screenshots-snapshot-site
OfficialServer Quality Checklist
Latest release: v1.0.0
- Disambiguation4/5
The three tools have distinct core purposes (capture, analyze, compare), but 'screenshot' and 'analyze' both involve capturing a live webpage, which could cause confusion. Descriptions provide enough clarity, but the overlap is noticeable.
Naming Consistency5/5All tool names are single-word verbs—screenshot, analyze, compare—following a consistent and predictable pattern. There is no mixing of conventions or vague naming.
Tool Count5/5With 3 tools, the server is well-scoped for its purpose of capturing, analyzing, and comparing webpages. Each tool occupies a distinct role, and the count is within the ideal 3–15 range.
Completeness4/5The tool set covers the primary workflows: capture (screenshot), analysis (analyze), and comparison (compare). Minor gaps exist, such as no explicit snapshot management or status listing, but these are not critical for the core functionality.
Average 3.9/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 16 commits in the last 12 weeks
- 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.
Tools from this server were used 2 times in the last 30 days.
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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, covering the safety profile. The description adds behavioral context like captcha detection and blank-page signals but does not disclose execution-related behaviors (e.g., javascriptCode execution) or output details. This adds some value without contradicting annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise, front-loaded sentences that convey the purpose and use cases without redundancy. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 14 parameters and no output schema, the description remains at a high level, omitting essential details about parameter behavior, required inputs beyond URL, and return values. This is insufficient for correctly invoking the tool in varied scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain any of the 14 parameters. It only mentions high-level use cases without mapping them to parameters like enableSummary, enableQuality, or format. This leaves agents without crucial parameter-level guidance.
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 states the tool captures and analyzes a webpage, with specific use cases (content summaries, SEO metadata, headings, quality signals). This distinguishes it from sibling tools like screenshot and compare, which likely focus on different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (summaries, SEO inspection, headings extraction, quality detection) but does not explicitly mention when not to use it or compare it with alternatives. The context is sufficient for basic selection guidance.
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?
Annotations already indicate read-only, idempotent, and open-world behavior. The description adds useful behavior context like 'live webpage', 'cookie hiding', and 'custom JS injection' without contradicting annotations. It does not detail all edge cases, but the annotations cover the core safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly packed sentence that front-loads the primary action and then lists supported features. Every word adds value, with no redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a broad overview of tool capabilities and pairs with a rich input schema, but it does not explain ambiguous parameters or output retrieval behavior. For a 12-parameter tool with no output schema, this is adequate for selection but not fully sufficient for correct invocation without additional inference.
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?
With 0% schema description coverage, the description's list of capabilities (e.g., 'device-sized renders', 'cookie hiding', 'HTML capture') indirectly maps to parameters like width/height, hideCookie, and format. However, many parameters (hide, delay, convert, country, language, fullSize) remain ambiguous and uncompensated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool captures a live webpage and lists specific use cases (screenshots, PDFs, HTML capture, etc.). It does not explicitly distinguish from sibling tools 'analyze' and 'compare', but the capture focus is apparent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit use-case guidance with 'Use this for...' and enumerates supported output types and features. It does not mention exclusions or alternative tools, but the context is clear for selecting this tool for capture tasks.
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?
Annotations already provide readOnlyHint, openWorldHint, and idempotentHint. The description adds value by explaining that it accepts live webpage states or PNG captures and returns before/after/diff/metrics, which is not covered by annotations. No contradiction is present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two sentences, front-loaded with the core purpose and followed by use cases. Every word contributes, with no repetition or fluff.
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?
Despite the nested object complexity and lack of output schema, the description covers the main function and return value structure. Strong annotations compensate for safety, but the description would benefit from explaining threshold and capture sub-properties to be fully self-sufficient.
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 0%, so the description must compensate. It clarifies that 'before' and 'after' can be either live URLs or PNG captures, but it does not explain the 'threshold' parameter or the many sub-properties like hide, delay, width, etc., leaving gaps in understanding.
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 explicitly states 'Compare two live webpage states or two PNG captures and return before, after, diff, plus mismatch metrics.' This clearly identifies the verb (compare), the resource (two webpage states or PNG captures), and the outputs, distinguishing it from sibling tools like 'screenshot' and 'analyze'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description says 'Useful for QA, release review, and visual regression workflows,' which provides clear contexts for when to use the tool. However, it does not explicitly mention when not to use it or contrast it with alternatives, so it falls short of a 5.
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
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/snapshot-site/snapshot-site-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server