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sebastienrousseau

bankstatementparser-mcp

by sebastienrousseau
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Summarize statement balances

summarize_statement
Read-onlyIdempotent

Summarize a bank statement's balances and totals by extracting key summary fields from inline text input, skipping transaction rows. Supports formats like CAMT, MT940, CSV, OFX.

Instructions

Summarize an inline statement's balances and totals only.

Use this when you need just the opening/closing balances, currency, and
other summary fields without the per-transaction rows. For the full
transaction detail alongside the summary, use ``parse_statement``
instead.

Args:
    content: The raw statement text.
    filename: Original filename; its extension selects the format.
    format: Explicit format override.

Returns:
    The summary record with Decimal values stringified.

Raises:
    ValueError: If the format is unsupported or cannot be detected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoExplicit format identifier that overrides detection from the filename. One of: 'camt' (CAMT.053), 'pain001', 'csv', 'ofx', 'qfx', 'mt940'. When omitted, the format is inferred from the filename extension.
contentYesThe raw statement text to summarize, inline (not a file path). Accepts ISO 20022 CAMT.053 and pain.001 XML, SWIFT MT940, CSV exports, and OFX/QFX payloads.
filenameNoOriginal filename of the payload; its extension (.xml, .csv, .ofx, .qfx, .mt940, .sta) selects the format when 'format' is omitted. Defaults to 'statement.xml'.statement.xml

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the bar is lower. The description adds valuable context: returns Decimal values as stringified, raises ValueError for unsupported formats, and clarifies the tool works inline. No annotations are contradicted.

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 concise: 100 words, structured with Args, Returns, Raises. Every sentence contributes meaning. The purpose is front-loaded, and no extraneous information is present.

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?

Given the presence of annotations, an output schema, and 3 parameters, the description covers all needed context: what the tool does, parameters with clarifications, return type, and error conditions. It is fully informative for an AI agent to select and invoke correctly.

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 baseline is 3. The description adds value by clarifying that 'content' is raw text (not a file path), that 'filename' selects format via extension and has a default, and that 'format' is an explicit override. It also lists accepted format values in the schema description, but that is part of the schema.

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 states a specific verb ('summarize') and resource ('statement balances and totals only'), clearly distinguishing it from the sibling tool 'parse_statement' which does full transaction detail. The title and name reinforce this.

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

Usage Guidelines5/5

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

Explicitly tells when to use this tool ('when you need just the opening/closing balances') and when not to ('For full transaction detail... use parse_statement instead'), providing direct comparison and clear usage boundaries.

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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