Python Code Runner
Enables execution of Python code in a safe environment, including running scripts, installing packages, and retrieving variable values. Supports file operations and package management through pip.
README
mcp-run-python-code
Python interpreter, MCP server, no API key, free. Get results from running Python code.
Overview
This MCP server provides tools for running Python code, installing packages, and executing Python files. It can be easily integrated with MCP clients, including Claude and other LLM applications supporting the MCP protocol.
Features
- Execute Python code in a safe environment
- Install Python packages using pip
- Save Python code to files and run them
- Run existing Python files
- Return specific variable values from executed code
- Error handling and debugging support
Installation
From pip
You can install the MCP Run Python Code Server using uv:
uv pip install mcp-run-python-code
Or using pip:
pip install mcp-run-python-code
From source
git clone https://github.com/shibing624/mcp-run-python-code.git
cd mcp-run-python-code
pip install -e .
Usage
Python Demo
from run_python_code import RunPythonCode
tool = RunPythonCode(base_dir='/tmp/tmp_run_code/')
# 示例1:基本代码执行
result = tool.run_python_code("x = 10\ny = 20\nz = x * y", "z")
print(f"结果: {result}") # 输出: 结果: 200
# 示例2:保存并运行文件
result = tool.save_to_file_and_run(
file_name="calc.py",
code="a = 5\nb = 15\nc = a + b",
variable_to_return="c"
)
print(f"结果: {result}") # 输出: 结果: 20
# 实例3:安装python包
result = tool.pip_install_package("requests")
print(f"结果: {result}")

Running as a standalone MCP server
Run the server with the stdio transport:
uvx mcp-run-python-code
or
uv run mcp-run-python-code
or
python -m mcp-run-python-code
Then, you can use the server with any MCP client that supports stdio transport.
Integrating with Cursor
To add the weather MCP server to Cursor, add stdio MCP with command:
uvx mcp-run-python-code
Tools available
run_python_code- Execute Python code and optionally return a variable valuesave_to_file_and_run- Save Python code to a file and execute itpip_install_package- Install Python packages using piprun_python_file- Run an existing Python file and optionally return a variable value
Examples
Example 1: Basic Code Execution
from run_python_code import RunPythonCode
tool = RunPythonCode(base_dir='/tmp/tmp_run_code/')
# Execute simple calculations
code = "result = 2 ** 10"
value = tool.run_python_code(code, "result")
print(value) # Output: 1024
Example 2: Run python File
from run_python_code import RunPythonCode
tool = RunPythonCode(base_dir='/tmp/tmp_run_code/')
# Save code to a file and run it
script_code = """
def fibonacci(n):
if n <= 1:
return n
return fibonacci(n-1) + fibonacci(n-2)
result = fibonacci(10)
print(f"Fibonacci(10) = {result}")
"""
result = tool.save_to_file_and_run("fib.py", script_code, "result")
print(result) # Output: 55
Example 3: Data Processing
from run_python_code import RunPythonCode
tool = RunPythonCode(base_dir='/tmp/tmp_run_code/')
# JSON data processing
code = """
import json
data = {'name': '张三', 'age': 30}
json_str = json.dumps(data, ensure_ascii=False)
"""
result = tool.run_python_code(code, "json_str")
print(result) # Output: {"name": "张三", "age": 30}
Contact
- Issues and suggestions:
- Email: xuming624@qq.com
- WeChat: Add me (WeChat ID: xuming624) with the message: "Name-Company-NLP" to join our NLP discussion group.
<img src="https://github.com/shibing624/weather-forecast-server/blob/main/docs/wechat.jpeg" width="200" />
License
This project is licensed under The Apache License 2.0 and can be used freely for commercial purposes.
Please include a link to the mcp-run-python-code project and the license in your product description.
Contribute
We welcome contributions to improve this project! Before submitting a pull request, please:
- Add appropriate unit tests in the
testsdirectory - Run
python -m pytestto ensure all tests pass - Submit your PR with clear descriptions of the changes
Acknowledgements
- Built with MCP Python SDK
Recommended Servers
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.
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.
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.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
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.
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.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
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.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.