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search_servers

Search the MCP server directory by keyword and/or filters. Keyword matches name, description, and GitHub topics. Returns active servers sorted by relevance then stars. Supply at least one of query, category, or topic — with no query, filters alone enumerate a whole category or topic by stars. Data refreshes nightly from the public GitHub API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 10)
queryNoKeywords, e.g. 'postgres', 'browser automation'. Optional if category or topic is given.
topicNoOptional GitHub topic filter, exact match, e.g. 'kubernetes'. Any topic string works, not only the curated ones from list_topics.
categoryNoOptional category slug filter, e.g. 'databases' (see list_categories)
languageNoOptional implementation language filter, e.g. 'Python'

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden — and it delivers: active-only filtering, sort order (relevance then stars), nightly refresh from the public GitHub API, and match scope are all disclosed. This goes well beyond the schema and gives an agent accurate expectations for ordering, freshness, and what gets filtered out.

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 sentences of roughly 60 words, each carrying distinct information: search scope, result ordering, and invocation requirements plus data freshness. Content is front-loaded with the verb+resource, and there is zero redundancy with the schema.

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 5-parameter search tool, the description covers matching, filtering, ordering, freshness, and the required-input constraint, while the schema documents every parameter. The one gap is result shape: no output schema exists and the description never states what fields each result contains, so an agent cannot be certain results carry the identifier needed to chain to get_server.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers all 5 parameters at 100%, so the baseline is 3. The description adds real value by stating the cross-parameter constraint (at least one of query/category/topic) and the interpretation of a missing query (category/topic enumeration by stars) — information that cannot be derived from any individual parameter's schema description.

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?

Opens with a specific verb+resource: 'Search the MCP server directory by keyword and/or filters.' It then pins down exact matching semantics (name, description, GitHub topics), which distinguishes it from siblings like get_server (single-server fetch), list_categories, and list_topics without needing to open their schemas.

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?

Provides explicit invocation guidance: 'Supply at least one of query, category, or topic,' and explains the zero-query path where filters alone enumerate a whole category or topic by stars. Parameter descriptions also cross-reference siblings (list_categories, list_topics), orienting the agent. It never explicitly states when not to use this tool versus get_server, so it just misses the top bar.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.9/5.0
Disambiguation4/5

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.

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness4/5

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.