Layero
Server Details
Build a landing page in your IDE chat and deploy it — servers and CDN inside Russia.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- LayeroInfra/layero-claude
- GitHub Stars
- 0
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.
Tool Definition Quality
Average 3.6/5 across 5 of 5 tools scored. Lowest: 2.4/5.
Each tool has a clear and distinct purpose: composing, listing design systems/structures, adding integrations, and deploying. No overlap in functionality.
All tool names follow a consistent verb_noun pattern (list_design_systems, list_structures, add_integration, compose_landing, deploy). No mixing of conventions.
5 tools is well-scoped for a landing page builder server. Each tool serves a necessary step in the workflow without unnecessary redundancy.
Covers the core lifecycle: list available templates, compose, add integration, deploy. Minor gaps like update or delete operations are absent but not critical for the server's stated purpose.
Available Tools
5 toolsadd_integrationBInspect
Wire form submissions into a destination.
Returns the integration recipe. The agent executes the steps itself — runs terminal commands, edits files, deploys a relay if needed.
| Name | Required | Description | Default |
|---|---|---|---|
| kind | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| playbook | Yes | |
| next_action | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It clearly discloses that the tool returns a multi-step recipe (terminal commands, file edits, relay deployment) rather than performing the integration directly, which is valuable behavioral insight.
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 very concise at two sentences, with the key purpose in the first sentence. The second sentence could be slightly better structured but is still efficient.
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 simplicity (one parameter with enum), the description covers the output behavior (returns a recipe) and agent action required. However, the lack of parameter details and output schema usage limits 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 description coverage is 0% and the description does not mention the only parameter 'kind'. The enum values (telegram, google_sheets, custom) are left unexplained, forcing the agent to infer meaning from the parameter name alone.
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 states 'Wire form submissions into a destination,' which is a clear verb+resource pairing. It distinguishes from siblings (compose_landing, deploy, etc.) but could be more specific about the integration types.
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 mentions that the tool returns a recipe that the agent executes itself, providing some usage context. However, it does not specify when to use this tool versus alternatives or clarify any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compose_landingAInspect
Drive the 3-step quiz flow and produce a complete landing.
This is the **main entry point**. Don't ask the user questions in chat
before calling this — the tool opens native quiz dialogs in the IDE
itself. Call this immediately when the user describes what they want.
The three quizzes are:
1. **Motivation** — what's being built, for whom, the desired action.
2. **Look & feel** — palette, tone, optional references.
3. **Final picks** — design system (top 3 matched), where submissions go,
project name slug.
Returns a ``ComposeResult`` with the file bundle to write to disk. The
agent then writes the files using the IDE's filesystem tool and proceeds
to integration setup / deploy.
| Name | Required | Description | Default |
|---|---|---|---|
| user_message | Yes | The user's full message verbatim — do not paraphrase. Used to pre-fill quiz defaults and inform matching. |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| brief | No | |
| files | No | |
| status | Yes | |
| structure | No | |
| integration | No | |
| next_action | No | |
| design_rules | No | |
| project_name | No | |
| design_system | No | |
| category_guide | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavior: it opens quiz dialogs, conducts three quizzes, returns a ComposeResult with a file bundle, and expects the agent to write files afterward. This goes beyond a simple 'create landing' statement, though it could mention any side effects or limitations.
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 front-loaded with the main purpose and structures the quiz steps clearly. It is concise enough but could be slightly trimmed by condensing the quiz list into a single line; however, each sentence contributes to understanding.
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?
The description fully covers the tool's role in the workflow: when to call, what happens in the quiz, what the output is, and the subsequent agent actions (writing files, integration). Given the simple parameter set and presence of an output schema, this is complete.
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?
The schema defines one parameter (user_message) with full coverage. The description adds value by specifying that the message must be verbatim and that it pre-fills quiz defaults, which aids correct invocation beyond the schema's technical description.
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 tool drives a 3-step quiz flow and produces a complete landing, making the purpose explicit. It distinguishes itself from siblings by labeling itself as the 'main entry point' and contrasting with other tools like add_integration and deploy.
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?
It explicitly states to call this immediately when the user describes their goal, and not to ask questions in chat because the tool opens native dialogs. This provides clear when-to-use and when-not-to-use guidance, effectively setting the tool apart from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deployAInspect
Deploy the landing to Layero.
Returns the deploy playbook and the canonical command sequence. The agent is expected to execute these in the user's terminal — do not paste the commands and wait.
| Name | Required | Description | Default |
|---|---|---|---|
| mode | No | preview | |
| project_dir | No | . |
Output Schema
| Name | Required | Description |
|---|---|---|
| commands | Yes | |
| playbook | Yes | |
| next_action | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that the tool returns a deploy playbook and command sequence, and warns against pasting commands blindly. This goes beyond basic annotations (none provided) by detailing expected agent behavior. Minor ambiguity remains about whether the tool actually deploys or generates instructions only.
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 just two sentences, front-loading the core purpose and adding necessary usage instruction with no superfluous words.
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 presence of an output schema (assumed), the description does not need to detail return values. However, it omits parameter guidance, and the tool's behavior (deploy vs. generate commands) could be clearer. Adequate but missing parameter context.
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 description coverage is 0%. The description does not mention the two parameters ('mode' and 'project_dir') or their roles, leaving the agent to guess their meaning and defaults.
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 action 'Deploy the landing to Layero,' specifying the verb and resource. It distinguishes the tool from siblings like add_integration or compose_landing, which have different functions.
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 provides explicit guidance on how to use the output: 'The agent is expected to execute these in the user's terminal — do not paste the commands and wait.' This clarifies the agent's role. However, it does not explicitly state when to use this tool versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_design_systemsAInspect
Return the catalogue of design systems Layero ships with.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose behavioral traits such as read-only nature, side effects, or authentication requirements; minimal transparency.
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?
Extremely concise single sentence that directly conveys the purpose with no waste; appropriately sized for a simple list operation.
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 zero parameters and presence of output schema, the description is mostly complete. It could clarify scope (e.g., 'default' design systems) but is adequate.
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?
No parameters, so schema coverage is 100%. Description adds no extra meaning but is sufficient; baseline of 4 is appropriate.
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 states a specific verb ('Return') and resource ('catalogue of design systems'), clearly distinguishing it from sibling tools like 'list_structures'.
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?
No guidance on when to use this tool versus alternatives or when not to use it; lacks context for selection among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_structuresAInspect
Return the catalogue of landing structures Layero ships with.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States 'return' implying read-only, but does not explicitly mention non-destructiveness, auth needs, or caching behavior. Minimal disclosure beyond obvious.
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?
Single sentence of 10 words. No fluff, every word is necessary. Optimal conciseness for a simple tool.
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?
Tool has no parameters and has an output schema. Description adequately states what is returned (catalogue of landing structures). For a simple list tool, this is complete.
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?
Zero parameters, so baseline 4 applies. Schema has no properties, and description adds no extra meaning, which is acceptable given no parameters.
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?
Description clearly states 'Return the catalogue of landing structures Layero ships with'. Verb 'list' matches tool name, resource 'structures' is specified, and context of 'landing structures' differentiates from sibling tools like list_design_systems.
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?
No explicit guidance on when or when not to use this tool. Usage is implied by name and description but lacks exclusions or alternatives, making it adequate but not strong.
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.
Discussions
No comments yet. Be the first to start the discussion!