Skip to main content
Glama
bingal

Webshot MCP

by bingal
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'webshot' has a clear and distinct purpose of generating webpage screenshots, leaving no ambiguity for an agent to misselect between multiple options.

    Naming Consistency5/5

    The naming is perfectly consistent as there is only one tool, 'webshot', which follows a clear and descriptive pattern. There are no other tools to compare against, so no inconsistencies in verb_noun patterns or style mixing can arise.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and may indicate an incomplete or overly narrow scope. For a webshot server, one tool might suffice for basic screenshot generation, but it lacks related operations like configuration, batch processing, or image editing, making it feel thin and potentially inadequate for broader use cases.

    Completeness2/5

    The server is severely incomplete for a webshot domain. While the single tool covers the core action of generating screenshots, there are obvious gaps such as setting parameters (e.g., resolution, timeout), handling errors, or managing multiple screenshots. This minimal surface will likely cause agent failures when more complex tasks are required beyond basic screenshot capture.

  • Average 2.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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.

  • 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

  • Behavior2/5

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

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action ('生成' meaning generate/creates) but doesn't mention side effects (e.g., file creation, network usage), performance aspects (e.g., speed, rate limits), or error handling. This leaves significant gaps for a tool that performs external operations.

    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 extremely concise with a single phrase ('生成网页截图'), which is front-loaded and wastes no words. For a tool with a well-documented schema, this brevity is appropriate, though it may sacrifice completeness.

    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?

    Given the tool's complexity (8 parameters, no output schema, no annotations), the description is inadequate. It doesn't explain return values (e.g., file path, error messages), behavioral traits, or usage context, leaving the agent to rely solely on the schema for operational details.

    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?

    The description adds no parameter-specific information beyond the input schema, which has 100% coverage with detailed descriptions for all 8 parameters. Since the schema fully documents parameters like 'url' and 'output', the description doesn't need to compensate, but it also doesn't enhance understanding of parameter interactions or defaults.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description '生成网页截图' (generate webpage screenshot) clearly states the verb (generate) and resource (webpage screenshot), making the purpose understandable. However, it lacks specificity about the tool's scope or any distinguishing features, and with no sibling tools, differentiation isn't needed but the description remains somewhat vague.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides no guidance on when to use this tool, such as prerequisites (e.g., internet access, URL validity), alternatives, or constraints (e.g., timeouts, size limits). With no sibling tools, explicit alternatives aren't required, but general usage context is missing.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

webshot-mcp MCP server

Copy to your README.md:

Score Badge

webshot-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/bingal/webshot-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server