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README.md

@@ -9,12 +9,40 @@ app_file: app.py
 pinned: false
 license: mit
 short_description: creates a venv, install dependencies and run your script
-tag: mcp-server-track
 ---
 
 ## run_my_script
 
-test script:
+
+Executes a user-provided self contained Python script inside an isolated virtual environment with automatic dependency management.
+
+This function is intended to serve as a backend execution engine in a Model Context Protocol (MCP) server setting,
+where a language model may submit scripts for evaluation. It creates a secure workspace, detects dependencies,
+installs them using `uv`, executes the script, captures its output (including stdout and generated files), and
+returns all relevant results. 
+
+⚠️ Limitations & Guidance for mcp server Use:
+- Scripts should be self-contained, avoid system-level access, and primarily focus on data processing, text generation,
+  visualization, or machine learning tasks.
+- The code can output logs, JSON, images, CSVs, or any other files, which are returned as artifacts.
+- Avoid infinite loops or long-running background processes. Timeout support can be added externally.
+
+Args:
+    code (str): The Python script to execute. Should include all import statements and logic. 
+      
+    user_input (str, optional): A string input available to the script via the SCRIPT_INPUT environment variable. 
+        Can be plain text, JSON, Markdown, or even base64-encoded images.
+
+Returns:
+    Tuple[str, Dict[str, str], str]:
+        - logs (str): Full stdout and stderr logs of the executed script.
+        - artifacts (Dict[str, str]): A dictionary of output files with their names and summaries or indicators 
+          (e.g., image or CSV placeholders). Includes a "__workdir__" key pointing to the working directory.
+        - zip_path (str): Path to a ZIP archive containing all output artifacts for download.
+
+
+
+**test script:**
 ```python
 import os
 import base64
@@ -43,7 +71,7 @@ flipped.save(os.path.join(output_path, "flipped.png"))
 print("Image flipped and saved as flipped.png.")
 ```
 
-input:
+**test input:**
 ```json
 {
   "img": "iVBORw0KGgoAAAANSUhEUgAAAQAAAAEACAIAAADTED8xAAADMElEQVR4nOzVwQnAIBQFQYXff81RUkQCOyDj1YOPnbXWPmeTRef+/3O/OyBjzh3CD95BfqICMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMK0CMO0TAAD//2Anhf4QtqobAAAAAElFTkSuQmCC"

app.py

@@ -60,6 +60,54 @@ def zip_artifacts(output_dir: Path, zip_path: Path):
 
 
 def run_script(code: str, user_input: str = "", cleanup_enabled: bool = True, cleanup_after: int = 600):
+    """
+    Executes a user-provided self contained Python script inside an isolated virtual environment with automatic dependency management.
+
+    This function is intended to serve as a backend execution engine in a Model Context Protocol (MCP) server setting,
+    where a language model may submit scripts for evaluation. It creates a secure workspace, detects dependencies,
+    installs them using `uv`, executes the script, captures its output (including stdout and generated files), and
+    returns all relevant results. 
+
+    ⚠️ Limitations & Guidance for LLM-based Use:
+    - Scripts should be self-contained, avoid system-level access, and primarily focus on data processing, text generation,
+      visualization, or machine learning tasks.
+    - The code can output logs, JSON, images, CSVs, or any other files, which are returned as artifacts.
+    - Avoid infinite loops or long-running background processes. Timeout support can be added externally.
+
+    Args:
+        code (str): The Python script to execute. Should include all import statements and logic. 
+            Example:
+                ```python
+                import json
+                import os
+                input_path = os.environ["SCRIPT_INPUT"]
+                with open(input_path) as f:
+                    data = json.load(f)
+                print("Processed:", data["name"])
+                ```
+
+        user_input (str, optional): A string input available to the script via the SCRIPT_INPUT environment variable. 
+            Can be plain text, JSON, Markdown, or even base64-encoded images.
+            Example:
+                ```json
+                {"img": "base64string..."}
+                ```
+
+        cleanup_enabled (bool, optional): 
+            Whether to automatically delete old execution directories.
+
+        cleanup_after (int, optional): 
+            Number of seconds after which completed runs should be deleted, if cleanup is enabled.
+
+    Returns:
+        Tuple[str, Dict[str, str], str]:
+            - logs (str): Full stdout and stderr logs of the executed script.
+            - artifacts (Dict[str, str]): A dictionary of output files with their names and summaries or indicators 
+              (e.g., image or CSV placeholders). Includes a "__workdir__" key pointing to the working directory.
+            - zip_path (str): Path to a ZIP archive containing all output artifacts for download.
+    """
+
+    
     base_dir = Path("./script_runs")
     base_dir.mkdir(exist_ok=True)
     if cleanup_enabled: