Lunoo Rankings
Server Details
Consensus rankings for 75,000+ products across 2,600+ niches.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
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 3.8/5 across 3 of 3 tools scored.
Each tool targets a distinct operation: finding niches, fetching item details, and retrieving rankings. No overlap or ambiguous boundaries.
All tools follow a consistent verb_noun pattern in snake_case (find_niche, get_item, get_rankings), making them predictable and easy to use.
With only 3 tools, the server is tightly scoped to its purpose of exploring rankings, ensuring each tool has a clear role without unnecessary complexity.
The tool set covers the core workflows of searching niches, viewing item details, and fetching rankings. A minor gap is the lack of a way to list all niches without a query, but the core functionality is present.
Available Tools
3 toolsfind_nicheAInspect
Find a niche by query string. Returns top 10 matching niches with slugs and URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query (e.g., "anime", "restaurants in Paris") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries the burden. It discloses the return limit (top 10) and output structure (slugs, URLs), but does not mention auth requirements, rate limits, or any side effects. Adequate for a simple search tool.
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, concise and front-loaded. Every word adds value, but it could be slightly more structured (e.g., separate return description).
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?
Description covers the essential: query parameter, return structure (slugs, URLs), and result limit (top 10). No output schema, but description compensates. Missing details like error cases, but sufficient for basic usage.
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%, and the parameter description in the schema already explains the query field. The tool description adds no additional meaning beyond what the schema provides, earning a baseline score of 3.
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 the tool finds a niche by query string and specifies it returns top 10 matches with slugs and URLs. This distinguishes it from siblings get_item and get_rankings, which are for different resources.
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. The description does not mention when not to use it or provide context for selecting among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_itemAInspect
Fetch structured data (JSON-LD) for an item by slug. Useful for extracting metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Item slug (e.g., "frieren-beyond-journeys-end") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It mentions output format (JSON-LD) but does not discuss side effects, authentication, or error handling. The read-only nature is implied but not stated.
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 two sentences, no redundant information, and is front-loaded with the key action and output format.
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 simple single-parameter tool with no output schema and no annotations, the description adequately covers input, output format, and purpose. Minor lack of error behavior details.
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%, and the description adds an example for the slug parameter ('frieren-beyond-journeys-end'), providing extra context beyond the type 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 clearly states the tool fetches structured data (JSON-LD) for an item by slug, and distinguishes from siblings like 'find_niche' and 'get_rankings' which serve different purposes.
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 says 'useful for extracting metadata' hinting at when to use, but does not provide explicit guidance on when not to use or alternatives among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_rankingsAInspect
Fetch rankings for a niche. Returns top N items with scores, descriptions, and URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of items to return (1-50, default 10) | |
| niche | Yes | Niche slug (e.g., "anime", "japanese-city") |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It mentions returning top N items with scores, descriptions, and URLs, but does not explain what 'rankings' means (e.g., ordering criteria, update frequency).
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, no filler, front-loaded with key action and result. Every word earns its place.
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?
For a simple tool with two parameters and no output schema, the description covers purpose, return structure, and parameter usage. Lacks detail on ranking methodology but is otherwise 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?
Schema coverage is 100%, so the description adds minimal value beyond the schema. It confirms 'limit' controls the number of items and 'niche' is the target, but no deeper semantics.
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 verb 'Fetch' and the resource 'rankings for a niche', and distinguishes from siblings 'find_niche' (searching niches) and 'get_item' (retrieving a single item).
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 implies usage when rankings are needed, but lacks explicit when-not or alternative guidance. Sibling tools are provided but no direct comparison.
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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