MCP Run Python vs SandboxAPI
A side-by-side look at the MCP Run Python and SandboxAPI MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose MCP Run Python for code execution work as a local process; choose SandboxAPI for code execution over a hosted endpoint. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose MCP Run Python when
- You need dedicated capabilities in the Code Execution domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
Choose SandboxAPI when
- You need dedicated capabilities in the Code Execution domain.
- You prefer a remote HTTP/SSE transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
SANDBOXAPI_API_KEY, MCP_API_KEY, MCP_PORT, SANDBOXAPI_URL. - You want tools like
execute_code, execute_batch, list_languages.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Code Execution | Code Execution |
| Quality signal | 48/100 · Fair | 49/100 · Fair |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Remote HTTP/SSE |
| Auth | No auth required | API key required |
| Pricing | Free | BYOK (pay the provider) |
| Required env vars | None listed | SANDBOXAPI_API_KEYMCP_API_KEYMCP_PORTSANDBOXAPI_URL |
| Verified owner | Community listing | Community listing |
| GitHub stars | 20,470 | 2 |
| Directory activity | 2 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | Not listed | 3 |
| Full listing | View MCP Run Python | View SandboxAPI |
Tools & capabilities
MCP Run Python tools
No tool names declared yet. Check the project README from the listing page.
SandboxAPI tools 3
execute_codeExecute code in a sandboxed container.execute_batchExecute multiple code snippets. Each runs in its own isolated sandbox.list_languagesList all supported programming languages with versions and example code. No parameters.
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.
MCP Run Python
{
"mcpServers": {
"pydantic-pydantic-ai-mcp-run-python": {
"command": "uvx",
"args": [
"--with",
"pydantic-ai-harness",
"clai"
]
}
}
}
SandboxAPI
{
"mcpServers": {
"sandboxapi": {
"url": "https://mcp.sandboxapi.dev/mcp"
}
}
}
Frequently asked questions
MCP Run Python is categorized under Code Execution and uses a local stdio subprocess. SandboxAPI belongs to Code Execution and uses a remote HTTP/SSE transport. Pick MCP Run Python for code execution work and SandboxAPI for code execution.
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.
MCP Run Python is listed as free. Auth: no auth required. SandboxAPI 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 pydantic-pydantic-ai-mcp-run-python and sandboxapi as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, MCP Run Python has a quality signal of 48/100 (Fair) with 2 views, 0 installs and 20,470 GitHub stars. SandboxAPI has 49/100 (Fair) with 3 views, 0 installs and 2 GitHub stars.