Revuo.ai MCP

mcp.score_server

Read-only

Score an MCP server against the Revuo quality rubric. Pass either a product slug (scored from cached probe data on the product's direct-probe MCP entry; fast) OR an endpoint URL (probed live). Returns: { target, server, summary { coreAwarded/Max/Percent, extensionAwarded/Max/Percent, probedAt }, categories[] (ServerMetadata, CapabilityQuality, ConfigurationUX, RevuoExtensions), checks[] (every rubric check with awarded/max/passed/evaluated/fixSuggestion/evidence), topFixes[] (failed checks ranked by points-at-stake), probe (probe diagnostics) }. Core score (max 100) is Smithery-comparable. Extension score covers Revuo-specific signals (response time today; freshness, error envelope, schema stability are not yet implemented and report evaluated=false — excluded from totals, never counted as a failure). A check with evaluated=false is a Revuo gap, not the server's fault. Errors: { error: { code: 'bad_input'|'not_found', ... } }.

Input Schema

TableJSON Schema

Name	Required	Description
`url`	No	MCP endpoint URL (HTTPS) to probe and score. Mutually exclusive with slug.
`slug`	No	Product slug whose direct-probe MCP server to score. Mutually exclusive with url.
`refresh`	No	When passing slug, force a fresh probe instead of using cached probe data. Default false.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`error`	No
`probe`	No
`checks`	No
`server`	No
`target`	No
`summary`	No
`topFixes`	No
`categories`	No

TDQS

A4.6/5.0

Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=true. The description aligns by explaining the tool is read-only and returns score data. It also discloses that checks with evaluated=false are Revuo gaps, not server faults, adding context beyond annotations. A small deduction for not explicitly stating that the tool does not modify any resources, though it's implied.

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?

The description is informative and well-structured, starting with the main purpose, then detailing modes, return values, and special notes. It is slightly verbose but each sentence adds necessary context. Could be tightened by removing some redundant phrases, but overall efficient.

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

Completeness5/5

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

Given the tool's complexity (two modes, return structure with multiple fields), the description covers all aspects: mode selection, return object, error handling, and special case of evaluated=false. Output schema exists and is referenced, so return values are fully documented.

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 coverage is 100%, with each parameter described. The description adds value by clarifying the relationship between slug and url (mutually exclusive) and explaining the refresh parameter's effect. This compensates for the lack of enum values or nested objects.

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?

Description clearly states it scores an MCP server against the Revuo quality rubric, with two distinct modes (slug for cached, fast; endpoint URL for live probe). This verb+resource combination uniquely identifies the tool and differentiates it from siblings, which are about listing, searching, and managing categories/products/tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly explains when to use slug (cached probe data, fast) vs endpoint URL (live probe), and notes mutual exclusivity. Also describes the refresh parameter for forcing a fresh probe. Provides clear context for choosing between alternatives.

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

A4.3/5.0

Disambiguation4/5

Tools are generally distinct, but products.search and products.find_by_capability overlap in capability-based search, causing potential ambiguity. However, descriptions clarify the differences.

Naming Consistency3/5

Naming follows a dot-separated pattern with verb-noun, but there are inconsistencies: use of underscores (mcp.score_server), varying verb choices (list, find, get, search), and mixing of object and action order.

Tool Count5/5

14 tools cover a comprehensive range of functionality for a directory/MCP server—from browsing categories to detailed tool search and drift detection—without feeling excessive.

Completeness4/5

The set covers most key operations (CRUD, search, rankings, MCP setup, change detection), but lacks tools for updating or modifying data, which is acceptable for a mostly read-driven directory API.

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