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negm17111995

Circlfi-MCP

by negm17111995
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JavaScript
Remote

Server Quality Checklist

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

  • Latest release: v1.1.0

  • Disambiguation5/5

    The two tools serve completely distinct purposes: one focuses on intrinsic valuation of a single stock, while the other screens the entire market. There is no overlap or potential for confusion.

    Naming Consistency5/5

    Both tools use a consistent 'get_' prefix followed by a descriptive noun phrase (get_stock_valuation, get_market_screener), following a clear verb_noun pattern.

    Tool Count3/5

    With only 2 tools, the server feels underpopulated for its stated domain of stock analysis and screening. While the tools are individually valuable, the scope suggests more tools would be reasonable (e.g., price data, fundamentals).

    Completeness2/5

    The server only covers valuation and market screening, leaving out essential stock analysis operations like price history, financial statements, or news. This is a significant gap for a stock analysis server.

  • Average 3.8/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 4 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 ISC 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.

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

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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 must cover behavioral traits. It mentions the subscription requirement but lacks details on rate limits, response size, pagination, data freshness, or any limits when using 'fetchAll'. Important behavioral context is missing.

    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 three sentences long, front-loading the main purpose and key details. Every sentence adds value with no redundant information.

    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?

    The tool has no output schema, but the description does not explain the return structure (JSON fields or CSV columns). It also lacks error handling or limit information. Given the complexity (3 params, nested object, fetching all data), it is incomplete.

    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?

    Schema description coverage is 100%, and the description adds value by recommending CSV for downloadable files. The parameters are well-documented in both schema and description, with the nested filter object clearly explained.

    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 screens the entire stock market (5,900+ stocks) using CirclFi data, with specific filters and output formats. It distinguishes itself from the sibling tool 'get_stock_valuation' which focuses on individual stock valuation.

    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 mentions a required paid subscription and recommends CSV for downloadable files, providing some usage guidance. However, it does not explicitly contrast with the sibling tool or state when not to use it.

    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 must disclose behavioral traits. It mentions 'latest' and includes model types but does not detail rate limits, caching, data freshness, or output format. Partial transparency.

    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, no fluff. Front-loaded with key info: verb, resource, source. Every word adds value.

    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 low complexity (1 parameter, no output schema, no annotations), the description adequately covers what the tool does. Could mention output structure but not strictly necessary. Mostly complete.

    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% with parameter 'ticker' already well-described. Description does not add extra semantic value beyond the schema, so baseline score of 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?

    Description uses specific verb 'Get' and resource 'latest intrinsic valuation of a single stock', names the engine 'CirclFi's 13-model engine', and lists example models. This clearly distinguishes from the sibling tool 'get_market_screener', which likely screens multiple stocks.

    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?

    Description implies when to use (when wanting intrinsic valuation for one stock) but does not provide explicit guidance on when not to use or direct alternative to sibling. Lacks explicit usage conditions.

    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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