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MisarMail MCP Server

by io.github.Misar-AI

list_templates

Read-onlyIdempotent

List the saved email templates on the account, with the variable placeholders each one expects.

Use it to pick a template before composing a send, and to see which variables you must supply — a template rendered with a missing variable goes out with a visible gap. These are the account's own templates; list_marketplace_items covers third-party ones instead.

Reads only; no template is created, edited, or sent. Requires an API key. An empty list means none have been saved yet, which is not an error.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default 1)
typeNoFilter by template type
limitNoResults per page (default 20)

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?

The description goes beyond annotations by stating it 'Reads only; no template is created, edited, or sent,' and adds practical details like requiring an API key and that an empty list is not an error. This fully discloses behavioral expectations.

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 well-structured and every sentence adds value: it covers purpose, usage, distinction from sibling, read-only nature, API key requirement, and empty-list semantics without unnecessary verbosity.

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?

The description is thorough for a read-only list operation. It explains the tool's role, expected inputs, output characteristics (placeholders), and edge cases (empty list, missing variable). Given no output schema, it sufficiently covers all necessary context.

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 already provides descriptions for all three parameters (page, type, limit), so the description adds little to parameter understanding. It does not elaborate on parameter usage beyond what the schema offers, but it does not need to.

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's function: listing saved email templates with their variable placeholders. It distinguishes itself from list_marketplace_items, which covers third-party templates, making it unambiguous.

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?

It explicitly explains when to use the tool ('pick a template before composing a send') and what information it provides (which variables must be supplied). It also contrasts with a sibling tool, giving clear guidance on selection.

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