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philschmid

Code Sandbox MCP Server

by philschmid
OverviewSchemaRelated ServersScoreDiscussions
Python

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    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.

    Naming Consistency5/5

    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.

    Tool Count2/5

    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.

    Completeness2/5

    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.

  • Average 3.3/5 across 2 of 2 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • No commit activity data available
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

  • Behavior2/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description carries the full burden. It mentions the sandbox environment and capture of output/error, but lacks details on execution limits, security implications, error handling, or what the sandbox entails. For a code execution tool with zero annotation coverage, this is insufficient behavioral disclosure.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence with no wasted words. It front-loads the core action and key details, making it easy to parse quickly.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness3/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (code execution), lack of annotations, and presence of an output schema, the description is minimally adequate. It covers the basic purpose and output capture but misses critical behavioral aspects like safety, limits, and comparison to siblings. The output schema likely handles return values, reducing the burden here.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema description coverage is 100%, so the schema already documents the 'code' parameter fully. The description adds that included libraries are '@google/genai', which provides some context beyond the schema, but doesn't elaborate on syntax, supported features, or other libraries. Baseline 3 is appropriate as the schema does most of the work.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the action ('Execute JavaScript code') and the environment ('in the sandbox environment'), and specifies what it captures ('standard output and error'). It distinguishes from the sibling 'run_python_code' by specifying JavaScript, but doesn't explicitly contrast them. The purpose is specific and actionable.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives like 'run_python_code', nor does it mention any prerequisites, constraints, or typical use cases. It simply states what the tool does without context for selection.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden. It discloses key behavioral traits: execution in a 'sandbox environment' (implying isolation/safety) and capture of 'standard output and error'. However, it lacks details on execution limits, timeouts, memory constraints, security implications, or response format beyond capture. The description adds value but is incomplete for a code execution tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness5/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is a single, efficient sentence with zero waste. It is front-loaded with the core action and environment, making it easy to parse. Every word earns its place without redundancy or fluff.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the tool's complexity (code execution), no annotations, and an output schema present (which covers return values), the description is reasonably complete. It specifies the sandbox environment and capture behavior, which are critical for understanding. However, it lacks details on execution constraints and security, leaving some gaps for a potentially risky operation.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters3/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 100%, with the parameter 'code' fully documented in the schema (including available libraries). The description adds no additional parameter semantics beyond what the schema provides, such as code length limits or syntax requirements. Baseline 3 is appropriate as the schema does the heavy lifting.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose4/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description clearly states the tool's purpose: 'Execute Python code in the sandbox environment and captures the standard output and error.' It specifies the verb ('execute'), resource ('Python code'), and environment ('sandbox'), but doesn't explicitly differentiate from its sibling 'run_javascript_code' beyond the language name.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'run_javascript_code' or any other alternatives, nor does it specify prerequisites, constraints, or typical use cases. Usage is implied by the language name only.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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