added venv, venv-uv env support and some more tools to let LLM install missing dependencies just in case

Author: jefcoder

README.md

@@ -1,21 +1,26 @@
 # MCP Code Executor
 [![smithery badge](https://smithery.ai/badge/@bazinga012/mcp_code_executor)](https://smithery.ai/server/@bazinga012/mcp_code_executor)
 
-The MCP Code Executor is an MCP server that allows LLMs to execute Python code within a specified Conda environment. This enables LLMs to run code with access to libraries and dependencies defined in the Conda environment.
+The MCP Code Executor is an MCP server that allows LLMs to execute Python code within a specified Python environment. This enables LLMs to run code with access to libraries and dependencies defined in the environment.
 
 <a href="https://glama.ai/mcp/servers/45ix8xode3"><img width="380" height="200" src="https://glama.ai/mcp/servers/45ix8xode3/badge" alt="Code Executor MCP server" /></a>
 
 ## Features
 
 - Execute Python code from LLM prompts
-- Run code within a specified Conda environment 
+- Run code within a specified environment (Conda, virtualenv, or UV virtualenv)
+- Install dependencies when needed
+- Check if packages are already installed
+- Dynamically configure the environment at runtime
 - Configurable code storage directory
 
 ## Prerequisites
 
 - Node.js installed
-- Conda installed
-- Desired Conda environment created
+- One of the following:
+  - Conda installed with desired Conda environment created
+  - Python virtualenv
+  - UV virtualenv
 
 ## Setup
 
@@ -57,24 +62,101 @@ To configure the MCP Code Executor server, add the following to your MCP servers
       ],
       "env": {
         "CODE_STORAGE_DIR": "/path/to/code/storage",
+        "ENV_TYPE": "conda",
         "CONDA_ENV_NAME": "your-conda-env"
       }
     }
   }
 }
 ```
 
-Replace the placeholders:
-- `/path/to/mcp_code_executor` with the absolute path to where you cloned this repository 
-- `/path/to/code/storage` with the directory where you want the generated code to be stored
-- `your-conda-env` with the name of the Conda environment you want the code to run in
+### Environment Variables
+
+#### Required Variables
+- `CODE_STORAGE_DIR`: Directory where the generated code will be stored
+
+#### Environment Type (choose one setup)
+- **For Conda:**
+  - `ENV_TYPE`: Set to `conda`
+  - `CONDA_ENV_NAME`: Name of the Conda environment to use
+
+- **For Standard Virtualenv:**
+  - `ENV_TYPE`: Set to `venv`
+  - `VENV_PATH`: Path to the virtualenv directory
+
+- **For UV Virtualenv:**
+  - `ENV_TYPE`: Set to `venv-uv`
+  - `UV_VENV_PATH`: Path to the UV virtualenv directory
+
+## Available Tools
+
+The MCP Code Executor provides the following tools to LLMs:
+
+### 1. `execute_code`
+Executes Python code in the configured environment.
+```json
+{
+  "name": "execute_code",
+  "arguments": {
+    "code": "import numpy as np\nprint(np.random.rand(3,3))",
+    "filename": "matrix_gen"
+  }
+}
+```
+
+### 2. `install_dependencies`
+Installs Python packages in the environment.
+```json
+{
+  "name": "install_dependencies",
+  "arguments": {
+    "packages": ["numpy", "pandas", "matplotlib"]
+  }
+}
+```
+
+### 3. `check_installed_packages`
+Checks if packages are already installed in the environment.
+```json
+{
+  "name": "check_installed_packages",
+  "arguments": {
+    "packages": ["numpy", "pandas", "non_existent_package"]
+  }
+}
+```
+
+### 4. `configure_environment`
+Dynamically changes the environment configuration.
+```json
+{
+  "name": "configure_environment",
+  "arguments": {
+    "type": "conda",
+    "conda_name": "new_env_name"
+  }
+}
+```
+
+### 5. `get_environment_config`
+Gets the current environment configuration.
+```json
+{
+  "name": "get_environment_config",
+  "arguments": {}
+}
+```
 
 ## Usage
 
-Once configured, the MCP Code Executor will allow LLMs to execute Python code by generating a file in the specified `CODE_STORAGE_DIR` and running it within the Conda environment defined by `CONDA_ENV_NAME`.
+Once configured, the MCP Code Executor will allow LLMs to execute Python code by generating a file in the specified `CODE_STORAGE_DIR` and running it within the configured environment.
 
 LLMs can generate and execute code by referencing this MCP server in their prompts.
 
+## Backward Compatibility
+
+This package maintains backward compatibility with earlier versions. Users of previous versions who only specified a Conda environment will continue to work without any changes to their configuration.
+
 ## Contributing
 
 Contributions are welcome! Please open an issue or submit a pull request.