Code Sandbox MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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 |
|---|---|
| run_python_codeB | Execute Python code in the sandbox environment and captures the standard output and error. |
| run_javascript_codeB | Execute JavaScript code in the sandbox environment and captures the standard output and error. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| environment_details | Resource containing detailed information about the environments. Returns: str: The details of the languages |
TDQS
Scored across 2 tools
The two tools are perfectly distinct, each targeting a different programming language (JavaScript vs Python) with identical functionality otherwise. There is no overlap or ambiguity in purpose, making tool selection straightforward for an agent.
Both tools follow a consistent verb_noun pattern ('run_javascript_code' and 'run_python_code'), using the same verb 'run' and structured noun phrases. This predictability enhances readability and usability.
With only two tools, the server feels under-scoped for a 'Code Sandbox' purpose, as it lacks support for other common languages (e.g., Java, C++, Ruby) or additional sandbox operations (e.g., managing files, setting timeouts). This minimal set limits functionality and may require agents to work around gaps.
The tool surface is severely incomplete for a code sandbox domain, covering only JavaScript and Python execution. Missing are tools for other languages, code analysis, input/output handling, or environment configuration, which are typical for such systems, leading to potential agent failures in broader tasks.