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mailgun

Mailgun MCP Server

Official
by mailgun

get--v3-stats-filter

Retrieve filtered and grouped email delivery statistics for your Mailgun account to analyze campaign performance and track specific events over time.

Instructions

Filtered/grouped totals for entire account

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
startNo
endNo
resolutionNo
durationNo
eventYes
filterNo
groupNo
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. The description mentions 'filtered/grouped totals' which implies a read-only aggregation operation, but it doesn't specify whether this requires authentication, what the output format looks like, whether there are rate limits, or if the data is real-time vs historical. For a tool with 7 parameters and no annotation coverage, this is a significant gap in behavioral context.

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 extremely concise at just 5 words, which is appropriate for its length. However, it's arguably too brief given the tool's complexity (7 parameters, no annotations, many siblings). While front-loaded with the core concept, it lacks the detail needed for effective tool selection and usage.

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's complexity (7 parameters, 1 required, no annotations, no output schema, and many similar sibling tools), the description is inadequate. It doesn't explain what kind of statistics are returned, how parameters affect the output, or how this differs from other statistical tools in the server. The agent would struggle to use this tool correctly without additional documentation or trial-and-error.

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

Parameters2/5

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

The schema has 0% description coverage for all 7 parameters, and the description provides no information about what any parameter means or how they interact. While the description mentions 'filtered/grouped totals,' it doesn't explain which parameters control filtering versus grouping, what values are acceptable, or how 'event' (the only required parameter) relates to the statistics being retrieved. The description fails to compensate for the complete lack of schema documentation.

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

Purpose3/5

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

The description 'Filtered/grouped totals for entire account' states the general purpose (retrieving aggregated statistics) but lacks specificity about what kind of statistics or resources are involved. It doesn't clearly distinguish this tool from its many siblings (like 'get--v3-domain-stats-total' or 'get--v3-domain-tag-stats'), which appear to handle similar statistical data but for different scopes or entities.

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?

There is no guidance on when to use this tool versus alternatives. With 50+ sibling tools including many other 'get--v3-stats-*' and 'get--v3-domain-*' variants, the description provides no context about appropriate use cases, prerequisites, or exclusions. The agent must infer usage from the tool name and schema alone.

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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