
Python REPL
Runs Python code interactively within conversations, maintaining separate session state so variables and imports persist across executions.
Provides an interactive Python REPL environment for executing code within conversations, maintaining separate state for each session and supporting both expressions and statements.
What it does
- Execute Python code snippets
- Maintain persistent session state
- Capture stdout and stderr output
- View session execution history
- Run both expressions and statements
- Manage multiple separate sessions
Best for
About Python REPL
Python REPL is a community-built MCP server published by alec2435 that provides AI assistants with tools and capabilities via the Model Context Protocol. Use our online run python code tool to execute Python code online in an interactive REPL environment. Maintain session s It is categorized under developer tools.
How to install
You can install Python REPL in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
Python REPL is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
python_local MCP Server
An MCP Server that provides an interactive Python REPL (Read-Eval-Print Loop) environment.
Components
Resources
The server provides access to REPL session history:
- Custom
repl://URI scheme for accessing session history - Each session's history can be viewed as a text/plain resource
- History shows input code and corresponding output for each execution
Tools
The server implements one tool:
python_repl: Executes Python code in a persistent session- Takes
code(Python code to execute) andsession_idas required arguments - Maintains separate state for each session
- Supports both expressions and statements
- Captures and returns stdout/stderr output
- Takes
Configuration
Install
Claude Desktop
On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
Development/Unpublished Servers Configuration
```json "mcpServers": { "python_local": { "command": "uv", "args": [ "--directory", "/path/to/python_local", "run", "python_local" ] } } ```Published Servers Configuration
```json "mcpServers": { "python_local": { "command": "uvx", "args": [ "python_local" ] } } ```Development
Building and Publishing
To prepare the package for distribution:
- Sync dependencies and update lockfile:
uv sync
- Build package distributions:
uv build
This will create source and wheel distributions in the dist/ directory.
- Publish to PyPI:
uv publish
Note: You'll need to set PyPI credentials via environment variables or command flags:
- Token:
--tokenorUV_PUBLISH_TOKEN - Or username/password:
--username/UV_PUBLISH_USERNAMEand--password/UV_PUBLISH_PASSWORD
Debugging
Since MCP servers run over stdio, debugging can be challenging. For the best debugging experience, we strongly recommend using the MCP Inspector.
You can launch the MCP Inspector via npm with this command:
npx @modelcontextprotocol/inspector uv --directory /path/to/python_local run python-local
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
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