Web Scraping MCP Server
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
There is only one tool in this server, so there is no possibility of confusing it with another tool. The purpose is clearly stated as a universal web scraper, making the surface unambiguous by definition.
Naming Consistency2/5With a single tool there is no cross-tool naming pattern to evaluate. However, the name itself mixes snake_case prefixes with a camelCase verb and repeats 'web_scraping', making it awkward and internally inconsistent.
Tool Count3/5A single tool for a domain as broad as web scraping feels thin, but the one tool is extremely feature-rich and can serve as a universal scraper. It is borderline rather than an extreme mismatch.
Completeness4/5The tool covers the core web scraping workflow: fetching, rendering, extracting, screenshots, and structured output. It lacks explicit session/cache/scheduling management, but those can be worked around or handled externally.
Average 4.3/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- No commit activity data available
- Last stable release on
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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 provided, the description carries the full transparency burden. It discloses key behaviors such as using managed proxies, optional JS rendering, waiting conditions, blocking ads/resources, screenshots, and extraction capabilities. It does not mention rate limits or legal/ethical caveats, but the core behavioral traits are adequately described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is reasonably concise for a tool with 20 parameters. It front-loads the core purpose and capabilities, follows with specific use cases, and avoids redundant repetition of schema details. The structure is clear and scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (20 parameters, nested objects, no output schema), the description provides sufficient context: it explains what the tool does, when to use it, what output formats are available, and what extraction features exist. It does not describe an output schema, but the description adequately covers expected return types and capabilities.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The narrative description summarizes capabilities but does not add significant per-parameter meaning beyond the already detailed input schema descriptions. The schema itself provides strong parameter documentation, including nested objects and enum values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as a universal web scraper that fetches any public URL, with a specific verb ('Scrape Web Page') and a well-defined resource. It also distinguishes itself from the many specialized sibling tools by explicitly positioning itself as a fallback for sites without a dedicated API.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage guidance: use as a fallback/universal fetcher for sites without a dedicated API, for JS-heavy SPAs, bypassing bot protections, capturing screenshots, or producing clean markdown/structured JSON. This clearly tells an agent when to choose this tool over the specialized siblings.
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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