Skip to main content
Glama
AxLabs

Banana Accounting MCP Server

by AxLabs

Account card

banana_account_card
Read-only

Return the ledger of transactions for an account by ID. Supports filtering by period, custom columns, and JSON or HTML format.

Instructions

Return the account card (ledger of transactions) for an account. Defaults to JSON. Supports view, columns, navigation, period and filter.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
docNoAccounting document name as opened in Banana (e.g. "accounting.ac2"). Append "_p1", "_p2" for previous years. Defaults to BANANA_DEFAULT_DOC if set.
viewNoXML name of the view to return.
filterNoJavaScript expression to filter transactions, e.g. filter=row.value("Date")==="2024-01-15". Available: row, rowNr, table.
formatNoResponse format. Defaults to "json" for machine-readable output.
periodNoPeriod filter: an abbreviation like "Q1"/"3M"/"1Y" or a date range "2024-01-01/2024-03-31".
accountYesAccount id, e.g. "1000".
columnsNoComma-separated XML names of columns to return, e.g. "Account,Description,Balance".
navigationNoWhen true, include the HTML page navigation (only relevant for html format).
Behavior3/5

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read. The description adds 'Defaults to JSON' which is a useful behavioral detail beyond the schema, but it does not disclose other traits like response size, pagination, or error conditions. This is acceptable given annotation coverage but not rich.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the primary purpose, and every word adds value. It avoids restating schema details verbatim while still giving a concise overview.

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

Completeness4/5

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

With 8 parameters, all fully described in the schema, and no output schema, the description adequately sets expectations by calling it a ledger and noting the JSON default. It could have mentioned the response structure or pagination, but the schema and read-only annotations make it sufficiently complete for selection and invocation.

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

Parameters3/5

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

Schema description coverage is 100%, so every parameter is already well documented. The description merely lists some parameter names ('view, columns, navigation, period and filter') without adding deeper meaning. The only slight addition is 'Defaults to JSON', but that is also in the schema. Baseline 3 is appropriate.

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?

The description starts with a specific verb 'Return' and a clear resource: 'the account card (ledger of transactions) for an account'. It distinguishes this tool from siblings like banana_balance or banana_journal by naming a unique resource (account card) with a clarifying parenthetical.

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?

The description provides clear context: use this tool when you need the account card ledger for a specific account. It does not explicitly mention alternatives or exclusions, but the context is unambiguous, which aligns with 'clear context, no exclusions'.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AxLabs/banana-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server