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deenesjakoruzh
Xquik-dev

X Twitter Scraper

by Xquik-dev
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

92%
Profile completionA complete profile improves this server's visibility in search results.
  • Disambiguation5/5

    The two tools have completely distinct purposes: 'explore' is strictly for discovery/documentation of the 121 available endpoints, while 'xquik' is strictly for authenticated execution. No functional overlap exists.

    Naming Consistency3/5

    Mixed conventions: 'explore' follows a clear verb pattern, while 'xquik' is a branded product name that reveals nothing about its execution purpose. With only two tools this is readable, but lacks predictability.

    Tool Count3/5

    Two tools is borderline thin for a server claiming access to 121 endpoints across categories like composition, extraction, monitoring, and media. A single generic executor ('xquik') covering all CRUD operations is minimal.

    Completeness3/5

    While the generic 'xquik' tool technically covers all 121 endpoints, the surface lacks specific tools for common operations (e.g., no dedicated 'search_tweets' or 'post_tweet'). Agents must manually construct API paths using 'explore' first, creating friction.

  • Average 4.8/5 across 2 of 2 tools scored.

    See the tool scores section below for per-tool breakdowns.

  • This repository includes a README.md file.

  • This repository includes a LICENSE file.

  • Latest release: v0.1.2

  • 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.

  • This repository includes a glama.json configuration file.

  • View server inspector

  • This server provides 2 tools. View schema

  • No known security issues or vulnerabilities reported.

    Report a security issue

  • This server has been verified by its author.

  • View related servers

Tool Scores

  • Behavior5/5

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

    While annotations indicate read-only/idempotent status, the description adds substantial critical execution context: 'No network calls — runs against an in-memory catalog', 'Always free, no authentication', 60-second timeout, runtime error handling behavior, and detailed EndpointInfo return structure (method, path, free boolean, etc.).

    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?

    Though lengthy, content is well-structured with markdown headers (## When to use, ## Behavior, ## Examples) making it scannable. Every section serves a critical purpose for this complex code-execution tool; however, the length prevents a perfect score for conciseness.

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

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Absence of output schema is adequately compensated by detailed description of return values (result of filter function, EndpointInfo object contents including method, path, category, free status, parameters, responseShape) and error scenarios. Distinguishes from sibling tool completely.

    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 coverage is 100% providing baseline documentation for the 'code' parameter. Description adds significant semantic value through the 'Input format' section explaining the sandbox environment provides `spec.endpoints`, and four concrete examples demonstrating different filtering patterns (by free status, category, keyword, specific path lookup).

    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 explicitly states the tool 'Search[es] and browse[s] the Xquik X (Twitter) API specification to discover endpoints' and clearly distinguishes it from sibling tool 'xquik' (discover vs. live API calls). Uses specific verbs and identifies the exact resource (API specification/endpoints).

    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?

    Contains dedicated 'When to use' and 'When NOT to use' sections that explicitly direct users to call 'explore' FIRST before 'xquik', list specific scenarios (finding capabilities, checking subscription requirements), and explicitly prohibit using it for live data fetch or when endpoint details are already known.

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

  • Behavior5/5

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

    Annotations only declare destructive/open-world status; the description substantially expands with sandboxing constraints (Node.js VM, no filesystem), execution timeouts (60s), pagination mechanics (has_next_page, next_cursor), return value schemas (JSON objects vs success objects), credit costs ($0.00015/read, $0.0015/write), and specific error code meanings (402, 429, 404). No contradictions with annotations.

    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?

    Length is substantial but justified by tool complexity (sandboxed code execution, 121 endpoints, credit system). Information is front-loaded (purpose in first sentence) and hierarchically organized with clear headers (When to use, Behavior, Costs, Examples). Every section provides distinct operational value; examples are concise and illustrative.

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

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    For a single-parameter tool with no output schema, the description comprehensively covers: return value structures (in Behavior), pagination (critical for 121 endpoints), error handling, financial costs (credit system), sibling relationships, and execution constraints. No gaps remain for agent invocation decision-making.

    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 coverage is 100% with a detailed description for the single 'code' parameter. The description adds significant semantic value through the 'Input format' section and three concrete examples showing async arrow function patterns, method chaining, and query structures that clarify how to construct valid parameter values beyond the schema's syntactic definition.

    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 opens with a precise action statement ('Execute authenticated X (Twitter) API calls'), identifies the resource (X/Twitter), and enumerates capabilities (read data, publish content, manage accounts across 121 endpoints). It explicitly distinguishes from sibling 'explore' by stating xquik is for 'live X/Twitter operation' while explore is for endpoint discovery.

    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?

    Contains dedicated 'When to use' and 'When NOT to use' sections that explicitly name sibling tool 'explore' as the prerequisite for discovery and the alternative choice. Clear negative constraints provided ('Do NOT use to discover endpoints', 'Do NOT pass API keys'). Guidelines cover sequencing, authentication boundaries, and operational scope.

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

GitHub Badge

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

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If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.

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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.

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