官方说明> PRIMS – Python Runtime Interpreter MCP Server PRIMS is a tiny open-source **Model Context Protocol (MCP)** server that lets LLM agents run arbitrary Python code in a secure, throw-away sandbox.
PRIMS is a tiny open-source **Model Context Protocol (MCP)** server that lets LLM agents run arbitrary Python code in a secure, throw-away sandbox. • **One tool, one job.** Exposes a single MCP tool – run_code – that executes user-supplied Python and streams back stdout / stderr. • **Isolated & reproducible.** Each call spins up a fresh virtual-env, installs any requested pip packages, mounts optional read-only files, then nukes the workspace. • **Zero config.** Works over MCP/stdio or drop it in Docker. --- Quick-start 1. Local development environment 2. Launch the server 3. Docker Examples List available tools You can use the provided script to list all tools exposed by the server: Expected output (tool names and descriptions may vary): Run code via the MCP server Mount a dataset once & reuse it This mounts a CSV with mount_file and then reads it inside run_code without re-supplying the URL. Inspect your session workspace This shows how to use the **list_dir** and **preview_file** tools to browse files your code created. Persist an artifact to permanent storage The **persist_artifact** tool uploads a file from your output/ directory to a presigned URL. Example (Python): Download an artifact Small artifacts can be fetched directly: --- Available tools | Tool | Purpose | |---------------------|---------------------------------------------------------------| | run_code | Execute Python in an isolated sandbox with optional pip deps. | | list_dir | List files/directories inside your session workspace. | | preview_file | Return up to 8 KB of a text file for quick inspection. | | persist_artifact | Upload an output/ file to a client-provided presigned URL. | | mount_file | Download a remote file once per session to mounts/ . | See the examples/ directory for end-to-end demos. Contributing Contributions are welcome! Feel free to open issues, suggest features, or submit pull requests to help improve PRIMS.