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monarch-mcp2-obot

monarch-mcp2-obot

by dcode
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Receipts Get Receipt

receipts_get_receipt
Read-onlyIdempotent

Retrieve a specific receipt by ID from Monarch Money. Choose fields or output mode to get summary, full, or raw details.

Instructions

Get receipt.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "receipt_id": "<receipt_id>"
    },
    "name": "receipts_get_receipt"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsNoOptional dotted output field paths to return, such as ['id', 'merchant.name', 'category.name'].
receipt_idYes
output_modeNoOutput shape to return. Use summary for compact CLI-style defaults, full for complete structured data without raw, and raw for complete structured data including raw payloads.summary

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2/5.0
Behavior2/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description does not need to restate safety. However, it adds no behavioral context beyond the annotations, such as what happens for missing ids, whether associated merchant/category data is included, or how output_mode affects the response.

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

Conciseness2/5

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

The description is maximally concise, but it is under-specified rather than efficiently informative. One short sentence restating the tool name does not earn its place in a definition that needs to support correct tool selection and invocation.

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

Completeness2/5

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

There is no output schema, so the description should explain what a receipt getter returns or how to choose output shapes, but it does not. Combined with a minimal description and one undocumented required parameter, the definition leaves too much for the agent to infer.

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

Parameters2/5

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

The schema already documents fields and output_mode, but receipt_id has no description and the tool description adds no parameter-level clarification. The description 'Get receipt.' contributes nothing to understanding the three params or their interplay.

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

Purpose2/5

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

The description 'Get receipt.' is essentially a restatement of the tool title 'Get Receipt' and the tool name receipts_get_receipt. It names the verb and resource but provides no detail about scope, return content, or how it differs from sibling tools like receipts_list_receipts.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus alternatives. The existence of receipts_list_receipts implies this is for fetching a single resceipt by id, but the description never states that usage condition or contrasts with related tools.

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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