Synci

List transactions

list_transactions

Read-onlyIdempotent

List the user's financial transactions in a date window, newest first, across all account types (bank, deposit, line of credit, investment). Each row is lean by default: id, date, amount (negative = money out), currency, booked, payee, description (omitted when it duplicates payee), an account {id, name, institution} ref, and — when available — mcc, category, and bank_details (raw provider metadata: transaction/purpose codes, currency-exchange info, and the MCC category text that banks put in additional_information — useful for categorising spend when enrichment is off). Pass "verbose": true for the full, raw transaction record.

Investment rows also carry: type (raw activity, e.g. BUY / SELL / DIVIDEND / CRYPTO_SEND), is_cash_flow, units, and price_per_unit (the effective per-unit price in this row's currency, = |amount| / units). IMPORTANT for "what did I spend": rows with is_cash_flow=false are asset transfers or income-in-kind (crypto send/receive, staking, stock splits) — NOT money spent; exclude them from spending totals. Use amount, units and price_per_unit for trade figures; ignore any price written into the description string (it is the provider's own and can be in a different currency).

Dates: "date" is Synci's per-account authoritative date by default (what the user sees; "spending in June" means this). Override with date_field "booking" or "value" to filter/sort/show a specific date instead. Both booked and pending transactions are returned by default; filter with status ("all" | "booked" | "pending", default "all"). Pending amounts can still change.

Coverage: meta.earliest_available_date is the date the queried accounts are synced from. If it is later than your "from", the window is only PARTIALLY covered — data before it was never synced (not absent), so any total would silently under-report. Caveat the coverage, or narrow "from" to it.

Pagination: results are bounded by the date window and "limit" (default 50, max 100). Check meta.has_more: if true, request the next page by passing meta.next_cursor as "cursor" (keyset paging, no gaps or overlap). A page may hold fewer rows than "limit" (the user can exclude transactions from outbound channels), so never read a short page as the end of the data; only has_more=false is. Sensitive identifiers (IBAN, account numbers, etc.) are always omitted.

Input Schema

Name	Required	Description
`to`	No	Optional end date (YYYY-MM-DD), inclusive. Defaults to today.
`from`	No	Optional start date (YYYY-MM-DD), inclusive. Defaults to 30 days before "to".
`limit`	No	Optional max rows to return (1-100). Defaults to 50. Check meta.has_more and page with meta.next_cursor.
`cursor`	No	Optional. Pass meta.next_cursor from a previous call to fetch the next page (keyset paging).
`status`	No	Filter by settlement status. Defaults to "all" (booked + pending).
`verbose`	No	When true, return the full raw transaction record instead of the lean shape.
`account_id`	No	Optional. Restrict to a single financial account (id from list_accounts). Omit to span all accounts.
`date_field`	No	Which date to filter/sort/show on. "mapped" (default) is Synci's authoritative per-account date; "booking" or "value" force a specific field.

Output Schema

Name	Required	Description	Default
`data`	Yes	Newest first. Lean rows omit null/empty keys; with verbose:true each item is the full raw transaction record instead.
`meta`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 15, 2026

TDQS

A4.6/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: default lean shape vs verbose raw record, omitted sensitive identifiers (IBAN/account numbers), both booked and pending returned by default with mutable pending amounts, keyset paging with no gaps/overlap, and the warning that a short page is not the end of data. That is unusually rich operational context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Long but information-dense and clearly segmented with front-loaded purpose followed by Dates/Coverage/Pagination sections. A few passages restate schema content (limit default, cursor keyset paging), so it is not maximally tight, but no section is filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Even though an output schema exists, the description supplies the domain semantics an agent needs to interpret the rows correctly (is_cash_flow for spending totals, units/price_per_unit for trades, coverage under-reporting risk). Combined with 8 well-documented parameters, nothing material is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond it: amount sign convention ('negative = money out'), date_field semantics with a worked example, is_cash_flow exclusion rule for spending totals, and the note to ignore prices embedded in description strings. Defaults are largely duplicated from the schema, keeping this short of a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource and scope: 'List the user's financial transactions in a date window, newest first, across all account types'. It names the covered account types and distinguishes itself from list_holdings/get_account_balance by framing this as the transaction ledger rather than a snapshot or position list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives strong conditional guidance: when to pass verbose, when to override date_field ('spending in June' means mapped), how to handle partial coverage via meta.earliest_available_date, and how to page. It never explicitly names a sibling tool to use instead, which is the only gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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