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SendGrid MCP by usefulapi

Get email stats

sendgrid_get_stats
Read-only

Get global email statistics over a date range (delivered, opens, clicks, bounces, spam reports, etc.). Returns an array of { date, stats: [{ metrics: {...} }] }. SendGrid: GET /v3/stats.

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of results to return.
offsetNoNumber of results to skip (for pagination).
end_dateNoEnd date in YYYY-MM-DD format (defaults to today).
start_dateYesStart date in YYYY-MM-DD format (required).
aggregated_byNoHow to group the returned statistics.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

readOnlyHint=true already establishes the safe-read profile, and the description adds value beyond that by disclosing the exact return shape (array of {date, stats:[{metrics}]}) and the underlying endpoint. It omits auth requirements, rate limits, and pagination behavior, but the return-format disclosure is substantive for a tool with no output schema.

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?

Three tight sentences: purpose first, return shape second, endpoint last. No filler, and the most decision-relevant information (what it returns and over what range) is front-loaded.

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

Completeness4/5

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

With no output schema, the description compensates by describing the return structure, and annotations cover the safety profile while the schema fully covers parameters. The only gap is usage routing against the many sibling tools, which is not addressed.

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%, so all five parameters (limit, offset, end_date, start_date, aggregated_by) are already documented in the schema. The description only restates the date-range concept and lists returned metrics; it adds no syntax or format detail (e.g. date interplay, aggregation semantics) beyond what the schema provides. Baseline 3 applies.

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?

Specific verb (Get) and resource (global email statistics) with an enumerated metric list and explicit date-range scope, so the agent knows exactly what it produces. The word 'global' implicitly separates it from per-category siblings like sendgrid_list_bounces, but no sibling is named outright, so it falls short of full differentiation.

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?

'Global ... over a date range' weakly implies the aggregate-overview use case versus the targeted listing tools, but there is no explicit when-to-use, when-not, or named alternative. Usage is only inferable from the scope wording.

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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