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vrppaul

semantic-code-mcp

by vrppaul
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Python
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Server Quality Checklist

58%
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  • Latest release: v0.4.0

  • Disambiguation5/5

    Each tool has a distinct purpose: indexing, status checking, and searching. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: index_codebase, index_status, search_code.

    Tool Count5/5

    Three tools is well-scoped for a semantic code search server: one for building the index, one for checking its status, and one for querying it. Not too few, not too many.

    Completeness4/5

    The tools cover the core workflow (index, check, search). The search tool automatically re-indexes stale files, reducing the need for manual management. A minor gap is lack of an explicit delete or clear index tool, but it's not essential for basic usage.

  • Average 4.4/5 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 status not available

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  • 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

  • Behavior4/5

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

    With no annotations, the description discloses key behaviors: scanning Python files, extracting code elements, generating embeddings, and storing for search. It mentions incremental vs full re-indexing and returns statistics. However, it lacks warnings about prerequisites or performance impact.

    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 concise with a clear header, bullet explanation, and structured Args/Returns sections. Every sentence adds value without redundancy.

    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 presence of an output schema, the description adequately covers purpose, parameters, and behavioral nuances. It could mention that only Python files are supported and any prerequisites, but overall it is complete.

    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 description adds meaning beyond the input schema by explaining project_path as an absolute path and force as a re-index flag. Schema coverage is 0% per context, so description compensates well, though both parameters are described.

    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 indexes a codebase for semantic search, scanning Python files and extracting functions/classes/methods. This distinguishes it from siblings like 'search_code' and 'index_status'.

    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 explains when to use force=True vs incremental indexing, but does not explicitly state when not to use the tool or compare with alternatives like search_code. It provides clear context for the force parameter.

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

  • Behavior4/5

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

    The description discloses automatic indexing and re-indexing of changed files, which is a key behavioral trait. No annotations are provided, so the description handles the transparency burden well.

    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 clear sections: purpose, usage, behavioral note, args, and return. While slightly verbose in examples, every sentence adds value and it is easily scannable.

    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 complexity of semantic search with auto-indexing, the description covers purpose, usage context, parameter details, behavior, and return format. It lacks a warning about potential indexing delays but is otherwise complete.

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

    Parameters5/5

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

    The input schema has 0% description coverage, but the description explains each parameter in natural language: query as 'Natural language description,' project_path as 'Absolute path,' limit with default and maximum. This adds significant 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 performs semantic code search, distinguishes from text matching, and provides concrete examples. It differentiates from sibling tools (index_codebase, index_status) which are about indexing.

    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 advises when to use: 'when you want to find code related to a concept without knowing exact variable/function names.' It implicitly contrasts with text search but does not explicitly mention alternatives like grep. However, the guidance is sufficient.

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

  • Behavior4/5

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

    With no annotations, the description fully carries the burden. It clearly states what the tool returns and includes a note about staleness not needing manual action, implying no destructive side effects. It does not mention authentication or rate limits, but those are often implicit for read-only tools. The behavioral description is adequate for the tool's simplicity.

    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 very concise: two short sentences in the first paragraph, a one-sentence note, and an Args/Returns block that is minimal. Every element is useful, no redundant phrases. The structure is front-loaded with the purpose.

    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 has only one parameter and an output schema (though not detailed in the description), the description provides sufficient information about what the tool does and returns. The note about staleness adds valuable context. It could be slightly more precise about the return structure, but it is complete enough for typical use.

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

    Parameters5/5

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

    The input schema has one parameter (project_path) with no description beyond title and type (0% coverage). The description adds 'Absolute path to the project root directory,' providing essential semantics. This fully compensates for the lack of schema description.

    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 gets index status for a project, specifying the returned information (indexed status, last updated, files/chunks count). It distinguishes from the sibling search_code by noting that search_code automatically re-indexes stale files, implying this tool is for checking status without acting on staleness. The verb 'Get' and resource 'index status' are specific.

    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 explicitly tells when to use (to get index status) and when not to (no need to manually check staleness because search_code handles it). However, it does not provide guidance on when to use this tool versus the sibling index_codebase, which is a minor omission.

    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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