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ScrapeOps

ScrapeOps MCP Server

by ScrapeOps
OverviewSchemaRelated ServersScoreDiscussions
JavaScript

Server Quality Checklist

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

  • Latest release: v1.0.1

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: maps_web for general browsing and scraping, extract_data for structured data extraction, and return_links for URL extraction. There is no functional overlap.

    Naming Consistency4/5

    All tools follow a verb_noun pattern with underscores (maps_web, extract_data, return_links). However, 'maps_web' is a slightly ambiguous verb choice, deviating from the more descriptive verbs like 'extract' and 'return'.

    Tool Count4/5

    Three tools is low but sufficient for a focused scraping toolkit. They cover the core tasks: browsing, data extraction, and link analysis. Additional tools (e.g., dedicated screenshot) could be added, but the current count is reasonable.

    Completeness4/5

    The tool surface covers the primary scraping workflows: browsing with advanced features (maps_web), structured extraction (extract_data), and link discovery (return_links). Minor gaps exist, such as lack of form interaction or session management, but core needs are met.

  • Average 4.2/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

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  • 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

  • Behavior4/5

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

    With no annotations, the description carries full burden and discloses extraction modes, data schemas, anti-bypass options, and return format. However, it omits behaviors for many parameters like wait, mobile, and follow_redirects.

    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 well-structured with sections and examples, front-loading the purpose. It is appropriately sized but could be slightly trimmed without losing value.

    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 18 parameters and no output schema, the description covers core functionality well but lacks details on many optional parameters and error/rate-limit behaviors. It is complete for basic usage but not exhaustive.

    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 0%, so description compensates by explaining key parameters (url, mode, data_schema, bypass_level) via examples. But many parameters (e.g., wait, country, session_number) remain unexplained, making it only partially helpful.

    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 extracts structured data from webpages and provides a list of best-use cases. It distinguishes from siblings via usage examples and mentions auto and LLM modes.

    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 'Best for' section and examples provide clear context for when to use this tool. However, it does not explicitly state when not to use it or alternatives like maps_web or return_links.

    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?

    With no annotations, the description fully carries the burden. It details URL processing (relative to absolute, dedup, filtering), categorization into pages vs assets, and the JSON output structure. Example usage clarifies parameter behavior for bypass_level and country.

    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 well-organized with sections (Best for, What it extracts, URL Processing, Returns, Usage Examples). It is longer than necessary but front-loads key information and uses clear formatting.

    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 tool with 9 parameters, no output schema, and no annotations, the description covers functionality, output structure, and processing well. However, it lacks error handling, rate limit info, and full parameter descriptions, leaving some gaps.

    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?

    Schema coverage is 0% (no parameter descriptions in schema). The description only provides examples for url, bypass_level, and country, leaving 6 undocumented parameters (mobile, premium, residential, etc.) unexplained. This fails to compensate for the lack of schema documentation.

    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 it extracts and categorizes URLs from a webpage. It lists specific elements (links, images, scripts, etc.) and processing steps. Sibling tools (maps_web, extract_data) are distinct in purpose, so no ambiguity.

    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?

    Provides a 'Best for' section listing use cases like discovering links, building sitemaps, web crawling. It gives clear context for when to use, but does not explicitly state when not to use or compare to siblings. Lacks exclusion criteria.

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

  • Behavior4/5

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

    No annotations, but description comprehensively explains capabilities (geo-targeting, anti-bot, screenshots, wait controls) and return format. Lacks mention of potential side effects like cookies or rate limits, but overall transparent.

    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?

    Well-structured with sections, bullet points, and code examples. Front-loads purpose and key features. Slightly long but every section adds value; no wasted 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?

    With 18 parameters and no output schema, description provides thorough context: best-for, features, examples, default behavior, error handling, and return format. Missing explanations for a few parameters, but overall complete for a complex tool.

    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?

    With 0% schema description coverage, baseline is 4. Description explains many parameters via key features and usage examples (e.g., wait, wait_for, screenshot, render_js, bypass_level, residential). Some parameters (keep_headers, session_number) not mentioned, but coverage is high enough to justify a 4.

    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 is for browsing and scraping webpages with advanced proxy and rendering capabilities. It distinguishes from sibling tools by listing specific features like geo-targeting and JavaScript rendering.

    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?

    Explicitly provides 'Best for' scenarios and 'IMPORTANT - Default Behavior' instructions on when to use advanced parameters, requiring user confirmation for retries. This gives clear guidance on appropriate usage.

    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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