Excel Analytics MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| EXCEL_MCP_HOME | No | Override the base directory where data, tools, and configuration are stored (defaults to ~/Documents/Excel Analytics/). |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_datasetsA | Show all loaded tables with row/column counts. |
| describe_datasetB | Column names, types, sample values, and basic stats for a table. |
| queryA | Run a read-only SQL query against the database. Only SELECT queries allowed. |
| summarizeC | Quick statistical summary of a table or a specific column. |
| save_analysisC | Save a SQL template as a reusable named tool. |
| create_toolC | Create a custom Python tool (sandboxed). The code must define a run(db, **kwargs) function. |
| list_my_toolsB | Show all user-created tools (saved analyses and custom tools). |
| edit_toolC | Update an existing saved analysis or custom tool. |
| delete_toolB | Remove a user-created tool. |
| test_toolB | Run a tool with given parameters and return results. params should be a JSON string of the parameters to pass. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
The tools have some clear distinctions, but there is notable overlap between create_tool, save_analysis, and edit_tool, which all involve managing custom tools or analyses, potentially causing confusion. Other tools like describe_dataset and summarize serve distinct purposes, but the tool management cluster lacks clear boundaries.
Most tools follow a consistent verb_noun pattern (e.g., create_tool, delete_tool, list_datasets), with only minor deviations like 'query' and 'summarize' being single words. Overall, the naming is readable and predictable, though not perfectly uniform.
With 10 tools, the count is well-scoped for an Excel analytics server, covering data exploration, querying, and custom tool management. Each tool appears to serve a specific role without obvious bloat or redundancy.
The toolset covers core analytics workflows: data inspection (list_datasets, describe_dataset, summarize), querying (query), and custom tool lifecycle (create, edit, delete, test, list). A minor gap is the lack of data manipulation tools (e.g., update or insert), but this is reasonable for a read-focused analytics server.