usernames, passwords and one-time codes, and it produces a complete transaction history. Treat both as sensitive.

• Credentials belong in the MCP server's own configuration or environment, never in the chat, never in a file you create, and never in a command you echo back to the user.
• israeli-bank-mcp reads credentials from environment variables and deliberately never from tool arguments, precisely so they do not end up in the LLM conversation history. Its variable names are derived from the bank id and the login field by camelCase-to-upper-snake, so leumi plus username gives LEUMI_USERNAME, and otsarHahayal plus username gives OTSAR_HAHAYAL_USERNAME. Ask the banks://list resource which fields a given bank needs rather than guessing, because the shape differs per bank (Hapoalim wants a usercode, not a username). If a bank fails with a missing-credential error, it names the exact variables.
• Do not print, log, or repeat a credential, an OTP, or a card number, even partially, and do not ask the user to paste one into the conversation.
• Do not persist raw transaction dumps beyond what the current task needs, and tell the user where anything you do write is stored. Note that il-bank-mcp keeps scraped data in a local SQLite database, so the history outlives the session by design.
• Transaction descriptions reveal health providers, political donations, and religious institutions. Summarise; do not volunteer inferences about the person from their spending.

Gotchas

• The operational point, which IS load-bearing: israeli-bank-scrapers uses headless browser scraping, not an official Open Banking API, and agents routinely reach for UK Open Banking or generic PSD2 endpoints that do not exist in Israel. Israel's own open-banking regime is reported to derive from the Berlin Group NextGenPSD2 framework on its own timeline, but that characterisation is unverified in this skill and should not be repeated to a user as fact.
• Bank Leumi, Hapoalim, Discount, Mizrahi-Tefahot, and First International each have different API implementations. There is no single unified API across all Israeli banks.
• Mercantile and Otsar HaHayal are SEPARATE scrapers in the upstream library even though they are subsidiaries of Discount and FIBI respectively. Treat them as their own connection (each has its own loginFields shape). Do not assume Discount credentials cover Mercantile or that FIBI credentials cover Otsar HaHayal.
• Transaction history depth is bank-specific and this skill does not have a sourced table of it. Reports put Hapoalim and Leumi below 12 months and the FIBI group at 12 or more, but that is unverified. Treat "up to 12 months" as a ceiling, never a promise, and tell the user what the scrape actually returned rather than what you expected.
• What the library can retrieve depends on the installed version, so pin before you debug. As of israeli-bank-scrapers 6.9.0 (2026-07-22) Leumi exposes savings accounts and Max exposes credit card balances; neither existed in the 6.7.x line. If a user reports a missing Leumi savings account or a missing Max balance, check the version before assuming the scrape failed. Anything older than 6.7.10 will also fail outright on Max (login page) and Isracard (bot detection) rather than just return less.
• Both MCP wrappers declare the scraper as a caret range (^6.7.3 and ^6.1.4), not a hard pin, so a fresh install resolves to the current release. What actually freezes a user on an old scraper is a committed lockfile or a stale Docker image, so check the INSTALLED version rather than the declared range when you are diagnosing a capability gap.
• Israeli bank account numbers include a branch number (snif) prefix. Agents may validate account numbers using international IBAN format, but Israeli domestic transfers use the local branch+account format.
• Credit card statements in Israel are issued by separate companies (Isracard, Max, CAL) and not directly by the banks. Agents may try to fetch credit card data from the bank API instead of the card company.

Troubleshooting

Error: "2FA required"

Cause: the bank login may require two-factor authentication Solution: Complete 2FA through your bank's app/SMS when prompted by the MCP server. This is a one-time setup per session.

Error: "Scraper timeout"

Cause: Bank website slow or blocking automated access Solution: Retry after a few minutes. If persistent, check israeli-bank-scrapers GitHub issues for known bank-specific issues.

Error: "Missing credit card transactions"

Cause: Credit card company is separate from bank in Israel Solution: Add credit card company (Visa Cal, Max, Isracard) as a separate connection in the MCP server configuration.