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MasonChow

Source Map Parser MCP Server

by MasonChow
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.6.0

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: lookup_context maps a single position to source context, parse_stack processes multiple stack entries, and unpack_sources extracts all source files. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: lookup_context, parse_stack, unpack_sources. The naming is predictable and easy to understand.

    Tool Count4/5

    With 3 tools, the server is focused and each tool serves a core need in source map parsing. While the count is small, it is appropriate for the domain; adding a validation or metadata tool could be beneficial but not necessary.

    Completeness4/5

    The toolset covers the primary tasks: single position mapping, stack trace parsing, and source extraction. Minor gaps exist (e.g., no direct source map metadata or validation), but the core functionality is well-covered.

  • Average 3.6/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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

  • Behavior3/5

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

    No annotations are provided, so the description bears the full burden. It mentions the return value includes a JSON object or null if unmappable, but does not disclose side effects, authentication needs, or error handling behavior for invalid input or network issues.

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

    Conciseness4/5

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

    The description is concise, well-structured with markdown headings and a clear list of parameters. Every sentence adds value, though the parameter descriptions could be omitted since they duplicate the schema.

    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?

    For a simple lookup tool without output schema, the description adequately covers purpose, parameters, and return behavior including null case. It lacks error scenarios and relation to sibling tools, but is sufficient for basic usage.

    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 coverage is 100% with parameter descriptions. The tool description largely repeats those descriptions but adds the default value for contextLines and includes a Returns section not present in the schema. It adds minimal new meaning beyond the schema.

    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 looks up original source code context for a specific line and column in compiled code. It identifies the exact action and resource, and implicitly distinguishes from siblings like parse_stack and unpack_sources through its unique focus on source map lookups.

    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 its siblings (parse_stack, unpack_sources). It doesn't mention any context or prerequisites, leaving the agent without clear decision criteria for tool 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?

    No annotations are provided, so the description carries the full burden. It describes the return format and error handling, but does not disclose any behavioral traits like side effects, rate limits, or authentication requirements. The description is adequate but not rich.

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

    Conciseness4/5

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

    The description is well-structured with a header, explanation, parameter list, and return section. It is somewhat verbose but each part contributes to clarity. It is front-loaded with the purpose, making it easy to scan.

    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 lack of annotations and output schema, the description covers the tool's purpose, parameters, return values, and error behavior. It is missing explicit usage guidelines and a note on sibling differentiation, but overall provides sufficient context for an agent to use the tool effectively.

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

    Parameters4/5

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

    The input schema provides descriptions for all three fields in stacks, giving high coverage. The description adds value by explaining the optional 'ctxOffset' parameter and its default, which is not present in the schema. This enriches understanding beyond the schema alone.

    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 parses error stack traces using source maps to map to source code locations. It is specific and distinct from the sibling tools 'lookup_context' and 'unpack_sources', but does not explicitly differentiate itself.

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

    Usage Guidelines3/5

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

    The description explains what the tool does and its parameters, but it does not provide explicit guidance on when to use this tool versus the siblings or what prerequisites are needed. Usage is implied rather than stated.

    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?

    No annotations provided, so description carries full burden. It explains the output format (JSON with sources, sourceRoot, etc.) but does not mention side effects, permissions, error handling, or rate limits. For a read-only tool, this is adequate but minimal.

    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?

    Very concise: one heading, a brief description, and a bulleted return list. Every sentence adds value. Information is front-loaded and well-organized.

    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?

    Given no output schema, the description fully explains the return format. The single parameter is described. The tool is simple and the description is complete for an agent to understand and invoke it correctly.

    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 coverage is 100% with one parameter, and the description restates 'sourceMapUrl' but adds no extra meaning beyond the schema. However, it does detail the return structure, which adds context. Baseline 3 is appropriate.

    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 it extracts all source files and content from a source map, using specific verb 'extract' and resource 'source map sources'. It distinguishes from siblings like 'lookup_context' and 'parse_stack' by focusing on source map unpacking.

    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?

    No guidance on when to use this tool versus alternatives. Description lacks context about prerequisites, limitations, or when not to use it. Sibling tools are not compared.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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