Excel MCP Server

by ishayoyo

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TypeScript

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ratio_analysis

Calculate financial ratios from Excel/CSV data and compare them against industry benchmarks for performance evaluation.

Instructions

Perform comprehensive financial ratio analysis with industry benchmarks

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": {
      "filePath": "<filePath>"
    },
    "name": "ratio_analysis"
  }
}

Input Schema

Name	Required	Description	Default
`filePath`	Yes	Path to the CSV or Excel file with financial statement data
`sheet`	No	Sheet name for Excel files (optional)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Jan 2, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'comprehensive' analysis and 'industry benchmarks', but doesn't specify what ratios are calculated, how benchmarks are applied, output format, or any limitations (e.g., data requirements, processing time). This is inadequate for a tool that likely performs complex financial computations.

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 a single, efficient sentence with no wasted words. It front-loads the core purpose ('Perform comprehensive financial ratio analysis') and adds valuable context ('with industry benchmarks'), making it easy to parse quickly.

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?

Given the complexity of financial ratio analysis, no annotations, and no output schema, the description is insufficient. It doesn't explain what ratios are computed, how benchmarks are sourced, or the return format, leaving significant gaps for an AI agent to use the tool effectively.

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 100%, so the schema already documents both parameters ('filePath' and 'sheet'). The description adds no additional parameter semantics beyond implying financial data is needed, which is already suggested by the tool's purpose. This meets the baseline for high schema coverage.

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 tool's purpose as 'Perform comprehensive financial ratio analysis with industry benchmarks', which includes a specific verb ('perform') and resource ('financial ratio analysis'). It distinguishes from many siblings like 'statistical_analysis' or 'trend_analysis' by specifying financial ratios, though it doesn't explicitly differentiate from 'dcf_analysis' or 'budget_variance_analysis' which are also financial tools.

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. It doesn't mention prerequisites (e.g., financial data format), exclusions, or comparisons to siblings like 'dcf_analysis' or 'budget_variance_analysis', leaving the agent to infer usage context solely from the tool name and description.

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