STE Dictionary MCP Server

An MCP server that checks text against ASD-STE100 Simple Technical English (STE): which words are approved, which aren't, and what STE word replaces each violation. Works entirely offline from a static dictionary snapshot in data/ — no network access at runtime. See docs/superpowers/specs/2026-08-21-ste-mcp-design.md for the full design.

Setup

pip install -r requirements.txt
python scripts/download_nltk_data.py
pytest

The check_structure tool needs two small NLTK data packages (the punkt_tab sentence/word tokenizer and the averaged_perceptron_tagger_eng POS tagger -- classic statistical models, not deep learning). Running python scripts/download_nltk_data.py once after installing dependencies downloads them and trims out the non-English tokenizer languages NLTK's downloader pulls by default, keeping the on-disk footprint to a few MB instead of ~58MB. It's safe to re-run. If you skip this step, check_structure raises a RuntimeError telling you to run it.

The server reads its dictionary snapshot from the STE_DATA_DIR environment variable, defaulting to ./data (relative to the working directory the server is launched from). The snapshot in data/ is committed to this repo, so no separate download step is needed.

Related MCP server: SpellChecker MCP Server

Running standalone

python -m ste_mcp.server

Speaks MCP over stdio.

Installing into Claude Code

Register the server with the Claude Code CLI. Use an absolute path to your Python interpreter if python on your PATH doesn't have the mcp package installed.

Local scope (available only when Claude Code is run from this repo):

cd /absolute/path/to/ste-dictionary-mcp
claude mcp add --transport stdio --env STE_DATA_DIR=/absolute/path/to/ste-dictionary-mcp/data ste-dictionary -- python -m ste_mcp.server

User scope (available from any directory). Because user-scope servers don't run with this repo as their working directory, wrap the launch in a small script that cds into the repo first, e.g. ~/.claude/ste-launcher.sh:

#!/bin/sh
cd /absolute/path/to/ste-dictionary-mcp
exec python -m ste_mcp.server

Then register it:

chmod +x ~/.claude/ste-launcher.sh
claude mcp add --transport stdio --scope user --env STE_DATA_DIR=/absolute/path/to/ste-dictionary-mcp/data ste-dictionary -- ~/.claude/ste-launcher.sh

Verify with claude mcp list, or /mcp inside a session.

Claude Desktop configuration

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "ste-dictionary": {
      "command": "python",
      "args": ["-m", "ste_mcp.server"],
      "cwd": "/absolute/path/to/ste-dictionary-mcp",
      "env": {
        "STE_DATA_DIR": "/absolute/path/to/ste-dictionary-mcp/data"
      }
    }
  }
}

Tools

check_word/check_text are word-list-based, not a grammar checker: they check vocabulary, not sentence structure. check_structure adds lightweight structural checks (via a small statistical POS tagger, not a full grammar engine) for the ASD-STE100 rules a word list can't catch -- see its docstring in ste_mcp/structure.py for the exact rules and their heuristic limitations. It is diagnostic only (no rewrite suggestions); the agent using these tools is responsible for rewriting.

Some words have both an STE-approved sense and a non-STE sense (e.g. "long" as a plain adjective is STE, but "as long as"/"no longer" is not). For those, check_word returns status: "ambiguous" (instead of "non_ste") along with a note telling the caller to verify which sense applies in context, and check_text reports them in a separate ambiguous bucket/summary count rather than non_ste. status: "non_ste" is reserved for words where every matched sense is non-STE.