Click on "Deploy 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., "@office-mcp make an Excel report with October sales, totals, and frozen headers"
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.
MCP server that turns JSON into real files. Excel, Word, CSV — no code
generation, no broken binaries, no openpyxl in your context window.
LLMs cannot reliably emit a valid .xlsx. They can write Python that sometimes
does, without formatting, formulas, column widths or multiple sheets — and they
burn 200 lines of context doing it. This server replaces that with one tool call:
15 lines of JSON in, a proper file out.
agent → make_xlsx({path, sheets}) → report.xlsx with styled headers, number
formats, frozen panes, autofilter and a =SUM total rowuvx --from git+https://github.com/xxxsonaaaaaa-maker/office-mcp office-mcpNo npm account, no PyPI, no build step. Python 3.10+.
Related MCP server: Excel MCP Server
Any MCP client (Claude Desktop, Cursor, Windsurf, Continue, custom):
{
"mcpServers": {
"office": {
"command": "uvx",
"args": ["--from", "git+https://github.com/xxxsonaaaaaa-maker/office-mcp", "office-mcp"]
}
}
}Tool | Output | Highlights |
|
| multiple sheets, column types ( |
|
| headings, paragraphs, bullets, tables with a real Word style |
|
| custom delimiter, UTF-8 BOM so Excel opens Cyrillic correctly |
{
"path": "out/report.xlsx",
"title": "October sales",
"sheets": [{
"name": "October",
"columns": [
{"header": "Item", "width": 28},
{"header": "Qty", "type": "number"},
{"header": "Price", "type": "money"},
{"header": "Total", "type": "money"}
],
"rows": [["Nails 90mm", 120, 12, 1440], ["Screws 4x50", 500, 3, 1500]],
"totals": true
}]
}Result: out/report.xlsx, styled header row, 1440 formatted as money,
=SUM(D4:D5) in the total row.
Relative paths only; .. is rejected — the server cannot write outside
its working directory.
Extension must match the tool (.xlsx, .docx, .csv), otherwise the
call fails with a readable message instead of writing a corrupt file.
Errors are returned as isError content with a human-readable reason, so
the agent can fix the arguments and retry instead of guessing.
Zero transport coupling. office_core.py is pure dict → bytes.
The MCP layer, a CLI or an HTTP API are thin wrappers over the same core.
No storage. Files are written locally; nothing is uploaded anywhere.
No magic. The server compiles a spec. It does not invent content, call an LLM, or require a key.
v0.1 — XLSX, DOCX, CSV. PPTX and PDF are next; see PLAN.md.
MIT
Создаёт CSV с настраиваемым разделителем и BOM (для корректного открытия в Excel с кириллицей). Для простых выгрузок, когда Excel не нужен.
Inputs: path (required), rows (required), bom, columns, +1 more.
Создаёт документ Word (.docx): заголовки, абзацы, маркированные списки, таблицы. Используй для договоров, писем, ТЗ, отчётов и любых текстовых документов.
Inputs: path (required), blocks (required), title.
Создаёт настоящий Excel-файл (.xlsx) из JSON-описания: листы, колонки с шириной и типом (text/number/money/percent/float), строки, строка «Итого» с формулами SUM. Используй, когда пользователь просит таблицу, отчёт, смету или выгрузку в Excel.
Inputs: path (required), sheets (required), title.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
Scored across 3 tools
Each tool maps to a distinct output format (xlsx, docx, csv), and the descriptions explicitly differentiate use cases (e.g., make_csv is for simple exports when Excel isn't needed). The only mild overlap is between make_xlsx and make_csv for tabular data, but the guidance resolves it well.
All three tools follow a clean, predictable verb_noun pattern (make_xlsx, make_docx, make_csv) with consistent casing and format suffixes. There is no deviation or ambiguity in naming style.
Three tools is at the low end but each is well-defined and earns its place for document generation. For a broad 'office' scope one might expect a few more (e.g., pptx), so it's slightly under-scoped rather than excessive.
The surface covers creation for three common formats but is generation-only: there is no ability to read, parse, or edit existing files, and PowerPoint is absent. These notable gaps limit the server to one-way output workflows.
Turns agent output into versioned web pages, PDFs, Word docs, spreadsheets and Markdown.
Real .docx and .xlsx files from structured data, with automatic Hebrew/Arabic RTL.
Convert, create and edit Word, PowerPoint, Excel and PDF documents from any AI agent.
Turn a JSON file or pasted JSON into an Excel workbook and a CSV, right in the chat.
