english-tutor-mcp

Practice English by just talking to your AI assistant — and get a daily report of your recurring grammar patterns, without ever being corrected mid-conversation.

Works with any MCP client that runs local (stdio) servers: Claude Code, Claude Desktop, Codex CLI, Cursor, and more.

• While you chat — every English message you write is silently logged, verbatim, into a local SQLite database. No corrections, no interruptions: fluency practice stays fluent.
• When you ask — /report analyzes everything since your last report as a whole and saves a markdown report. You get patterns ("drops articles before abstract nouns — 6 times"), not one-off nitpicks.
• Local-only — no API key, no account, no hosted server. Everything lives in ~/.english-tutor/ on your machine.

Quick start (Claude Code)

claude mcp add english-tutor -s user -- npx -y english-tutor-mcp

Then just talk to your assistant in English — anywhere, about anything. Every English message is collected quietly. Whenever you want feedback (tomorrow, or after a few days):

/mcp__english-tutor__report

It analyzes everything since your last report and saves it to ~/.english-tutor/reports/. Forgot for three days? It catches up on all three at once.

Commands

Prompt	What it does
/report	Analyzes all conversations not yet analyzed — however many days have piled up — and saves a markdown report. Run it in a fresh session
/report [days]	Retrospective mode: re-analyzes the last N days as one window (e.g. 7 for a weekly review), surfacing patterns too rare to show up in a single day
/weak-points [days]	Shows persistent weak points aggregated from saved reports (default 30 days). Read-only
/language [lang]	Sets the language your feedback is written in, persisted across sessions. By default it is inferred — reports arrive in your native language, quotes stay in English

Other clients

Claude Desktop — claude_desktop_config.json

{
  "mcpServers": {
    "english-tutor": {
      "command": "npx",
      "args": ["-y", "english-tutor-mcp"]
    }
  }
}

Cursor — .cursor/mcp.json

{
  "mcpServers": {
    "english-tutor": {
      "command": "npx",
      "args": ["-y", "english-tutor-mcp"]
    }
  }
}

Codex CLI — ~/.codex/config.toml

[mcp_servers.english-tutor]
command = "npx"
args = ["-y", "english-tutor-mcp"]

ChatGPT web/desktop app: not supported yet — ChatGPT connectors only reach remote MCP servers over HTTPS, while this server runs locally over stdio to keep your data on your machine. If you use the ChatGPT ecosystem, Codex CLI works today. A remote-capable HTTP mode is under consideration for v2.

How it works

1. Capture, don't judge. During conversation the model only calls log_utterance, storing your message exactly as you typed it — the errors are the data. Real-time correction would both break fluency practice and destroy the samples.
2. Patterns, not sentences. Analysis always runs over a whole day's corpus at once. One sentence shows a missing article; forty sentences show where you drop articles. Findings below 3 occurrences are discarded.
3. The host model does the analysis. The server is deliberately just SQLite CRUD — that's why no API key is needed and installation is one line. The AI subscription you already have does the thinking.
4. Nothing is ever missed. Sessions queue up unanalyzed until your next /report, which catches them all up in one pass — skipping days costs you nothing.

Data

Path	Contents
~/.english-tutor/db.sqlite	sessions, verbatim utterances, findings, report index
~/.english-tutor/reports/YYYY-MM-DD.md	daily markdown reports

Relocate everything with ENGLISH_TUTOR_DB=/path/to/db.sqlite. Delete the directory to erase all data — nothing leaves your machine.

License

MIT License