MCP Code Executor
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CONDA_ENV_NAME | Yes | The name of the Conda environment you want the code to run in | |
| CODE_STORAGE_DIR | Yes | The directory where you want the generated code to be stored |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| execute_codeA | Execute Python code in the conda environment. For short code snippets only. For longer code, use initialize_code_file and append_to_code_file instead. |
| initialize_code_fileA | Create a new Python file with initial content. Use this as the first step for longer code that may exceed token limits. Follow with append_to_code_file for additional code. |
| append_to_code_fileA | Append content to an existing Python code file. Use this to add more code to a file created with initialize_code_file, allowing you to build up larger code bases in parts. |
| execute_code_fileA | Execute an existing Python file. Use this as the final step after building up code with initialize_code_file and append_to_code_file. |
| read_code_fileA | Read the content of an existing Python code file. Use this to verify the current state of a file before appending more content or executing it. |
| install_dependenciesC | Install Python dependencies in the conda environment |
| check_installed_packagesC | Check if packages are installed in the conda environment |
| configure_environmentC | Change the environment configuration settings |
| get_environment_configB | Get the current environment configuration |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Each tool has a clearly distinct purpose with no ambiguity. For example, initialize_code_file, append_to_code_file, and read_code_file handle different file operations, while execute_code and execute_code_file target different execution methods. The descriptions explicitly differentiate tools like execute_code (for short snippets) versus the file-based workflow.
All tool names follow a consistent verb_noun pattern using snake_case, such as append_to_code_file, check_installed_packages, and configure_environment. There are no deviations in naming style or convention across the set, making them predictable and readable.
With 9 tools, the count is well-scoped for a code execution server. Each tool earns its place by covering distinct aspects like file management, environment configuration, dependency handling, and code execution, without being overly sparse or bloated.
The tool set provides complete coverage for the code execution domain, including CRUD-like operations for files (initialize, append, read), environment management (configure, get config, install dependencies), and execution (code snippets, files). There are no obvious gaps, and the workflow from file creation to execution is fully supported.