Python Exec Sandbox vs Claude Task Master
A side-by-side look at the Python Exec Sandbox and Claude Task Master MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Python Exec Sandbox for code execution work as a local process; choose Claude Task Master for developer tools as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Python Exec Sandbox when
- You need dedicated capabilities in the Code Execution domain.
- You prefer a local stdio subprocess transport.
- You want tools like
execute_python, check_environment, validate_script.
Choose Claude Task Master when
- You need dedicated capabilities in the Developer Tools domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY, PERPLEXITY_API_KEY, XAI_API_KEY, OPENROUTER_API_KEY, MISTRAL_API_KEY, TASK_MASTER_TOOLS.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Code Execution | Developer Tools |
| Quality signal | 52/100 · Good | 61/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | API key required |
| Pricing | Not declared | BYOK (pay the provider) |
| Required env vars | None listed | ANTHROPIC_API_KEYOPENAI_API_KEYGOOGLE_API_KEYPERPLEXITY_API_KEYXAI_API_KEYOPENROUTER_API_KEYMISTRAL_API_KEYTASK_MASTER_TOOLS |
| Verified owner | Community listing | Community listing |
| GitHub stars | 1 | 28,266 |
| Directory activity | 2 views 0 installs 0 upvotes | 10 views 0 installs 0 upvotes |
| Tools | 3 | Not listed |
| Full listing | View Python Exec Sandbox | View Claude Task Master |
Tools & capabilities
Python Exec Sandbox tools 3
execute_pythonExecute a Python script with automatic dependency management. The script can include PEP 723 inline metadata (# /// script blocks) for declaring dependencies. Additional dependencies can also be passed via the dependencies parameter and will be merged. Args: script: Python source code to execute. May include PEP 723 metadata. dependencies: Extra PEP 508 dependency specifiers to make available. timeout_seconds: Maximum execution time (1-300, default 30). Returns: Formatted output with stdout, stderr, exit code, and duration. Example - simple script: execute_python(script="print('hello')") Example - with dependencies parameter: execute_python( script="import requests; print(requests.get('https://example.com').status_code)", dependencies=["requests>=2.32"] ) Example - with inline dependency metadata (preferred for multiple deps): execute_python(script=''' # /// script # dependencies = ["pandas>=2.2", "numpy>=1.26"] # /// import pandas as pd import numpy as np print(pd.DataFrame({"a": np.arange(5)}).describe()) ''') Always pin dependency versions (e.g. "pandas>=2.2" instead of "pandas") for reproducible results. The inline metadata block (# /// script ... # ///) is the recommended way to declare dependencies directly in the script (see PEP 723: https://peps.python.org/pep-0723/). The dependencies parameter is a simpler alternative when you just need to add a few packages. Both accept standard pip-style version specifiers like "requests>=2.28" or "pandas" (see PEP 508: https://peps.python.org/pep-0508/).check_environmentCheck the execution environment and report status. Returns information about Python version, uv version, platform, sandbox configuration, and cache status.validate_scriptValidate a Python script's PEP 723 metadata and dependencies without executing it. Checks metadata syntax, dependency format, and requires-python compatibility. Args: script: Python source code to validate. May include inline dependency metadata (# /// script blocks, see https://peps.python.org/pep-0723/). dependencies: Extra dependency specifiers to validate, using standard pip-style format like "requests>=2.28" (see https://peps.python.org/pep-0508/). Returns: Validation result with metadata details or error information.
Claude Task Master tools
No tool names declared yet. Check the project README from the listing page.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Python Exec Sandbox
{
"mcpServers": {
"python-exec-sandbox": {
"command": "uvx",
"args": [
"mcp-python-exec-sandbox"
]
}
}
}
Claude Task Master
{
"mcpServers": {
"eyaltoledano-claude-task-master": {
"command": "npx",
"args": [
"-y",
"task-master-ai"
],
"env": {
"ANTHROPIC_API_KEY": "YOUR_ANTHROPIC_API_KEY_HERE",
"OPENAI_API_KEY": "YOUR_OPENAI_API_KEY_HERE",
"GOOGLE_API_KEY": "YOUR_GOOGLE_API_KEY_HERE",
"PERPLEXITY_API_KEY": "YOUR_PERPLEXITY_API_KEY_HERE",
"XAI_API_KEY": "YOUR_XAI_API_KEY_HERE",
"OPENROUTER_API_KEY": "YOUR_OPENROUTER_API_KEY_HERE",
"MISTRAL_API_KEY": "YOUR_MISTRAL_API_KEY_HERE",
"TASK_MASTER_TOOLS": "YOUR_TASK_MASTER_TOOLS_HERE"
}
}
}
}
Frequently asked questions
Python Exec Sandbox is categorized under Code Execution and uses a local stdio subprocess. Claude Task Master belongs to Developer Tools and uses a local stdio subprocess. Pick Python Exec Sandbox for code execution work and Claude Task Master for developer tools.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Python Exec Sandbox has no declared pricing — check the project's own site. Claude Task Master is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add python-exec-sandbox and eyaltoledano-claude-task-master as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Python Exec Sandbox has a quality signal of 52/100 (Good) with 2 views, 0 installs and 1 GitHub stars. Claude Task Master has 61/100 (Good) with 10 views, 0 installs and 28,266 GitHub stars.