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edestory

StarMeet MCP Server

by edestory
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Server Quality Checklist

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

  • Latest release: v1.2.0

  • Disambiguation5/5

    Each tool covers a distinct aspect of Vedic astrology: birth chart (kundali), lunar mansion (nakshatra), and daily almanac (panchang). No overlap in purpose.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (calculate_kundali, get_nakshatra, get_panchang) with underscores and specific astrological terms.

    Tool Count4/5

    3 tools is on the lower end but appropriate for a focused Vedic astrology server covering core areas. Slightly thin but not problematic.

    Completeness2/5

    Missing key Vedic astrology features like compatibility matching, transit analysis, and full chart interpretation. The kundali tool explicitly states it's a preview, indicating significant gaps.

  • Average 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
    • 3 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

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 burden. It states the tool is a 'Preview' implying read-only, but doesn't disclose authentication needs, rate limits, or what happens on invalid input. Basic transparency is present but incomplete.

    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?

    Two sentences efficiently convey purpose, outputs, and limitations. Front-loaded with verb and resource.

    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 preview tool with 5 parameters and no output schema, the description covers inputs, outputs, and a limitation (full chart on website). It is suitable for the tool's scope, though error handling and output format are omitted.

    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%, so baseline is 3. The description adds little beyond the schema (e.g., latitude examples are in schema). It does not explain the ayanamsa options or how parameters affect the output.

    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 previews a Vedic birth chart and lists specific outputs (Lagna, Sun/Moon sign/house, Nakshatra, Dasha). It differentiates from siblings (get_nakshatra, get_panchang) by focusing on the full chart preview rather than specific elements.

    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 implies usage for a birth chart preview and notes that the full chart is available on a website, providing a boundary. However, it lacks explicit when-to-use vs siblings or when-not-to-use guidance.

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

  • Behavior2/5

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

    No annotations are provided, and the description does not disclose behavioral traits beyond the obvious read nature. It mentions data source but lacks details on authentication, rate limits, or side effects. For a simple read tool, this is acceptable 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?

    Two concise sentences: the first states purpose and return fields, the second adds data source. No unnecessary words, front-loaded with key information.

    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's simplicity (one param, read-only, no output schema), the description covers all essential aspects: input format, return fields, data source. Minor omission of spelling/sensitivity details, but examples suffice.

    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 schema has 100% coverage for the single parameter 'name', and the description adds value by providing examples and clarifying the format (English names, supported list). This goes beyond the schema's minimal 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's purpose: 'Get detailed profile of any of the 27 Vedic nakshatras.' It lists specific return fields and differentiates from siblings by being a dedicated nakshatra lookup.

    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 implicitly guides usage by focusing on nakshatra details, but lacks explicit when-to-use vs alternatives. However, the specificity makes it clear when to invoke this tool instead of siblings like calculate_kundali or get_panchang.

    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 burden. Describes what it returns and mentions external service (star-meet.com), but does not disclose side effects, rate limits, or authentication needs. Adequate for a read-only query.

    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?

    Two concise sentences: first states purpose and outputs, second adds use case and attribution. No unnecessary words.

    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 5 optional parameters, no output schema, and no annotations, description covers purpose, outputs, and use case. Lacks return structure details but lists outputs adequately.

    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 parameter descriptions. Description adds overall context but does not significantly extend parameter meaning beyond schema. 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?

    Clearly states what the tool does: 'Get the Vedic Panchang (Hindu almanac) for any date and location.' Lists specific outputs (Tithi, Nakshatra, Yoga, etc.) and distinguishes from sibling tools like calculate_kundali and get_nakshatra.

    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?

    Explicitly states usage context: 'Essential for muhurta (auspicious timing) selection.' Does not explicitly mention when not to use, but sibling tool names provide differentiation.

    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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