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Excel MCP Server

Excel MCP Server

by ishayoyo
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TypeScript
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read_file

Read CSV or Excel files with chunking support for large datasets. Specify sheet names, row offsets, and limits to extract data efficiently.

Instructions

Read an entire CSV or Excel file with optional chunking for large files

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": "read_file"
  }
}

Input Schema

NameRequiredDescriptionDefault
filePathYesPath to the CSV or Excel file
sheetNoSheet name for Excel files (optional, defaults to first sheet)
offsetNoStarting row index for chunked reading (0-based, optional)
limitNoMaximum number of rows to return (optional, enables chunking)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions chunking for large files, which is useful, but doesn't address critical aspects like error handling (e.g., what happens if file doesn't exist), performance characteristics, memory usage, or output format details. For a file reading tool with zero annotation coverage, this leaves significant behavioral gaps.

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 perfectly concise - a single sentence that communicates the core functionality with no wasted words. It's front-loaded with the main purpose and includes the key additional feature (chunking) efficiently.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (file reading with chunking options), 100% schema coverage for parameters, but no annotations and no output schema, the description is minimally adequate. It covers what the tool does but lacks important context about behavior, error conditions, and output format that would help an agent use it 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?

The description mentions 'optional chunking for large files' which relates to the offset and limit parameters, but doesn't add meaningful semantics beyond what the 100% schema coverage already provides. The schema descriptions thoroughly document each parameter's purpose and optionality, so the description adds minimal value here, meeting the baseline expectation.

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 with a specific verb ('Read') and resource ('CSV or Excel file'), and mentions optional chunking for large files. However, it doesn't explicitly differentiate from sibling tools like 'read_file_chunked' or 'get_file_info', which reduces clarity about when to choose this specific tool.

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 multiple sibling tools like 'read_file_chunked', 'get_file_info', and 'bulk_aggregate_multi_files', there's no indication of when this tool is preferred or what distinguishes it from similar file reading operations.

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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