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Write Like Me

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Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all

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Описание

Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.

README

An MCP (Model Context Protocol) server that learns your personal writing style from a local document corpus and gives Claude self-updating style context — so the prose it produces on your behalf actually sounds like you.

100% local. Nothing leaves your machine. The server reads your documents on-device, derives statistical style metrics, and serves them to Claude over stdio. There is no network call and no LLM code path in v0.1 — the actual rewriting is done by the Claude you're already talking to, guided by the style context this server provides.

How It Works

  1. You point it at your writing — a directory (or set of files) of things you've written: essays, emails, posts, docs, notes.
  2. It learns your voice locally — sentence rhythm, lexical diversity, contraction habits, punctuation tics, signature phrases, formality markers — and writes a profile.json plus a searchable excerpt index (examples.db).
  3. It watches for changes — edit or add to your corpus and the profile and index rebuild automatically (debounced).
  4. Claude uses it as style context — before writing for you, Claude loads your profile and can pull real excerpts of your writing for grounding, then matches your voice. You never upload anything.

Privacy & Local-Only Posture

This is the whole point of the project, so it is worth being explicit:

Guarantee How it's enforced
No network access The server has no HTTP client and no LLM call. A regression test runs the full tool flow with all sockets patched to raise.
No verbatim corpus stored profile.json holds derived statistics + short (≤3-token) signature phrases only — never your sentences. Enforced by a dispersion floor + a dedicated test.
Excerpts stay local find_writing_examples serves excerpts live from a local SQLite index and returns source basenames only — never absolute paths.
Private data stays out of the repo The default data dir is ~/.write-like-me (outside any clone). If you keep config/profile/index inside a clone, those paths are gitignored.
Clean build artifacts uv build ships only the package + packaging metadata — no corpus, no profile.json, no *.db. Verified by a test.
Secret scanning secret-scan.yml runs both TruffleHog and Gitleaks.

Install

Requirement: Python ≥ 3.10. You must tell the server where your writing lives — via a config file, the WRITE_LIKE_ME_CONFIG env var, or ~/.write-like-me.json.

Option A: Install from GitHub

pip install git+https://github.com/gwicho38/write-like-me-mcp.git

Option B: Run without installing (uvx)

uvx write-like-me-mcp /path/to/your/write-like-me.json

Option C: Clone and install locally

git clone https://github.com/gwicho38/write-like-me-mcp.git
cd write-like-me-mcp
pip install -e .

Configuration

The server is driven by a small JSON config that names your writing sources and which profile is active.

write-like-me.json example

{
  "active_profile": "default",
  "data_dir": "~/.write-like-me",
  "profiles": {
    "default": {
      "sources": ["~/writing", "~/notes"],
      "exclude": ["drafts/"],
      "file_extensions": [".md", ".markdown", ".txt", ".docx", ".pdf", ".html", ".htm"]
    },
    "work": {
      "sources": ["~/work/memos"]
    }
  },
  "llm": { "enabled": false }
}
Field Required Default Description
active_profile yes Which entry in profiles to build and serve.
profiles yes Map of profile name → settings. The schema is multi-profile-ready; v0.1 builds only the active one.
profiles.<name>.sources yes Directories and/or files to learn from (~ expanded).
profiles.<name>.exclude no [] Path components to skip during the scan.
profiles.<name>.file_extensions no see table below Which extensions to analyze.
data_dir no ~/.write-like-me Where profile.json + examples.db are written.
llm.enabled no false Reserved for a future server-side rewrite path; always false in v0.1.

Config discovery priority

The config file is resolved at startup with this priority (first match wins):

Priority Method Example
1 (highest) CLI argument write-like-me-mcp /path/to/write-like-me.json
2 Environment variable WRITE_LIKE_ME_CONFIG=/path/to/write-like-me.json
3 Home-dir config file ~/.write-like-me.json

If no config is found, the server exits with a clear error explaining how to create one — it never silently defaults to a directory.

Setup

Claude Code (CLI)

claude mcp add write-like-me -- write-like-me-mcp /path/to/your/write-like-me.json

That's it. The server starts automatically with every claude session.

To change config, remove and re-add:

claude mcp remove write-like-me
claude mcp add write-like-me -- write-like-me-mcp /new/path/to/write-like-me.json

Claude Desktop

Add this to your Claude Desktop config file:

OS Config path
macOS ~/Library/Application Support/Claude/claude_desktop_config.json
Windows %APPDATA%\Claude\claude_desktop_config.json
Linux ~/.config/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "write-like-me": {
      "command": "write-like-me-mcp",
      "args": ["/path/to/your/write-like-me.json"]
    }
  }
}

Alternative: Environment Variable

Instead of passing the config path as an argument:

export WRITE_LIKE_ME_CONFIG="/path/to/your/write-like-me.json"

Supported File Types

Format Extensions Notes
Plain text .txt, .md, .markdown UTF-8 with encoding fallback
PDF .pdf Extracted with PyMuPDF
Word .docx Headings + tables preserved
HTML .html, .htm Boilerplate (script/style/nav) stripped
Rich Text .rtf Not supported in v0.1 — the plain reader would leak RTF control codes into the corpus and corrupt the metrics; proper handling is deferred.

Available Tools

Once configured, Claude gains access to these five tools:

Tool Description
get_style_profile Return the full learned style profile (sentence rhythm, vocabulary, punctuation, signature phrases, and a ready-to-use style guide). Call this before writing prose on the user's behalf.
find_writing_examples FTS5/BM25 search for representative real excerpts of the user's writing, for few-shot grounding. Returns basenames only.
apply_style Compare a draft to the user's profile and return a concrete rewrite brief — draft-vs-author metric gaps plus the style guide. The calling LLM does the rewrite.
analyze_writing_style (Re)scan the corpus and rebuild profile.json + examples.db. Runs automatically at startup and on corpus changes; call explicitly to force a rebuild.
style_status Report profile/index health, readiness, document count, and whether the (reserved) LLM path is enabled.

Example Usage

Once set up, ask Claude things like:

  • "Draft a reply to this email so it sounds like me."
  • "Rewrite this paragraph in my voice — check my style profile first."
  • "Write a short post about X the way I'd write it; pull a couple of my real examples for reference."

Claude will load your style profile, optionally retrieve real excerpts, and match your voice — all from context this server computes locally.

Architecture

Claude (Desktop / Code / API)
    │
    ▼  stdio transport (stdout = protocol; stderr = logs)
write-like-me MCP Server
    ├── FastMCP            (5 tool definitions)
    ├── Style Analyzer     (sentence/lexical/punctuation/phrase metrics)
    ├── StyleProfile       (derived-stats model → profile.json)
    ├── Excerpt Index      (SQLite FTS5 + BM25, paragraph excerpts → examples.db)
    ├── Watchdog Watcher   (debounced corpus-change rebuilds)
    └── Text Extractors    (TXT/MD, PDF, DOCX, HTML)
            │
            ▼
    Your local corpus              Your local data dir
    ~/writing, ~/notes, ...   →    ~/.write-like-me/<profile>/
                                     ├── profile.json   (derived stats only)
                                     └── examples.db    (local excerpt index)

Nothing in this diagram crosses the machine boundary: there is no network edge.

Version Boundary: v0.1 → v0.2

v0.1 is intentionally local-only and LLM-free:

  • apply_style returns a rewrite brief (metric gaps + style guide); the Claude you're already talking to performs the actual rewrite. A server-side LLM apply_style that returns finished rewritten prose is deferred to a future version.
  • The config carries a reserved llm block (enabled: false) so this can be added later without a schema change. In v0.1 it is always disabled, and a test guarantees no socket is ever opened.

Development

git clone https://github.com/gwicho38/write-like-me-mcp.git
cd write-like-me-mcp
uv sync --extra dev

# Run the local quality gate (lint, type-check, tests)
uv run ruff check .
uv run mypy src
uv run pytest

# Run the server directly against a test config
uv run write-like-me-mcp /path/to/test/write-like-me.json

# Inspect interactively with the MCP Inspector
npx @modelcontextprotocol/inspector write-like-me-mcp /path/to/test/write-like-me.json

Testing notes

  • Tests are hermetic: builds and data dirs go to tmp_path, and HOME is monkeypatched so the real home is never touched.
  • The OSS-safety suite (tests/test_oss_safety.py) and the no-verbatim-corpus suite (tests/test_no_verbatim_corpus.py) encode the privacy guarantees in the table above — they are the project's reason for existing, so keep them green.

License

MIT — see LICENSE.

from github.com/gwicho38/write-like-me-mcp

Установка Write Like Me

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/gwicho38/write-like-me-mcp

FAQ

Write Like Me MCP бесплатный?

Да, Write Like Me MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Write Like Me?

Нет, Write Like Me работает без API-ключей и переменных окружения.

Write Like Me — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Write Like Me в Claude Desktop, Claude Code или Cursor?

Открой Write Like Me на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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