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Provides an MCP server to read data from Excel files and expose it to clients.
Configuration
View docs{
"mcpServers": {
"algonacci-mcp-excel": {
"command": "uv",
"args": [
"--directory",
"%USERPROFILE%/Documents/GitHub/mcp-excel",
"run",
"python",
"main.py"
]
}
}
}This MCP server enables clients to read data from Excel files by running a Python-based process under the MCP runtime. It exposes a simple interface for Excel data access, making it easy to query rows, cells, and sheet structures from your applications that rely on MCP as a central data source.
You run this MCP server alongside your other MCP components and connect with an MCP client to request data from Excel files. The server is designed to start a local process that reads and serves Excel data as needed by your client. Use it when you need to extract tabular data from spreadsheets and feed it into workflows, dashboards, or automation routines.
Prerequisites you need before starting:
Install the MCP runtime tooling (uv) on your system so you can launch the server process.
Place the server code and its dependencies in a project directory you control.
Add the MCP configuration snippet shown below to your MCP config file to register the Excel reader server.
The following configuration enables the MCP client to start the server that reads Excel data. The runtime command is uv, which runs a Python script named main.py from the specified directory.
Code snippet to add to your MCP config:
{
"mcpServers": {
"sql_access": {
"command": "uv",
"args": [
"--directory",
"%USERPROFILE%/Documents/GitHub/mcp-excel",
"run",
"python",
"main.py"
]
}
}
}