Excel MCP Server

by ishayoyo

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TypeScript

Local

get_headers

Extract column headers from Excel or CSV files to understand data structure and prepare for analysis.

Instructions

Get the column headers (first row) of a file

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": "get_headers"
  }
}

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

B3.2/5.0

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 the action but omits critical details such as error handling (e.g., for invalid file paths or unsupported formats), performance considerations (e.g., for large files), or output format. This is a significant gap for a tool with potential file I/O operations.

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 that front-loads the core purpose without unnecessary words. It avoids redundancy and wastes no space, 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 tool's complexity (file I/O with potential format variations) and lack of annotations or output schema, the description is incomplete. It fails to address behavioral aspects like error cases, output structure, or limitations, leaving gaps that could hinder effective agent use.

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%, with clear parameter documentation in the input schema. The description adds no additional meaning beyond implying the tool works with CSV or Excel files (hinted by 'sheet' parameter), but this is already covered in the schema. Baseline 3 is appropriate as the schema adequately defines parameters.

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 specific action ('Get') and resource ('column headers (first row) of a file'), distinguishing it from siblings like 'get_cell' or 'get_range' by focusing on header extraction rather than cell values or data ranges. It precisely defines the tool's function without ambiguity.

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 'read_file' or 'get_file_info', which might also provide header information. It lacks context on prerequisites (e.g., file format compatibility) or exclusions, leaving usage decisions to inference.

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