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blas0

code2mcp

by blas0
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TypeScript
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The single tool 'execute_code' has a clearly distinct purpose: executing TypeScript code with access to MCP tool APIs. Since there is only one tool, there is no ambiguity or overlap with other tools. The tool's description is specific and focused on code execution within a sandbox environment.

    Naming Consistency5/5

    With only one tool named 'execute_code', naming consistency is inherently perfect. The tool follows a clear verb_noun pattern (execute_code), and there are no other tools to compare or create inconsistencies with.

    Tool Count2/5

    The server has only one tool, which feels too thin for its apparent scope. The tool description mentions access to multiple MCP tool APIs (context7, playwright, chrome-devtools), suggesting a broader purpose of code execution with various integrations, but the tool surface is limited to a single generic execution tool. This could lead to agent confusion or inefficiency in handling specific tasks.

    Completeness2/5

    The server is severely incomplete for its implied domain. While 'execute_code' provides a generic execution capability, there are no dedicated tools for common operations like listing available APIs, managing the sandbox environment, or handling errors. The tool relies on embedded API calls within code, which may cause gaps in agent workflows and reduce usability for specific tasks.

  • Average 4.2/5 across 1 of 1 tools scored.

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

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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

  • Behavior5/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It excellently describes the sandbox environment constraints (no network/filesystem access, only MCP APIs), how console.log output is returned, and that intermediate data stays in the sandbox. It also details the available MCP APIs (context7, playwright, chrome-devtools) with their specific functions and parameters, providing rich behavioral context beyond basic execution.

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

    Conciseness2/5

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

    The description is extremely long (over 1500 words) and not front-loaded. While it contains valuable information, much of it (like detailed API listings with parameters) could be better presented elsewhere. The core purpose is buried among extensive API documentation. It lacks efficient structure and contains significant redundancy in parameter listings that don't directly serve the tool's description purpose.

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

    Completeness5/5

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

    For a complex tool with no annotations and no output schema, the description provides exceptional completeness. It covers execution environment constraints, available APIs with detailed functions, examples of usage patterns, data flow considerations, and security boundaries. Given the tool's complexity and lack of structured metadata, this description gives the agent everything needed to understand how to use the tool effectively.

    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 input schema has 100% description coverage, clearly documenting both parameters. The description doesn't add any additional semantic information about the 'code' or 'timeout' parameters beyond what the schema provides. It focuses on behavioral aspects and API details instead. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't enhance parameter understanding but doesn't need to compensate for gaps.

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

    Purpose5/5

    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 TypeScript code with access to MCP tool APIs.' It specifies the language (TypeScript), the execution environment (sandbox), and the key capability (access to MCP tool APIs). This is specific, distinguishes it from any hypothetical siblings, and goes beyond just restating the name.

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

    Usage Guidelines4/5

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

    The description provides clear context for when to use this tool: for executing TypeScript code in a sandbox with MCP API access. It includes examples of single calls and multi-step workflows. However, it doesn't explicitly state when NOT to use it or mention alternatives, as there are no sibling tools provided. The guidance is comprehensive within its scope but lacks comparative exclusion criteria.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
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  • Evaluate tool definition quality.

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