Search and discover AI-ready websites from the international llms.txt directory using a read-only remote MCP server.
Get approved sites in the llmsmap.ru catalog with llms.txt URLs, token counts, and metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of sites to return, capped at 50. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It communicates the scoped content (approved sites, specific attributes) but says nothing about return format, ordering, pagination behavior beyond the schema's cap, or any access constraints. Adequate but thin for a no-annotation 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?
A single efficient sentence that front-loads the action and lists the relevant attributes with no filler. It earns its space, though it could have slipped in a sibling-mention without bloat.
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 list tool with one fully-documented optional parameter, the description covers the essential intent and scope. However, it omits the return structure and any guidance distinguishing it from search_catalog, leaving those to be inferred.
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%: the single optional limit parameter is fully documented in the schema ('Maximum number of sites to return, capped at 50'). This meets the baseline; the description adds no additional parameter context, which is acceptable given the schema already covers it.
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 clear action (get), resource (approved sites in the llmsmap.ru catalog), and the included attributes (llms.txt URLs, token counts, metadata). It's concrete, though the distinction from sibling search_catalog is implied by the 'approved sites' list framing rather than explicitly named.
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?
There is no guidance on when to use this tool versus the sibling search_catalog. It doesn't say 'use search_catalog to filter by keyword' or note any exclusions, leaving the agent to infer the list-versus-search split from the tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search the llmsmap.ru catalog by product name or URL.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of sites to return, capped at 50. | |
| query | Yes | Search term (product name or part of URL). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions only the search capability and does not reveal any behavioral traits such as output format, pagination, read-only nature, rate limits, or error handling. The limit parameter's cap is left undocumented in the description, and no mention is made of what the tool returns.
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 a single, concise sentence that immediately states the tool's purpose and search criteria. It is front-loaded and free of filler, making it easy to parse quickly.
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 search tool with no annotations and no output schema, the description should clarify what results to expect and when to use it. It only covers the search function, missing usage guidance and behavioral expectations. The cap on limit is present in the schema but not highlighted, and no information about the result format is offered. The simplicity of the tool does not excuse these gaps.
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 both parameters are already described in the schema. The description's phrase 'by product name or URL' adds minimal extra meaning over the schema's 'Search term (product name or part of URL)', offering no additional syntax or format details. The limit parameter is not elaborated upon in the description. This aligns with the baseline of 3 for high schema coverage.
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 clear verb ('Search'), a specific resource ('the llmsmap.ru catalog'), and the search criteria ('by product name or URL'). It is easy to distinguish from the sibling 'list_catalog' because 'search' implies filtering while 'list' implies enumeration.
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 gives no explicit guidance on when to use this tool versus the sibling 'list_catalog' or any alternatives. It does not specify conditions like 'use when you need a specific product, not a full listing', leaving the choice ambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
list_catalogsearch_catalogClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
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Claim ownership of the server listing
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Add one secure layer between your agents and this server.
The two tools have clearly distinct purposes: one lists the catalog, the other searches it. There is no overlap or ambiguity in their intended use, making misselection unlikely.
Both tool names follow a consistent verb_noun pattern (list_catalog, search_catalog), which is predictable and easy to understand. Naming is uniform and follows a standard convention.
With only two tools, the server feels minimal, but for a read-only directory catalog, listing and searching cover the core functionality. The count is at the lower end of the acceptable range.
The tool surface covers the primary operations for a directory: browsing all entries and searching by name/URL. Minor gaps exist (e.g., no filters, categories, or detailed views), but the core read-only workflow is complete.