Stata AI Fusion

MCP Server + Skill Knowledge Base + VS Code Extension for Stata

Let AI directly execute Stata code, generate publication-quality analysis, and provide a complete IDE experience.

Quick Start • Features • MCP Tools • Skill Knowledge • VS Code Extension • 中文文档

Why Stata AI Fusion?

Stata is one of the most widely used statistical packages in economics, political science, epidemiology, and biostatistics. Yet while R and Python users have enjoyed deep AI integration for years, Stata has remained isolated from the AI-assisted coding revolution.

stata-ai-fusion bridges that gap. It gives AI assistants (Claude, Cursor, GitHub Copilot, and others) the ability to start a real Stata session, run commands, inspect data, extract estimation results, and capture graphs -- all through the open Model Context Protocol (MCP).

The project ships as three complementary components so every workflow is covered:

Architecture

The data flow is straightforward:

1. AI Assistant sends a tool call (e.g. run_command) via MCP.
2. MCP Server dispatches the request to the Session Manager, which maintains one or more persistent, interactive Stata processes.
3. Stata executes the command; the server captures output, strips SMCL markup, detects errors, and auto-exports any new graphs.
4. The cleaned result (text + optional base64 image) flows back to the AI, which interprets it and responds to the user.

Quick Start

Claude Code (recommended)

# Register the MCP server in one command
claude mcp add stata-ai-fusion -- uvx --from stata-ai-fusion stata-ai-fusion

# Verify
claude mcp list

Then try:

> Load the auto dataset in Stata and regress price on mpg and weight with robust SE

Claude Desktop

Edit your config file:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "stata": {
      "command": "uvx",
      "args": ["--from", "stata-ai-fusion", "stata-ai-fusion"]
    }
  }
}

Restart Claude Desktop. The Stata tools will appear in the tool list.

Cursor / VS Code (MCP)

Create .cursor/mcp.json or .vscode/mcp.json in your project root:

{
  "servers": {
    "stata": {
      "command": "uvx",
      "args": ["--from", "stata-ai-fusion", "stata-ai-fusion"]
    }
  }
}

Claude.ai (Skill Only)

This mode provides code-generation guidance only (no live Stata execution).

1. Download stata-ai-fusion-skill.zip from the Releases page.
2. Go to Claude.ai > Project > Project Knowledge > Upload.
3. Upload the zip file.

The AI will now reference the 5,653-line knowledge base when writing Stata code for you.

VS Code Extension

# Option 1: VS Code Marketplace
# Search "Stata AI Fusion" in the Extensions panel

# Option 2: From GitHub Release
code --install-extension stata-ai-fusion-0.2.3.vsix

# Option 3: Cursor
cursor --install-extension stata-ai-fusion-0.2.3.vsix

Features

MCP Server -- 11 tools for AI-driven analysis

The server exposes 11 MCP tools. Each tool can be called by any MCP-compatible AI assistant.

Conversation Example

User: "Analyze the determinants of car prices in the auto dataset."

AI calls: run_command("sysuse auto, clear")
AI calls: inspect_data()                          -> 74 obs, 12 variables
AI calls: run_command("regress price mpg weight foreign, robust")
AI calls: get_results("e", "N r2 F")              -> N=74, R²=0.52, F=29.1
AI calls: run_command("scatter price mpg || lfit price mpg")
AI calls: export_graph(format="png")               -> [base64 image]

AI: "The regression shows that each additional mile per gallon is associated
     with a $49.50 decrease in price, controlling for weight and origin..."

Skill Knowledge Base -- 5,653 lines of Stata expertise

The knowledge base uses a Progressive Disclosure architecture:

• SKILL.md (486 lines) serves as the entry-point router.
• 14 reference files cover specific domains; the AI loads them on demand.
• The AI never reads all 5,653 lines at once -- it fetches only what the current task requires.

VS Code Extension -- complete Stata IDE

MCP Tools Reference

Skill Knowledge Base

Configuration

Stata Auto-Discovery

The server automatically detects your Stata installation using a three-tier strategy:

1. Environment variable -- STATA_PATH takes highest priority.
2. Standard paths --
   • macOS: /Applications/Stata*/, /Applications/StataNow/
   • Linux: /usr/local/stata*/, /usr/local/bin/
   • Windows: C:\Program Files\Stata*\
3. System PATH -- which stata-mp, which stata-se, which stata

Supported editions: MP, SE, IC, BE (Stata 17, 18, 19 and StataNow).

If auto-detection fails, set the environment variable explicitly:

export STATA_PATH="/Applications/Stata/StataMP.app/Contents/MacOS/stata-mp"

Multi-Session Support

The server supports multiple concurrent Stata sessions with complete data isolation:

• Each session maintains its own dataset, variables, and estimation results.
• Sessions persist between tool calls -- no need to reload data after every command.
• A default session is created automatically; create named sessions for parallel workflows.
• Idle sessions are automatically cleaned up after 1 hour (configurable).
• All sessions are cleaned up gracefully on server shutdown.

AI calls: run_command(code="sysuse auto, clear", session_id="session_A")
AI calls: run_command(code="sysuse nlsw88, clear", session_id="session_B")
# session_A has 74 obs (auto), session_B has 2,246 obs (nlsw88)

Troubleshooting

The server searches for Stata in three places (see Stata Auto-Discovery). If none work, you'll see:

StataNotFoundError: No Stata installation found

Fix it:

1. Find your Stata executable manually:

   # macOS
   find /Applications -name "stata-mp" -o -name "stata-se" -o -name "stata" 2>/dev/null
   
   # Linux
   which stata-mp || which stata-se || which stata
   
   # Windows (PowerShell)
   Get-ChildItem "C:\Program Files\Stata*" -Recurse -Filter "Stata*.exe" | Select-Object FullName
   

2. Set the path explicitly:

   # macOS / Linux
   export STATA_PATH="/Applications/Stata/StataMP.app/Contents/MacOS/stata-mp"
   
   # Windows (PowerShell)
   $env:STATA_PATH = "C:\Program Files\Stata18\StataMP-64.exe"
   

3. For Claude Code, add it to your MCP config:

   {
     "env": {
       "STATA_PATH": "/path/to/your/stata"
     }
   }
   

Common pitfalls:

• On macOS, point to the binary inside the .app bundle, not the .app itself
• On Windows, use the full path including -64 suffix for 64-bit editions
• StataNow uses different binary names — check Contents/MacOS/ for the exact name

pexpect is the library that drives Stata's interactive console. Issues appear as:

ModuleNotFoundError: No module named 'pexpect'
# or
pexpect.exceptions.ExceptionPexpect: The command was not found ...

Fix it:

# If using uv (recommended)
uv pip install pexpect

# If using pip
pip install pexpect

Windows users: pexpect has limited Windows support. The server uses pexpect.popen_spawn on Windows, which works but has some limitations:

• No pseudo-terminal (PTY), so some Stata output formatting may differ
• more pagination must be disabled (the server handles this automatically)
• If you encounter issues, try running from WSL2 instead

Symptom: Claude Code or Cursor shows "MCP server failed to start" or the Stata tools don't appear.

Step 1 — Test the server standalone:

# Should print tool list and wait for input
uv run stata-ai-fusion

If this fails, check the error message:

• StataNotFoundError → see Stata not found above
• ModuleNotFoundError → install missing dependency: uv pip install stata-ai-fusion
• Address already in use → another instance is running; kill it first

Step 2 — Check your MCP configuration:

For Claude Code (~/.claude/settings.json or project .claude/settings.json):

{
  "mcpServers": {
    "stata-ai-fusion": {
      "command": "uvx",
      "args": ["stata-ai-fusion"]
    }
  }
}

For Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "stata-ai-fusion": {
      "command": "uvx",
      "args": ["stata-ai-fusion"]
    }
  }
}

Step 3 — Enable debug logging:

export MCP_STATA_LOGLEVEL=DEBUG
uv run stata-ai-fusion

This shows every Stata interaction, including discovery, session creation, and command execution.

Path separators:
Always use forward slashes or raw strings in STATA_PATH:

# PowerShell
$env:STATA_PATH = "C:/Program Files/Stata18/StataMP-64.exe"
# or
$env:STATA_PATH = "C:\Program Files\Stata18\StataMP-64.exe"

Stata edition detection on Windows:
The server checks the Windows registry under HKEY_LOCAL_MACHINE\SOFTWARE\StataCorpLP and HKEY_CURRENT_USER\SOFTWARE\StataCorpLP for installed editions. If your registry entries are non-standard (e.g., portable install), set STATA_PATH manually.

Long path issues:
If your project path exceeds 260 characters, enable long path support:

# Run as Administrator
New-ItemProperty -Path "HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem" `
  -Name "LongPathsEnabled" -Value 1 -PropertyType DWORD -Force

Antivirus interference:
Some antivirus software blocks pexpect from spawning Stata. Add your Stata directory and Python environment to the exclusion list if the server hangs on "Creating session."

Why it happens: Idle sessions are automatically cleaned up after 1 hour to free system resources. If your AI conversation pauses for a long time and then resumes, the session may have been closed.

Fix it:

• Simply run another command — the server auto-creates a new default session
• If you need a specific named session: ask the AI to call create_session
• For long-running batch jobs, use run_do_file with batch_mode=true (designed for extended execution)

Tip: You can check active sessions at any time by asking the AI to call list_sessions.

By design, the server truncates very large outputs to stay within AI context window limits:

• Head: first 3,000 characters
• Tail: last 5,000 characters
• Inline graphs: up to 5 per run_command, 3 per run_do_file

For large outputs, use run_do_file with batch_mode=true — this captures all output to a log file and returns a summary instead of the full text.

For graphs, use export_graph to save specific graphs to files at full resolution rather than relying on inline preview.

Development

# Clone and set up
git clone https://github.com/haoyu-haoyu/stata-ai-fusion.git
cd stata-ai-fusion
uv sync

# Run unit tests (no Stata required)
uv run pytest tests/test_discovery.py -v

# Run integration tests (requires Stata)
uv run pytest tests/test_integration.py -v

# Build Python package
uv build

# Build VS Code extension
cd vscode-extension && npm install && npm run build

Testing

All 85 tests pass on Stata MP 19 (macOS arm64).

Project Structure

stata-ai-fusion/
├── src/stata_ai_fusion/
│   ├── __main__.py          # CLI entry point
│   ├── server.py            # MCP server + resource registration
│   ├── stata_discovery.py   # Auto-detect Stata installation
│   ├── stata_session.py     # Interactive & batch session manager
│   ├── graph_cache.py       # Graph capture and base64 encoding
│   ├── result_extractor.py  # r()/e()/c() result extraction
│   └── tools/               # 11 MCP tool implementations
├── skill/
│   ├── SKILL.md             # Main skill routing document (486 lines)
│   └── references/          # 14 reference documents (5,167 lines)
├── vscode-extension/
│   ├── src/                 # TypeScript extension source (5 files)
│   ├── syntaxes/            # TextMate grammar
│   └── snippets/            # 30 code snippets
├── tests/                   # 85 tests (39 unit + 46 integration)
├── assets/                  # Icon, architecture diagrams
└── pyproject.toml

Contributing

Contributions are welcome! Here are some ways to help:

• Bug reports: Open an issue describing the problem, your Stata version, and OS.
• New Skill references: Add a .md file to skill/references/ covering a Stata topic.
• New MCP tools: Implement a tool in src/stata_ai_fusion/tools/ and register it.
• VS Code improvements: Expand syntax grammar or add snippets.

Please run uv run pytest tests/ -v before submitting a PR.

License

MIT -- see LICENSE for details.

Acknowledgments

• Stata by StataCorp
• Model Context Protocol by Anthropic

PyPI • VS Code Marketplace • Releases • 中文文档