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Sealmetrics MCP Server

Sealmetrics MCP Server

by sealmetrics
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

generate_conversion_pixel

Create tracking pixels for conversions and microconversions to measure marketing performance in Google Tag Manager. Specify event types like sales or newsletter signups with optional monetary values.

Instructions

Generate a Sealmetrics tracking pixel for conversions or microconversions, ready for Google Tag Manager

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "generate_conversion_pixel"
  }
}

Input Schema

NameRequiredDescriptionDefault
account_idNoYour Sealmetrics account ID (optional if SEALMETRICS_ACCOUNT_ID is set)
event_typeNoEvent type: 'conversion' or 'microconversion'conversion
labelNoEvent label (e.g., 'sales', 'add-to-cart', 'newsletter-signup')
valueNoMonetary value for the event (optional)
ignore_pageviewNoSet to true to avoid counting an additional pageview (use when tracking button clicks on already-tracked pages)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
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 of behavioral disclosure. It states the tool generates a tracking pixel but lacks details on side effects (e.g., whether it triggers an API call, stores data, or requires authentication), performance considerations (e.g., rate limits), or output format (e.g., HTML/JavaScript code). The mention of 'ready for Google Tag Manager' implies integration but does not specify behavioral traits.

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?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It avoids redundancy and wastes no words, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's function.

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?

Given the tool has 5 parameters, no annotations, and no output schema, the description is insufficiently complete. It does not explain what the tool returns (e.g., the pixel code format), potential errors, or integration steps with Google Tag Manager. For a tool that likely outputs code or a URL, the lack of output details is a significant gap, leaving the agent uncertain about the result.

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?

The input schema has 100% description coverage, providing clear documentation for all 5 parameters (e.g., 'event_type' with enum values, 'ignore_pageview' with usage context). The description does not add any additional semantic meaning beyond the schema, such as explaining parameter interactions or providing examples. With high schema coverage, the baseline score of 3 is appropriate as the description does not compensate but also does not detract.

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?

The description clearly states the tool's purpose: 'Generate a Sealmetrics tracking pixel for conversions or microconversions, ready for Google Tag Manager.' It specifies the verb ('Generate'), resource ('tracking pixel'), and context ('for conversions or microconversions'), but does not explicitly differentiate from sibling tools like 'get_conversions' or 'get_microconversions', which appear to be read-only data retrieval tools rather than pixel generation tools.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It mentions the tool is 'ready for Google Tag Manager,' which hints at a deployment context, but does not specify scenarios, prerequisites, or comparisons with sibling tools. For example, it does not clarify if this should be used for real-time tracking versus historical data retrieval from the sibling tools.

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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