Excel Reader Server
The Excel Reader Server is a MCP server that provides tools for reading and extracting data from Excel (xlsx) files in JSON format.
Capabilities include:
Reading content from all sheets in an Excel file
Extracting data from a specific sheet by name (defaults to first sheet if unspecified)
Extracting data from a specific sheet by index (defaults to index 0 if unspecified)
Returning data structured as arrays of arrays (representing rows and cells)
Converting all values to strings and representing empty cells as empty strings
Providing clear error handling for common issues like file not found, invalid sheet names, or index out of range
Provides tools for reading and parsing Excel (.xlsx) files using Python, enabling extraction of data from entire workbooks or specific sheets by name or index.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Excel Reader Serverread the sales data from Q1_report.xlsx"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Excel Reader Server
A Model Context Protocol (MCP) server that provides tools for reading Excel (xlsx) files.
Features
Read content from all sheets in an Excel file
Read content from a specific sheet by name
Read content from a specific sheet by index
Returns data in JSON format
Handles empty cells and data type conversions
Related MCP server: OpenPyXL MCP Server
Installation
Requires Python 3.10 or higher.
# Using pip
pip install excel-reader-server
# Using uv (recommended)
uv pip install excel-reader-serverDependencies
mcp >= 1.2.1
openpyxl >= 3.1.5
Usage
The server provides three main tools:
1. read_excel
Reads content from all sheets in an Excel file.
{
"file_path": "path/to/your/excel/file.xlsx"
}2. read_excel_by_sheet_name
Reads content from a specific sheet by name. If no sheet name is provided, reads the first sheet.
{
"file_path": "path/to/your/excel/file.xlsx",
"sheet_name": "Sheet1" # optional
}3. read_excel_by_sheet_index
Reads content from a specific sheet by index. If no index is provided, reads the first sheet (index 0).
{
"file_path": "path/to/your/excel/file.xlsx",
"sheet_index": 0 # optional
}Response Format
The server returns data in the following JSON format:
{
"Sheet1": [
["Header1", "Header2", "Header3"],
["Value1", "Value2", "Value3"],
["Value4", "Value5", "Value6"]
]
}Each sheet is represented as a key in the top-level object
Sheet data is an array of arrays, where each inner array represents a row
All values are converted to strings
Empty cells are represented as empty strings
Error Handling
The server provides clear error messages for common issues:
File not found
Invalid sheet name
Index out of range
General Excel file reading errors
License
This project is released under the Apache 2 License. See the LICENSE file for details.
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Available Tools
3 toolsread_excelC
Read content from Excel (xlsx) files
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | Path to the Excel file |
TDQS
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 it reads content but doesn't specify what content is read (e.g., all sheets, default sheet, or entire file), how errors are handled, or any constraints like file size limits. This leaves significant behavioral gaps for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and siblings that suggest more specific functionality, the description is incomplete. It doesn't clarify the scope of reading (e.g., all sheets vs. a default), output format, or how it differs from siblings, leaving the agent with insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with 'file_path' clearly documented. The description adds no additional parameter semantics beyond the schema, such as file format details or path examples. Given the high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read content') and resource ('from Excel (xlsx) files'), making the purpose understandable. However, it doesn't explicitly differentiate from its siblings (read_excel_by_sheet_index and read_excel_by_sheet_name), which likely offer more specific reading options.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 its siblings or any alternatives. It lacks context about scenarios where this general read operation is preferred over sheet-specific reads, leaving the agent without usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_excel_by_sheet_indexA
Read content from a specific sheet by index in Excel (xlsx) files. Reads first sheet (index 0) if sheet_index not provided.
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | Path to the Excel file | |
| sheet_index | No | Index of the sheet to read (optional, defaults to 0) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the default behavior (reads first sheet if sheet_index not provided), which is useful. However, it lacks details on error handling (e.g., invalid file paths or indices), output format, or performance considerations like file size limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently conveys the tool's purpose, default behavior, and key distinction. Every word serves a purpose with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is adequate for a simple read operation but incomplete. It covers the basic functionality and default, but lacks details on return values, error cases, or constraints like supported Excel versions, which would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents both parameters. The description adds minimal value beyond the schema by mentioning the default for sheet_index, but does not provide additional context like file format restrictions (xlsx only) or practical usage examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read content'), resource ('from a specific sheet by index in Excel files'), and distinguishes from siblings by specifying 'by index' (vs. by name or general read). It explicitly mentions the default behavior for sheet_index.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (reading by sheet index) and implies alternatives through sibling tool names (read_excel_by_sheet_name for name-based reading). However, it does not explicitly state when NOT to use this tool or compare it directly to read_excel.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
read_excel_by_sheet_nameA
Read content from a specific sheet by name in Excel (xlsx) files. Reads first sheet if sheet_name not provided.
| Name | Required | Description | Default |
|---|---|---|---|
| file_path | Yes | Path to the Excel file | |
| sheet_name | No | Name of the sheet to read (optional, defaults to first sheet) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the read operation and default behavior, but lacks details on error handling (e.g., if sheet_name doesn't exist), performance considerations, or output format. It adequately describes the core behavior but misses advanced behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, consisting of two concise sentences that directly state the purpose and default behavior without any wasted words. Every sentence earns its place by providing essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (reading Excel files with optional parameters), no annotations, and no output schema, the description is minimally complete. It covers the basic operation but lacks details on output structure, error handling, or file format constraints, leaving gaps for an agent to infer.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
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 fully. The description adds no additional meaning beyond what the schema provides, such as examples or edge cases. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Read content'), resource ('from a specific sheet by name in Excel files'), and scope ('first sheet if sheet_name not provided'). It distinguishes from sibling tools by specifying it reads by sheet name rather than by index or general reading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool (to read a specific sheet by name) and includes a default behavior (reads first sheet if sheet_name not provided). However, it does not explicitly mention when to use alternatives like read_excel_by_sheet_index or read_excel, nor does it provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- First observed
read_excel - First observed
read_excel_by_sheet_index - First observed
read_excel_by_sheet_name
TDQS
The tools have significant overlap in purpose, as all three are focused on reading Excel files, with only minor variations in how they specify the sheet. An agent might easily confuse them or struggle to choose the right one for a given task, since the distinctions are subtle and not clearly differentiated in the descriptions.
The tool names follow a consistent verb_noun pattern with 'read_excel' as the base, and suffixes like '_by_sheet_index' and '_by_sheet_name' that clearly indicate the specific functionality. This makes the naming predictable and easy to understand across the set.
With only 3 tools, the server feels thin for a domain like Excel reading, which might benefit from additional operations such as writing, listing sheets, or handling different file formats. However, the count is not extreme and could be considered borderline for basic functionality.
The tool set is severely incomplete for an Excel server, as it only covers reading operations and lacks any writing, updating, or other common Excel functionalities like formatting, formula evaluation, or metadata access. This will likely cause agent failures when more comprehensive tasks are required.
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