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MisarMail MCP Server

by io.github.Misar-AI

get_monetization_stats

Read-onlyIdempotent

Get newsletter monetization figures: paid subscribers, monthly recurring revenue, churn, and revenue trend.

Use it for 'how is the paid newsletter doing' questions. These are account-level totals over a trailing window, so they cannot be broken down per campaign — use get_revenue_attribution for that.

Reads only; no billing state is changed and no subscriber is charged. Requires an API key. Revenue figures are reported in minor currency units unless stated otherwise, so check before presenting them as dollars. Zero paid subscribers is a real answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
periodNoTime window (default 30d)

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description reinforces this in domain terms ('Reads only; no billing state is changed and no subscriber is charged') and adds new behavioral details: API key required, revenue in minor currency units, and the zero-subscriber edge case. This goes beyond the annotation hints.

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 tightly focused sentences: purpose, usage guidance, and safety/caveats. Every sentence earns its place without repeating schema or annotation fields. The structure front-loads the core function and then layers context efficiently.

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?

For a simple read-only stats tool with one optional parameter and no output schema, the description covers purpose, usage boundaries, authentication, unit handling, and an edge case (zero subscribers). It also states what it cannot do, making it self-contained for an agent to decide when to invoke it.

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 schema fully documents the only parameter (period with enum values and default), so the description adds no further parameter-level meaning. The 'trailing window' phrase is consistent with but does not expand on the schema's 'Time window' description, so baseline 3 is appropriate.

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 retrieves newsletter monetization figures (paid subscribers, monthly recurring revenue, churn, revenue trend) with a specific resource scope. It explicitly differentiates from get_revenue_attribution, which handles per-campaign breakdowns, making it distinct among siblings.

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?

Provides a direct use case ('how is the paid newsletter doing') and an explicit alternative when per-campaign breakdown is needed ('use get_revenue_attribution for that'). Also mentions the API key requirement, giving clear prerequisites for invocation.

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

A3.7/5.0
Disambiguation3/5

Most tools are cleanly separated by resource and action, and the descriptions do a good job of cross-referencing related tools. However, there are several close clusters—get_analytics vs generate_report, get_deliverability_score vs run_deliverability_audit, check_dmarc vs verify_domain, and list_emails vs list_inbox_conversations vs get_email—that could cause an agent to pick the wrong one. The detailed descriptions reduce but do not eliminate this ambiguity.

Naming Consistency5/5

Tool names follow a consistent snake_case verb_noun pattern throughout: create_, get_, list_, send_, toggle_, and so on. Even multi-word actions like select_ab_test_winner and categorize_inbox_emails stay uniform. The only slight deviation is the bare verb upgrade, but it is readable and does not break the overall pattern.

Tool Count2/5

54 tools is far beyond the typical well-scoped MCP surface and lands heavily in the 'too many' range. While the domain is broad, many tools could be consolidated—multiple analytics/reporting tools, several deliverability checks, and separate email/inbox listing tools create redundancy. The sheer number increases selection overhead and makes the toolset harder for an agent to navigate reliably.

Completeness3/5

The core email marketing lifecycle is represented: domains, contacts, campaigns, templates, automations, sends, and analytics all have main operations. However, there are notable gaps—no update/delete for campaigns, templates, forms, or automations; no create/update/delete for forms; no sandbox enable/disable; and no way to install marketplace items. These are workable gaps but would cause failures for agents trying to perform full lifecycle management.

Resources