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ashizam

Telegram Pager MCP Server

by ashizam
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools.

    Naming Consistency5/5

    The single tool uses a clear verb_noun pattern (send_telegram_message), which is consistent and predictable.

    Tool Count3/5

    One tool is borderline for the 'Telegram Pager' purpose; while it could be sufficient for a narrowly scoped paging server, it feels thin compared to typical server sizes.

    Completeness2/5

    The server only supports sending messages, lacking any other operations like checking delivery status or managing contacts, which are significant gaps for a Telegram integration.

  • Average 3.1/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 15 commits in the last 12 weeks
    • No stable releases found
    • 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.

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

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  ]
}

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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 bears full responsibility for behavioral disclosure. It only states the basic action without any details about side effects, rate limits, error handling, or return values. The agent gains little insight into what happens beyond the call.

    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 two sentences long, with the first sentence stating the purpose and the second adding a critical usage note. No unnecessary words, and the most important information is front-loaded.

    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?

    The tool is simple with only two parameters, and there are no siblings to compare against. However, the description omits any mention of return values or behavior (even though an output schema exists but is not shown). It is adequate for a basic action but lacks completeness for an agent to predict outcomes.

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

    Parameters2/5

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

    The input schema has 0% description coverage, meaning no parameter descriptions exist. The tool description adds value for the 'username' parameter by specifying the format (no '@'), but does not explain 'message' or provide any other semantic details. This is minimal compensation for the schema gap.

    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 action ('Send a direct message') and the target ('a Telegram user'). The verb and resource are specific, and there are no sibling tools to differentiate, so it's adequately clear for the given context.

    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 provides a practical guideline about not using the '@' symbol in the username, which helps avoid common errors. However, it does not offer guidance on when to use this tool versus other potential alternatives (none listed) or any prerequisites.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

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