excel-engine-mcp
Enables real Excel desktop automation to recalculate formulas, read computed cell values, and export true-fidelity PDFs, complementing library-based workflows.
README
excel-engine-mcp
A local MCP server that drives the real Excel desktop application (COM automation) to do the things file-manipulation libraries (openpyxl etc.) fundamentally cannot: recalculate formulas, read computed cell values, and render true-fidelity PDF.
Design philosophy: this server complements library workflows instead of replacing them. Writing static cells and bulk data is faster with openpyxl — but openpyxl only stores formula strings (reading them back gives
None), and no library has Excel's render engine. This MCP handles only the engine-exclusive part, keeping its tool surface tiny (5 tools).
Requirements
- Windows 10+ with a logged-in interactive desktop session (Excel has no true headless mode)
- Microsoft Office (Excel) installed and licensed — verified on Office 2016+ (Excel 16.0)
- Python 3.10+ — verified on 3.12
- Claude Code or any MCP client
Install
git clone https://github.com/Feynman520/d01-p02-excel-engine-mcp.git
cd d01-p02-excel-engine-mcp
py -3.12 -m venv .venv # or: python -m venv .venv
.\.venv\Scripts\python.exe -m pip install -r requirements.txt
Register with Claude Code
Run this in the cloned folder (uses absolute paths, so it works from anywhere afterwards):
claude mcp add excel-automation --scope user -- "$PWD\.venv\Scripts\python.exe" "$PWD\server.py"
--scope user makes it available in every project. Use --scope project to limit it to one project.
Verify
$py = ".\.venv\Scripts\python.exe"; $env:PYTHONUTF8 = "1"
& $py tests\smoke_com.py # COM recalc / computed values / PDF / zombie cleanup
& $py tests\server_tools.py # MCP tool registration (does not launch Excel)
Tools (3 core + 2 diagnostics)
| # | Tool | Input → Output | Why engine-only |
|---|---|---|---|
| ① | excel_recalculate |
src_path, out_path → {out_path} |
Full dependency recalculation — libraries write formulas but cannot compute them |
| ② | excel_read_values |
path, sheet?, cell_range?, recalc? → {sheet,address,rows,cols,values,text} |
Reads computed cell values (openpyxl only has the formula strings) |
| ③ | excel_export_pdf |
src_path, out_path, sheet?, recalc? → {out_path} |
WYSIWYG PDF via Excel's render engine (print areas, fit-to-page, headers/footers) |
| — | excel_health |
→ {alive, excel_version} |
Session check (launches Excel on first call) |
| — | excel_restart |
→ {alive} |
Recovery from COM errors |
Typical flow: write inputs with openpyxl → excel_recalculate to bake real values →
excel_read_values to verify / excel_export_pdf for the final PDF.
Originals are never modified; results are always written to out_path.
Architecture notes
- Single STA worker thread (
engine/session.py): win32com COM objects are bound to the thread that created them, while FastMCP may hop threads — so every Excel call is serialized onto one dedicated thread. - Lazy session: Excel starts on the first tool call, is reused across calls, and is closed when the server stops.
DispatchEx+ early binding (gencache.EnsureDispatch): a dedicated Excel instance (never attaches to the user's open Excel), called through the type library. ⚠️ExportAsFixedFormatfails with 1004 (0x800A03EC) under late binding due to optional argument marshalling — early binding is required.- Zombie prevention: after
Quit(), any surviving dedicated Excel process is force-killed by PID (identified via the main window handle). - RPC-rejection retry:
RPC_E_CALL_REJECTEDright after startup is retried with backoff. - stdout protection: the one-time makepy cache generation output is redirected to stderr (stdout is the JSON-RPC channel).
Limitations
- Not suitable for unattended/service sessions (needs an interactive desktop).
- Bulk static writes are faster with libraries — that is by design.
License
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