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mukul-dutt

MentionsAPI MCP Server

mentions_watch

Monitor brand mentions across AI search surfaces and receive webhook alerts when mentions, rankings, or citations change.

Instructions

Set up a persistent monitor that webhooks you when brand mentions, ranks, or citations change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
brandYes
modeNoquick
intervalNodaily
webhook_urlYes
webhook_secretYes
trigger_onNo
Behavior4/5

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

Annotations indicate readOnlyHint=false (write), destructiveHint=false, and openWorldHint=true. The description adds behavioral context by specifying that the tool sets up a persistent monitor that sends webhooks on changes, which goes beyond the title. It does not contradict annotations.

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

Conciseness3/5

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

The description is a single 15-word sentence, which is concise and front-loaded with the core purpose. However, given the tool's complexity (7 parameters, webhook setup), the description could earn its place better by adding parameter guidance without becoming overly long. It is minimally adequate.

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

Completeness2/5

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

With 7 parameters, no output schema, and the expectation of webhook configuration, the description lacks critical details such as parameter semantics, return value (e.g., monitor ID), and behavior on duplicate monitors. The agent would struggle to use this tool correctly without additional context.

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

Parameters1/5

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

The input schema has 7 parameters with 0% description coverage. The main description does not mention or explain any parameter's purpose, default value, or constraints (e.g., 'query' vs 'brand', 'mode' enum options). This leaves the agent without guidance for filling parameters correctly.

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?

The description clearly states the tool sets up a persistent monitor that webhooks on changes to brand mentions, ranks, or citations. It uses a specific verb ('set up') and resource ('persistent monitor'), and the outcome is explicit. This distinguishes it from siblings like mentions_check (one-time check) and mentions_compare (comparison).

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

Usage Guidelines3/5

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

The description implies usage for continuous monitoring through phrases like 'persistent monitor' and 'webhooks you when...change,' but it does not explicitly state when to use this tool versus alternatives like mentions_check or mentions_discover. No exclusions or comparative guidance are provided.

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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