Lunch Money MCP Server

updateAsset

Modify an existing financial asset's balance, name, currency, or metadata in Lunch Money to maintain accurate financial tracking.

Instructions

Update an existing asset's properties including balance and metadata

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": {
      "id": "<id>"
    },
    "name": "updateAsset"
  }
}

Input Schema

Name	Required	Description	Default
`id`	Yes
`type_name`	No
`type_name_override`	No
`name`	No
`balance`	No
`balance_as_of`	No
`currency`	No
`institution_name`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jan 28, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is an update operation (implying mutation) but doesn't cover permissions needed, whether changes are reversible, rate limits, error conditions, or what happens to unspecified properties. For a mutation tool with 8 parameters and no annotation coverage, this is insufficient.

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 a single, efficient sentence that front-loads the core action. However, given the complexity (8 parameters, mutation operation), it may be too concise, as it omits necessary details that would help the agent use the tool correctly.

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?

For a mutation tool with 8 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It doesn't explain parameter meanings, behavioral traits, or return values, making it inadequate for safe and effective tool invocation by an AI agent.

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?

Schema description coverage is 0%, so all 8 parameters are undocumented in the schema. The description only mentions 'balance and metadata' as examples, covering at most 2 parameters (balance and possibly name/institution_name as metadata). It doesn't explain the purpose of id (required), type_name vs type_name_override, balance_as_of, currency, or other fields, leaving significant gaps.

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

Purpose4/5

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

The description clearly states the verb ('Update') and resource ('an existing asset's properties'), specifying the scope ('including balance and metadata'). It distinguishes from createAsset (creating vs updating) but doesn't explicitly differentiate from other update tools like updateTransaction or updateBudget.

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?

The description provides no guidance on when to use this tool versus alternatives like bulkUpdateTransactions or other update operations. It doesn't mention prerequisites (e.g., asset must exist) or exclusions, leaving the agent to infer usage from the name and context alone.

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