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sinch

Sinch MCP Server

Official
by sinch

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a single, clear purpose described in its name and description.

    Naming Consistency5/5

    The single tool name follows a consistent pattern of 'sinch-mcp-configuration', which is descriptive and aligns with the server's purpose. There are no other tools to compare against, so consistency is inherently perfect.

    Tool Count2/5

    A single tool for a server named 'Sinch MCP Server' suggests a very limited scope. While it might be appropriate for a minimal configuration server, it feels thin and underdeveloped for a general-purpose server, indicating potential gaps in functionality.

    Completeness1/5

    The tool only provides configuration retrieval, which is a meta-operation about the server itself. There are no tools for actual Sinch-related operations (e.g., sending messages, managing contacts), making the surface severely incomplete for any practical use case beyond server introspection.

  • Average 3.5/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 76 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 Apache 2.0.

  • 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

  • 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 discloses that the tool retrieves configuration and troubleshooting data, implying it's a read-only operation without side effects. However, it doesn't specify behavioral traits like rate limits, authentication needs, or response format, leaving gaps in transparency.

    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 and front-loaded, stating the main purpose in the first sentence and adding useful details in the second. Both sentences earn their place by clarifying the tool's function and output, with no wasted words or unnecessary elaboration.

    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 simplicity (0 parameters, no annotations, no output schema), the description is adequate but has gaps. It explains what the tool does and the type of information returned, but without an output schema, it doesn't detail the structure or format of the configuration data, which could hinder agent understanding.

    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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, and it appropriately focuses on the tool's purpose without redundant information, meeting the baseline for no parameters.

    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: 'retrieve the configuration of the Sinch MCP server' with specific details about what information is provided ('which tools are enabled and disabled with some troubleshooting information'). It distinguishes itself by focusing on server configuration rather than performing operations, though there are no sibling tools for comparison.

    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 implies usage context by mentioning 'troubleshooting information about why a tool would be disabled,' suggesting it should be used for diagnostic purposes. However, it lacks explicit guidance on when to use this tool versus alternatives or any prerequisites, as there are no sibling tools to compare against.

    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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  • Evaluate tool definition quality.

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