Smart Expense Management MCP

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add_event_expense

Add an expense to a group event and calculate how each member should split the cost using equal, percentage, or custom rules.

Instructions

Add an expense to a group event and compute per-member splits.

split_type options: "equal" → split evenly among all members (or included_member_ids) "percentage" → supply split_data={"friend_id": percent, ...} summing to 100 "custom" → supply split_data={"friend_id": amount, ...} summing to total

Returns the computed split immediately so you can verify it.

Example: Hotel ₹4000 paid by Neev, split equally among 4 friends: → each owes ₹1000

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": {
      "event_id": "<event_id>",
      "title": "<title>",
      "amount": "<amount>",
      "paid_by_friend_id": "<paid_by_friend_id>"
    },
    "name": "add_event_expense"
  }
}

Input Schema

Name	Required	Default
`title`	Yes
`amount`	Yes
`event_id`	Yes
`split_data`	No
`split_type`	No	equal
`paid_by_friend_id`	Yes
`included_member_ids`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 14, 2026

TDQS

A3.8/5.0

Behavior4/5

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

With no annotations, the description fully handles behavioral disclosure. It explains that the tool computes splits immediately and returns them for verification. It also outlines split_type behaviors. However, it does not mention potential side effects (e.g., overwriting duplicates) or error handling, which are minor omissions.

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?

The description is concise with two paragraphs and an example. It is well-structured and front-loaded. Every sentence adds value, though the example could be slightly integrated to reduce lines. Still, no waste.

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

Completeness3/5

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

Given the complexity (7 params, no annotations, output schema exists), the description adequately covers split computation and verification but lacks details on mandatory parameters and included_member_ids behavior. The output schema may cover return values, reducing the need for that detail, but parameter semantics still have gaps.

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 0%, so the description must compensate. It thoroughly explains split_type and split_data parameters with examples and options. However, other parameters (title, amount, event_id, paid_by_friend_id, included_member_ids) are not explained, leaving gaps. The example partially covers paid_by_friend_id and amount but not explicitly.

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 'Add an expense to a group event and compute per-member splits,' which is a specific verb+resource that clearly distinguishes it from siblings like create_expense (likely for personal expenses). It also provides details on split types, making the purpose precise.

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

Usage Guidelines3/5

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

The description implies usage for event expenses with splits but does not explicitly state when to use this tool versus alternatives (e.g., create_expense). No when-not-to-use or exclusions are provided, leaving the AI to infer from context.

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