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mcp_recommend

Recommend MCP servers for a described goal or task, or suggest servers based on recent tool-call patterns when no query is provided.

Instructions

Get MCP server recommendations. Pass query to describe a goal or task (e.g. "file sync with cloud storage", "manage GitHub issues"). Omit query to get suggestions based on your recent tool-call patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of recommendations (default 5, max 20)
queryNoFree-text goal or task. When provided, recommends servers that match this intent using semantic/keyword/expansion search. When omitted, recommends based on usage history.
categoryNoOptional category slug to filter (e.g. 'developer-tools', 'data-databases'). Only used with `query`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.3

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions search modes (semantic/keyword/expansion) and usage-history fallback, but says nothing about permissions, rate limits, ranking behavior, or what the response contains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two efficient sentences front-load the core action and then explain the query/no-query branches without waste.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only recommendation tool with no annotations and no output schema, the description covers invocation modes but leaves return shape, ranking, and any auth or rate-limit context unaddressed.

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

Parameters3/5

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

Schema coverage is 100% and the schema already documents all three parameters thoroughly, including limits and the category dependency on query. The description's parameter guidance largely repeats the schema, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (get recommendations for MCP servers) clearly. It distinguishes the tool from siblings like mcp_discover and mcp_list_active by focusing on recommendations driven by query or usage patterns, though it doesn't explicitly name how it differs from those siblings.

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?

The description gives clear conditions for passing query vs omitting it, which covers the main usage modes. However, it doesn't mention when to prefer this over mcp_discover or other siblings that also surface servers.

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