List the curated GitHub topics that have a directory page, with active-server counts. Topics are assigned by repository owners and imported verbatim, so the full dataset carries thousands of them; this returns only the curated subset. search_servers accepts any topic string, curated or not.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that topics are imported verbatim from repo owners, are curated, and that active-server counts accompany each topic. It doesn't specify output format, but this is a simple zero-parameter list.
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?
Three short sentences, front-loaded with the core purpose, followed by meaningful curation context and a pointer to the sibling. No filler.
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 zero-parameter listing tool, the description covers scope, data source, and relationship to search_servers. It doesn't define 'directory page' or detail 'active-server counts,' but the operation is simple enough for an agent to call correctly.
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?
Tool has zero parameters; schema coverage is trivially 100% and baseline for 0 params is 4. No parameter documentation needed.
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?
States a specific verb and resource ('List the curated GitHub topics that have a directory page, with active-server counts') and explicitly distinguishes from search_servers, which accepts any topic string. The curation context is clear from the first sentence.
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 explains that the full dataset has thousands of topics while this tool returns only the curated subset, and points to search_servers for non-curated topics. It doesn't explicitly say when not to use sibling tools like list_categories, but the core alternative is covered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly different primary purpose: dataset metadata, single-server lookup, category listing, topic listing, and searching. The only mild overlap is between list_categories and list_topics, but their descriptions and use cases are distinct enough to avoid real confusion.
Tool names follow a consistent verb_noun pattern: get_*, list_*, and search_*. All use lowercase snake_case, making the naming predictable and easy to navigate.
With five tools, the server is well-scoped for a read-only MCP server directory. Each tool covers a necessary access pattern: browse taxonomy, search servers, fetch details, and inspect dataset metadata.
The surface covers the core directory workflows: search, filter by category/topic, retrieve individual entries, and understand dataset provenance. The lack of an unfiltered 'list all servers' endpoint is a minor gap, but the search and category/topic enumeration paths provide workarounds.