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Python Repl

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A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute

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A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection, enabling LLM agents to execute Python code across multiple turns with variables that persist between calls.

README

A production-grade MCP server providing a persistent Python REPL with multi-session support, sandboxing, and timeout protection.

Built for LLM agents that need to execute Python code across multiple turns with variables that persist between calls.

✨ Features

Feature Description
Multi-session Isolated sessions with unique IDs — run parallel workflows
Persistent namespace Variables survive across calls within a session
Timeout protection Configurable execution timeout (SIGALRM on Unix)
Sandboxing Optional mode blocks dangerous modules (subprocess, socket, etc.)
Package install Install pip packages on-the-fly (prefers uv for speed)
File execution Run .py files inside the persistent session
Dual transport stdio (local) and streamable-http (remote)
Full introspection List variables, get history, check server status
Env-based config All settings via REPL_* environment variables

🚀 Quick Start

With Claude Desktop / Cursor (stdio)

Add to your MCP config:

{
  "mcpServers": {
    "python-repl": {
      "command": "uvx",
      "args": ["mcp-python-repl"]
    }
  }
}

With uv (local dev)

# Clone and run
git clone https://github.com/soufiane-aazizi/mcp-python-repl.git
cd mcp-python-repl
uv run mcp-python-repl

HTTP transport (remote / multi-client)

REPL_TRANSPORT=streamable-http REPL_PORT=8000 uv run mcp-python-repl

🛠️ Tools

Code Execution

Tool Description
repl_run_code Execute Python code with persistent namespace
repl_run_file Execute a .py file in the session
repl_install_package Install a pip package (uses uv if available)

Namespace Management

Tool Description
repl_list_namespace List all variables in a session
repl_get_variable Get the full value of a variable
repl_set_variable Inject a variable from JSON
repl_delete_variable Delete a specific variable
repl_clear_namespace Clear all variables in a session

Session Management

Tool Description
repl_list_sessions List all active sessions
repl_delete_session Delete a session and its data

Debugging

Tool Description
repl_get_history Get execution history for a session
repl_server_status Server config, Python version, session count

🔄 How Persistence Works

Call 1:  repl_run_code(code="data = [1,2,3]; total = sum(data); result = total")
         → returns: {"result": 6, "session_id": "a1b2c3d4e5f6", "new_variables": ["data", "total"]}

Call 2:  repl_run_code(code="doubled = [x*2 for x in data]; result = doubled", session_id="a1b2c3d4e5f6")
         → returns: {"result": [2,4,6], "new_variables": ["doubled"]}

Important: The result variable is for returning output to the caller. It does NOT persist. Use named variables instead.

⚙️ Configuration

All settings are configurable via environment variables:

Variable Default Description
REPL_TIMEOUT 30 Max execution time in seconds
REPL_MAX_SESSIONS 50 Maximum concurrent sessions
REPL_SESSION_TTL 120 Session expiry in minutes
REPL_MAX_OUTPUT 1048576 Max stdout/stderr capture (bytes)
REPL_SANDBOX false Enable sandboxing (true/false)
REPL_TRANSPORT stdio Transport: stdio or streamable-http
REPL_HOST 127.0.0.1 HTTP host (when using HTTP transport)
REPL_PORT 8000 HTTP port (when using HTTP transport)
REPL_WORKDIR cwd Working directory for executions

Sandbox Mode

When REPL_SANDBOX=true, the following modules are blocked:

subprocess, shutil, ctypes, socket, http.server, xmlrpc, ftplib, smtplib, telnetlib, webbrowser

And the following builtins are removed: exec, eval, compile, __import__ (replaced with a restricted version).

🧪 Development

# Install dev dependencies
uv sync --extra dev

# Run tests
uv run pytest -v

# Lint
uv run ruff check src/ tests/

# Test with MCP Inspector
npx @modelcontextprotocol/inspector uv run mcp-python-repl

📦 Project Structure

mcp-python-repl/
├── src/mcp_python_repl/
│   ├── __init__.py       # Package metadata
│   ├── config.py         # Env-based configuration
│   ├── session.py        # Multi-session manager with TTL
│   ├── executor.py       # Python code executor (timeout + sandbox)
│   └── server.py         # MCP server with all tools
├── tests/
│   └── test_core.py      # Unit + integration tests
├── pyproject.toml        # uv/hatch project config
├── LICENSE               # MIT
└── README.md

📄 License

MIT — See LICENSE.

from github.com/aazizisoufiane/mcp-python-repl

Install Python Repl in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install mcp-python-repl

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add mcp-python-repl -- uvx mcp-python-repl

FAQ

Is Python Repl MCP free?

Yes, Python Repl MCP is free — one-click install via Unyly at no cost.

Does Python Repl need an API key?

No, Python Repl runs without API keys or environment variables.

Is Python Repl hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Python Repl in Claude Desktop, Claude Code or Cursor?

Open Python Repl on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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