A
licenseNot graded
qualityC
maintenanceStructured design references from 1,000+ curated websites for AI-powered web design. Retrieve real CSS values, typography specs, color palettes, and design rationale via MCP.
1
MIT
Mobbin
by com.mobbin
Server Details
Search real-world UI & UX design references for mobile apps, web apps, and websites with Mobbin.
Ownership verified
- Status
- Healthy
- OAuth
- Works in Glama
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- mobbin/mobbin-mcp-server
- GitHub Stars
- 9
Available Tools
3 toolssearch_flowsSearch FlowsARead-onlyInspect
Search Mobbin for multi-step user flows (e.g. onboarding, checkout) using natural language. Returns evenly-spaced preview images inline along with metadata for each flow, including per-screen previews. Examine the returned images to understand each flow's actual content — do not describe screens based solely on metadata. On hosts that support MCP Apps, also renders an interactive gallery of the results.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number for paginating through results. Maximum 20. | |
| limit | No | Maximum number of flows to return. Lower limits are recommended to manage context size. | |
| query | Yes | Describe one user journey in plain language — the steps and what you'd see along the way. Be specific; detail helps. Good: "onboarding with personalization steps", "checkout with payment method selection". Avoid: combining multiple flows (search separately), negations, vague style words, disconnected keyword lists. Name a specific app to filter results to it (e.g. "Duolingo onboarding"). Do not include platform (ios/web) — use the dedicated parameter. | |
| platform | Yes | Platform to search. | |
| task_intent | No | One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data. | |
| image_format | No | Image format. Use jpg if your client does not support webp. | webp |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| page | Yes | 1-based page number of search results. |
| flows | Yes | |
| query | Yes | The natural language query used for this search. |
| has_next_page | Yes | Whether more pages of results are available. |
TDQS
A4.3/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavioral context beyond the readOnlyHint annotation: it discloses that results include inline evenly-spaced preview images, metadata, per-screen previews, and an interactive gallery on MCP Apps. It also instructs the agent to examine images rather than rely solely on metadata, which is valuable operational guidance.
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 concise and front-loaded with the core action, then adds only high-value behavior and usage details. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description, combined with the rich schema and output schema, gives an agent everything needed to call the tool correctly. It covers what the tool does, how results are returned, how to interpret them, and platform-specific gallery behavior.
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?
With 100% schema description coverage, the schema already documents every parameter thoroughly, including guidance for query, platform, page, limit, task_intent, and image_format. The tool description itself adds no parameter-specific semantics beyond what the schema provides.
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 states a specific action ('Search Mobbin for multi-step user flows') with concrete examples like onboarding and checkout, and clearly frames the tool as a flow-focused search rather than a screen or section search. This distinguishes it from the sibling tools search_screens and search_sections.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool — when looking for multi-step flows — but it never explicitly contrasts it with search_screens or search_sections. The query guidance in the schema adds helpful do's and don'ts, but no direct 'use this instead of X' guidance is present.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_screensSearch ScreensARead-onlyInspect
Search Mobbin for UI screens using natural language. Returns matching screens with inline images and metadata. Examine the returned images to understand each screen's actual content — do not describe or summarize screens based solely on metadata. Each screen has a mobbin_url — the canonical Mobbin link for that screen. When you present results to the user, ALWAYS cite each screen you mention as a markdown link to its mobbin_url so the user can open it on Mobbin. On hosts that support MCP Apps, also renders an interactive gallery of the results.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | Search mode. "standard" returns results with low latency. "deep" uses an AI-powered pipeline that interprets intent and scores each candidate for relevance, keeping the strong matches — ideal for nuanced queries. "fast" is a deprecated alias for "standard" and will be removed in a future version — use "standard" instead. | deep |
| limit | No | Maximum number of screens to return. Higher number of screens returned causes increased context usage. | |
| query | Yes | Describe one screen in plain language — the UI elements you'd see and how they relate. Be specific; detail helps. Good: "login screen with biometric authentication", "checkout page with promo code field and Apple Pay button". Avoid: combining multiple screens/intents (search separately), negations ("without ads"), vague style words ("modern", "clean"), disconnected keyword lists. Name a specific app to filter results to it (e.g. "Spotify now-playing screen"). Do not include platform (ios/web) — use the dedicated parameter. | |
| platform | Yes | Platform to search | |
| task_intent | No | One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data. | |
| image_format | No | Image format. Use jpg if your client does not support webp. | webp |
| exclude_screen_ids | No | Screen IDs to exclude from results |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| query | Yes | The natural language query used for this search. |
| screens | Yes |
TDQS
A4.5/5.0
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even with readOnlyHint=true and destructiveHint=false, the description adds significant behavioral value: it instructs the agent to examine returned images rather than inferring from metadata, mandates markdown citations to mobbin_url, and discloses the MCP Apps gallery rendering. These behaviors are not evident from annotations alone.
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 front-loaded with the core purpose and return value, then efficiently adds the most important usage constraints. Each sentence earns its place: the image-examination rule, the mobbin_url citation requirement, and the gallery rendering note are all materially useful without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a search tool with a rich input schema, a declared output schema, and read-only annotations, the description covers the essential behavioral guidance an agent needs: how to interpret results, how to cite them, and how the mode parameter affects latency/relevance. No critical calling detail is missing.
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 description coverage is 100%, so the schema already thoroughly documents all seven parameters, including enums, defaults, and constraints. The description reinforces query best practices but does not add new parameter-level meaning beyond what the schema already provides; baseline 3 is appropriate.
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 states a specific verb ('Search'), a clear resource ('Mobbin UI screens'), and a distinct deliverable ('matching screens with inline images and metadata'). The name and phrasing clearly distinguish it from siblings like search_flows and search_sections by focusing on individual screens rather than flows or sections.
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 description gives clear context for when to use this tool: when searching for UI screens by natural language, and it includes detailed query guidance such as avoiding combined intents and negations. It does not explicitly mention alternatives like search_flows or search_sections, so it stops short of full when/when-not differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_sectionsSearch SectionsARead-onlyInspect
Search Mobbin for website sections (e.g. About, Pricing, Footer) using natural language. Returns section images inline along with metadata. Examine the returned images to understand each section's actual content — do not describe or summarize sections based solely on metadata. On hosts that support MCP Apps, also renders an interactive gallery of the results.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number for paginating through results. | |
| limit | No | Maximum number of sections to return. Higher number of sections returned causes increased context usage. | |
| query | Yes | Describe one website section in plain language — the content and elements you'd see. Be specific; detail helps. Good: "pricing page with plan comparison table", "hero section with signup form". Avoid: combining multiple sections (search separately), negations, vague style words, disconnected keyword lists. | |
| task_intent | No | One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data. | |
| image_format | No | Image format. Use jpg if your client does not support webp. | webp |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
| page | Yes | 1-based page number of this batch of search results. |
| query | Yes | The natural language query used for this search. |
| sections | Yes | |
| has_next_page | Yes | Whether more pages of results are available. |
TDQS
A4/5.0
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool read-only and non-destructive; the description adds useful behavior beyond that: images are returned inline with metadata, results must be verified visually rather than summarized from metadata, and an interactive gallery appears on supporting MCP Apps hosts. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three focused sentences front-load the purpose, then explain the result-usage rule and the conditional gallery behavior. No filler or repetition of schema content.
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 read-only search tool, the description plus fully documented schema and output schema cover how to call it, what the results look like, and how to handle them. It is slightly incomplete only in not addressing sibling-tool selection or pagination/context-use nuance beyond the schema fields.
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 description coverage is 100% and the parameter descriptions are already rich, so the description does not need to re-explain parameters. It adds little parameter-specific meaning except emphasizing natural-language querying, which is the baseline expected when the schema carries the load.
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 names a specific verb and resource ('Search Mobbin for website sections') and gives concrete examples (About, Pricing, Footer) that set it apart from the sibling tools searching flows and screens. This is enough for an agent to recognize what this tool is for.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It clearly states natural-language input and instructs inspecting returned images, but it never says when to prefer search_sections over search_flows or search_screens, or when not to use it. The distinction from siblings is left to the tool name and examples rather than explicit usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- Changed
search_flows1 field changed- changed
Input schema / properties / task_intent / descriptionPrevious value: -"One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."New value: +"One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."
- Changed
search_screens1 field changed- changed
Input schema / properties / task_intent / descriptionPrevious value: -"One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."New value: +"One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."
- Changed
search_sections1 field changed- changed
Input schema / properties / task_intent / descriptionPrevious value: -"One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."New value: +"One short sentence summarizing the user's overall task. Helps return more relevant results. Write it in English even when the conversation is in another language. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data."
3 tool updates
- Changed
search_flows1 field changed- added
Input schema / properties / task_intentAdded value: +{ + "description": "One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data.", + "type": "string" +}
- Changed
search_screens1 field changed- added
Input schema / properties / task_intentAdded value: +{ + "description": "One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data.", + "type": "string" +}
- Changed
search_sections1 field changed- added
Input schema / properties / task_intentAdded value: +{ + "description": "One short sentence summarizing the user's overall task. Helps return more relevant results. MUST be the same across all calls for the same task. Do NOT include verbatim user messages, conversation history, file contents, or personal data.", + "type": "string" +}
3 tool updates
- First observed
search_flows - First observed
search_screens - First observed
search_sections
Frequently Asked Questions
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as
io.github.alice/server, link the matching GitHub user, then choose Claim with GitHub. An organization namespace such asio.github.acme/serveralso needs that organization to have installed the Glama AI GitHub App and approved its permissions, because GitHub discloses organization membership only to apps it has installed. Use HTTP or DNS when it has not.HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at
/.well-known/glama.jsonon the same origin as the connector, then choose Check HTTP challenge.DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
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
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
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.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Connectors
- mcpOAuthcom.gummble
Search 300k+ real app screens, flows, and UX microcopy from 1,500+ shipped products.
Search curated design styles, real product screens, and user flows for evidence-based design work.
Real iOS interaction clips, motion breakdowns, SwiftUI to match. Paid licence required.
Focused full-screen UI references and hosted design materials for coding agents.
Related MCP Servers
- AlicenseNot gradedqualityFmaintenanceEnables users to search and browse Mobbin's extensive library of mobile app designs, screenshots, and user flows directly from Claude. It allows for detailed exploration of UI patterns, elements, and personal collections using reverse-engineered API access.14045ISC
- AlicenseAqualityDmaintenance🎨 AI-powered UI/UX design intelligence - 1519+ curated design resources through MCP | React, Vue, Next.js, Flutter & more714727MIT
- AlicenseNot gradedqualityCmaintenanceProvides curated real website design references with structured JSON data on type, spacing, palette, and layout. Enables AI agents to search, browse, and analyze over 1,000 sites and their sections.1MIT
Try in Browser
Glama MCP Gateway
Add one secure layer between your agents and this server.
TDQS
A4.4/5.0
Disambiguation5/5
Each tool searches a distinct content type—flows, screens, and sections—so an agent can clearly choose based on what kind of result is needed. The entity types are separate enough that there is no meaningful overlap or ambiguity.
Naming Consistency5/5
All three tools follow the exact same search_<plural-noun> pattern. This is a perfectly consistent and predictable naming convention.
Tool Count5/5
Three tools is well-scoped for a search-only server. Each tool covers one core Mobbin content category, and none feel redundant or unnecessary.
Completeness5/5
The server's apparent purpose is to search Mobbin's design content, and it covers the three primary content types: flows, screens, and sections. There are no obvious missing operations for this read-only search domain.