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canova

Searchfox MCP Server

by canova
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TypeScript
Remote

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes: get_file retrieves specific file contents, while search_code performs code searches across repositories. There is no overlap or ambiguity between these operations, making tool selection straightforward for an agent.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun naming pattern (get_file, search_code) with clear, descriptive names that align with their functions. The naming convention is uniform and predictable throughout the set.

    Tool Count2/5

    With only two tools, the server feels severely under-scoped for a code search and exploration domain. While the tools are clear, the lack of additional operations (e.g., list repositories, browse directories, or more advanced search options) limits functionality and makes the toolset feel incomplete for typical use cases.

    Completeness2/5

    The toolset is notably incomplete for a code search server. It provides basic file retrieval and simple string search but lacks essential operations like repository listing, directory navigation, or more sophisticated search capabilities (e.g., with operators). This creates significant gaps that could hinder agent workflows in exploring or analyzing codebases.

  • Average 3.7/5 across 2 of 2 tools scored. Lowest: 2.9/5.

    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
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing

  • This repository is licensed under Apache 2.0.

  • 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

  • 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 'Get the contents' but does not disclose behavioral traits such as authentication requirements, rate limits, error handling, or whether it returns raw text or metadata. This leaves significant gaps for a tool that likely interacts with a repository system.

    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 a single, straightforward sentence that efficiently conveys the core purpose without unnecessary words. It is appropriately sized for a simple tool, though it could be slightly more structured by front-loading key details.

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

    Completeness2/5

    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 is incomplete. It does not explain what the tool returns (e.g., file content format, error responses) or address potential complexities like large files or permissions, which are critical for effective use by an AI agent.

    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 clear descriptions for 'repo' and 'path' parameters. The description adds minimal value beyond the schema, as it only reiterates that parameters specify the repository and file path without providing additional context or usage examples.

    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 verb ('Get') and resource ('contents of a specific file'), specifying the action and target. However, it does not explicitly differentiate from the sibling tool 'search_code', which likely searches for code patterns rather than retrieving a specific file's contents.

    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 is provided on when to use this tool versus alternatives like 'search_code'. The description implies usage for retrieving file contents but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage scenarios.

    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?

    Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: exact string matching only, no search operators, no OR logic, no phrase matching with quotes, and how multiple words are treated. It also implies this is a read-only operation through the search context.

    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 efficiently structured with two sentences: the first states the core purpose, and the second provides critical behavioral constraints. Every sentence earns its place by delivering essential information 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?

    For a search tool with no annotations and no output schema, the description provides good contextual completeness. It covers the search methodology constraints and basic usage guidance. The main gap is the lack of information about return format or result structure, which would be helpful given the absence of an output schema.

    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?

    With 100% schema description coverage, the schema already documents all 6 parameters thoroughly. The description adds some context about the query parameter's exact matching behavior, but doesn't provide additional semantic meaning beyond what's in the schema descriptions. This meets the baseline for high schema coverage.

    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 with specific verb ('Search for code') and resource ('in Mozilla repositories using Searchfox'). It distinguishes from the sibling tool 'get_file' by focusing on search functionality rather than file retrieval.

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

    Usage Guidelines5/5

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

    The description provides explicit guidance on when to use this tool versus alternatives: it specifies exact string matching only, warns against using multiple words expecting OR logic, and advises using separate queries or regexp mode for broader searches. This gives clear context for appropriate usage.

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

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