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Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4/5 across 1 of 1 tools scored.
With only one tool, there is no risk of confusion between tools. The tool's purpose is clearly defined and distinct.
Single tool naming is consistent by default. The name 'visual_check' is descriptive and follows a clear pattern.
While a single tool is on the low end, it is appropriate for a specialized visual testing server. The tool covers a focused use case without being overly minimal.
The tool captures screenshots and analyzes for visual bugs, covering the core functionality. However, additional tools for configuration, comparison baselines, or batch processing would make the surface more complete.
visual_checkAInspectScreenshot a URL and analyze it for visual bugs using AI. Returns whether issues exist, a summary, and a detailed issues list. Use this after deployments, PRs, or any UI change to catch layout problems.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to visually check (must be publicly accessible) | |
| prompt | No | Optional: specific aspect to focus on | |
| no_cache | No | Optional: bypass cache | |
| viewport | No | Optional: viewport size — desktop (1280px), tablet (768px), mobile (375px) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It explains the AI analysis and return structure but does not specify whether the tool is read-only, if screenshots are stored, or any authentication requirements. This leaves gaps for an agent to assess side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at two sentences, front-loading the core function and following with usage guidance. Every word adds value with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no output schema), the description adequately covers what the tool does and when to use it. However, it lacks details on behavioral aspects like caching or data retention, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds little beyond what the schema already provides. It does not elaborate on parameter defaults, constraints beyond the schema, or usage tips. The baseline of 3 is appropriate since the schema is already informative.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the function ('Screenshot a URL and analyze it for visual bugs using AI') and the output format ('Returns whether issues exist, a summary, and a detailed issues list'). It uses a specific verb and resource combination that leaves no ambiguity about the tool's purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly recommends usage after deployments, PRs, or UI changes, providing clear context. However, it does not discuss when not to use the tool or mention any alternatives, though no sibling tools are available.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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