Excel Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Excel Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A self-evolving data analytics toolkit for Claude Desktop. Drop your Excel files in, ask questions in plain English, and build up a personal library of reusable analysis tools — no coding required.
Requires Python 3.10+ and uv.
# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh
# Install and configure Claude Desktop
uvx excel-analytics-mcp --setupThat's it. Restart Claude Desktop and start asking questions.
git clone https://github.com/blakethom8/excel-mcp.git
cd excel-mcp
bash install.shThe install script will:
uv if needed~/Documents/Excel Analytics/Open the dashboard at http://localhost:8765 (starts automatically when Claude Desktop launches the server) and drag your Excel or CSV files into the upload zone.
In Claude Desktop, try prompts like:
When you find a useful query, ask Claude to save it:
Visit the Tools tab in the dashboard to:
Claude Desktop ←→ MCP Server (stdio) ←→ SQLite DB
↓
REST API (port 8765) ←→ Web Dashboardlocalhost:8765 to power the dashboardWhen you upload an Excel file:
| Tool | Description |
|---|---|
list_datasets | Show all loaded tables with row/column counts |
describe_dataset | Column names, types, sample values, and basic stats |
query | Run read-only SQL queries against your data |
summarize | Statistical summary of a table or specific column |
| Tool | Description |
|---|---|
save_analysis | Save a SQL query as a reusable named tool |
create_tool | Build a custom Python tool (sandboxed) |
list_my_tools | See all your saved tools |
edit_tool | Update an existing tool |
delete_tool | Remove a tool |
test_tool | Run a tool with test parameters |
Tools you create (via Claude or the dashboard) are saved as JSON files and automatically registered as MCP tools on startup. They persist across sessions and can be shared.
The web dashboard at http://localhost:8765 provides:
The dashboard is a single HTML file with no build step — it works in any modern browser.
All data stays on your machine in a visible, browsable folder:
| Path | Purpose |
|---|---|
~/Documents/Excel Analytics/data.db | SQLite database with all your uploaded data |
~/Documents/Excel Analytics/tools/ | Saved analyses and custom tools (JSON files) |
~/Documents/Excel Analytics/output/ | Generated output files |
~/Documents/Excel Analytics/config.json | User configuration |
You can override the base directory with the EXCEL_MCP_HOME environment variable.
SELECT). No writes, drops, or schema changes.~/Documents/Excel Analytics/. Nothing is sent to external servers. The MCP server communicates only with Claude Desktop on your machine.Edit ~/Documents/Excel Analytics/config.json:
{
"port": 8765,
"auto_scan": false
}| Setting | Default | Description |
|---|---|---|
port | 8765 | Dashboard port |
auto_scan | false | Auto-scan a directory for Excel files on startup |
git clone https://github.com/blakethom8/excel-mcp.git
cd excel-mcp
uv sync
uv run python -m excel_mcpMIT
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.