code-execution-mcp

code-execution-mcp

An MCP server that enables AI agents to execute terminal commands and Python code on the host system, leveraging Agent Zero's battle-tested implementation with session management and smart output handling.

Category
Visit Server

README

Code Execution MCP Server

A Model Context Protocol (MCP) server that exposes Agent Zero's battle-tested code execution capabilities.

This MCP server allows any AI agent (Claude, Cursor, Windsurf, etc.) to execute terminal commands and Python code on the host system using Agent Zero's proven implementation.

Features

  • Execute Terminal Commands: Run shell commands with full session persistence
  • Execute Python Code: Run Python code via IPython with session management
  • Multiple Sessions: Maintain separate execution contexts
  • Smart Output Handling: Automatic prompt detection, timeout management, and dialog detection
  • Cross-Platform: Works on Linux, macOS, and Windows (experimental)

MCP Client Configuration (no installation needed)

Add to your application MCP config:

  • simple case using uvx
{
  "mcpServers": {
    "code-execution": {
      "command": "uvx",
      "args": ["code-execution-mcp"]
    }
  }
}
  • or pipx if uvx is not installed
{
  "mcpServers": {
    "code-execution": {
      "command": "pipx",
      "args": ["run", "code-execution-mcp"]
    }
  }
}

Additional configuration

The MCP server can be configured via environment variables:

# Shell executable (default: /bin/bash on Unix, powershell.exe on Windows)
export CODE_EXEC_EXECUTABLE=/bin/bash

# Init commands (semicolon-separated, run when creating new sessions, empty by default)
export CODE_EXEC_INIT_COMMANDS="source /path/to/venv/bin/activate;export PATH=\$PATH:/custom/bin"

# Timeout configuration (in seconds)
export CODE_EXEC_FIRST_OUTPUT_TIMEOUT=30      # Wait for first output
export CODE_EXEC_BETWEEN_OUTPUT_TIMEOUT=15    # Wait between output chunks
export CODE_EXEC_DIALOG_TIMEOUT=5             # Detect dialog prompts
export CODE_EXEC_MAX_EXEC_TIMEOUT=180         # Maximum execution time

# Log directory (default empty = logging disabled)
export CODE_EXEC_LOG_DIR=/path/to/logs

Additional examples

  • start sessions with custom shell and python environment + logging
{
  "mcpServers": {
    "code-execution-mcp": {
      "command": "uvx",
      "args": ["code-execution-mcp"],
      "env": {
        "CODE_EXEC_EXECUTABLE": "/bin/zsh",
        "CODE_EXEC_INIT_COMMANDS": "source /Users/lazy/Projects/code-execution-mcp/.venv/bin/activate",
        "CODE_EXEC_LOG_DIR": "/Users/lazy/Projects/code-execution-mcp/logs"
      }
    }
  }
}
  • override timeouts
{
  "mcpServers": {
    "code-execution-mcp": {
      "command": "uvx",
      "args": ["code-execution-mcp"],
      "env": {
        "CODE_EXEC_FIRST_OUTPUT_TIMEOUT": "60",
        "CODE_EXEC_MAX_EXEC_TIMEOUT": "300"
      }
    }
  }
}

Manual installation

# Clone or download this package, then navigate to the directory
git clone https://github.com/agent0ai/code-execution-mcp.git
cd </path/to>/code-execution-mcp

# Install dependencies
pip install -e .

and run with config:

{
  "mcpServers": {
    "code-execution-mcp": {
      "command": "python",
      "args": ["</path/to/code-execution-mcp>/main.py"]
    }
  }
}

Available Tools

execute_terminal

Execute a terminal command in the specified session.

Parameters:

  • command (string, required): The shell command to execute
  • session (integer, optional): Session (terminal window) number (default: 0)

Output:

  • (string) The accumulated terminal output from the session

execute_python

Execute Python code via IPython in the specified session.

Parameters:

  • code (string, required): The Python code to execute
  • session (integer, optional): Session (terminal window) number (default: 0)

Output:

  • (string) The accumulated IPython output from the session

get_output

Get accumulated output from a terminal session.

Parameters:

  • session (integer, optional): Session (terminal window) number (default: 0)

Output:

  • (string) The accumulated terminal output from the session

reset_terminal

Reset a terminal session, closing and reopening it.

Parameters:

  • session (integer, optional): Session (terminal window) number (default: 0)
  • reason (string, optional): Reason for the reset

Output:

  • (string) Text confirmation for the agent

Session Management

  • Sessions (terminal instances) allow maintaining separate execution contexts for multitasking, persistence or context isolation
  • Each session can be used and reset individually
  • Sessions persist until reset
  • Session 0 is default
  • Any session number can be used

Virtual Environment Considerations

Important: When the MCP server is launched from a virtual environment, shell sessions may NOT automatically inherit the venv activation.

Solution: Use init commands to explicitly activate your virtual environment:

{
  "env": {
    "CODE_EXEC_INIT_COMMANDS": "source /path/to/venv/bin/activate"
  }
}

Platform Support

  • Linux: Fully tested and supported
  • macOS: Fully tested and supported
  • Windows: Experimental support via pywinpty
    • Some features may behave differently

Architecture

This MCP server is a minimal wrapper around Agent Zero's code execution tool:

  • Preserves Agent Zero's battle-tested logic
  • No rewrites or reimplementations
  • Uses Agent Zero's helper modules unchanged:
    • tty_session.py - TTY session management
    • shell_local.py - Local shell interface
    • print_style.py - Output styling and logging
    • strings.py - String manipulation utilities

Security

WARNING: This MCP server allows full code execution on the host system. Security is the responsibility of the MCP client.

Only use with trusted AI agents and in controlled environments.

License

MIT License

This project wraps and reuses code from Agent Zero (Copyright (c) 2025 Agent Zero, s.r.o), which is licensed under the MIT License.

See the LICENSE file for full license text and attribution details.

Credits

Built on Agent Zero's proven code execution implementation.

This MCP server preserves and reuses Agent Zero's battle-tested code:

  • Core execution logic from code_execution_tool.py
  • Helper modules: tty_session.py, shell_local.py, print_style.py, strings.py
  • All system message prompts

All credit for the robust code execution implementation goes to the Agent Zero team.

Uses FastMCP for MCP protocol handling.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured