Excel MCP Server

Overview Schema Source Related Servers Discussions Admin

data_profile

Analyze Excel or CSV files to generate comprehensive data profiling reports that identify column statistics, patterns, and quality issues for data validation and cleaning.

Instructions

Generate comprehensive data profiling report for all columns

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": "data_profile"
  }
}

Input Schema

Name	Required	Description	Default
`filePath`	Yes	Path to the CSV or Excel file
`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. While 'generate comprehensive data profiling report' implies a read-only analysis operation, the description doesn't specify what 'comprehensive' includes, whether it modifies the source file, what format the report takes, or any performance considerations. For a tool with no annotation coverage, this leaves significant behavioral questions unanswered.

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 extremely concise - a single sentence that efficiently communicates the core function. Every word earns its place: 'Generate' (action), 'comprehensive data profiling report' (output), 'for all columns' (scope). There's no wasted verbiage or unnecessary elaboration.

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 data profiling (which typically includes statistics, data types, null counts, patterns, etc.), the lack of annotations, and no output schema, the description is insufficient. It doesn't explain what 'comprehensive' means, what the report format is, or how results are returned. For a tool that presumably produces rich analytical output, more context is needed about what the agent can expect.

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 fully documents both parameters (filePath and sheet). The description doesn't add any parameter-specific information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.

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: 'Generate comprehensive data profiling report for all columns.' It specifies the action (generate), the output type (data profiling report), and scope (for all columns). However, it doesn't differentiate from sibling tools like 'statistical_analysis' or 'smart_data_analysis' that might also analyze data.

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. With many sibling tools for data analysis (statistical_analysis, correlation_analysis, trend_analysis, etc.), there's no indication of what distinguishes data profiling from these other analytical functions or when it's the appropriate choice.

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