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FinanceKit MCP

FinanceKit MCP

by vdalhambra
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

portfolio_analysis

Read-only

Analyze stock portfolio value, allocation, performance, and diversification from holdings in 'SYMBOL:SHARES' format.

Instructions

Analyze a stock portfolio — total value, allocation, performance, and diversification.

Provide holdings as 'SYMBOL:SHARES' pairs (e.g., 'AAPL:10,MSFT:5,GOOGL:3'). Returns current portfolio value, weight distribution, sector breakdown, and individual position details.

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": {
      "holdings": "<holdings>"
    },
    "name": "portfolio_analysis"
  }
}

Input Schema

NameRequiredDescriptionDefault
holdingsYesPortfolio holdings as 'SYMBOL:SHARES' pairs separated by commas. Example: 'AAPL:10,MSFT:5,GOOGL:3'

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.0
  2. Removedv1.2.0
  3. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

The annotations indicate readOnlyHint=true, and the description describes an analysis that reads data without side effects. The description adds no additional behavioral context (e.g., data freshness, dependencies) beyond what annotations convey.

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 (two short paragraphs) and front-loaded: the first line states purpose, the second gives input format and output. Every sentence is necessary and no words are wasted.

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?

Given the tool's simplicity (single required parameter, presence of output schema), the description adequately covers input, output, and purpose. It could optionally mention that the portfolio must be in the specified format or that sector breakdown is based on current market data, but it is sufficiently complete for an agent to use it 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?

The schema description covers the 'holdings' parameter (100% coverage), but the tool description adds value by explaining the input format with an example and detailing the return categories (value, weight, sector breakdown). This goes beyond the schema's minimal description.

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 clearly states the tool's purpose: 'Analyze a stock portfolio — total value, allocation, performance, and diversification.' The verb 'analyze' and resource 'stock portfolio' are specific and distinct from sibling tools like company_info or risk_metrics.

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 explains the input format ('Provide holdings as 'SYMBOL:SHARES' pairs') and output categories, but does not explicitly state when to use this tool versus alternatives (e.g., risk_metrics for risk analysis). The usage context is implied but not contrasted with siblings.

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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