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Glama

MisarMail MCP Server

by io.github.Misar-AI

get_automation

Read-onlyIdempotent

Get one automation workflow in full: its trigger, every step with its settings, and current enrolment counts.

Use it to understand exactly what an automation will do to contacts before activating it — the step list is where sends, waits and branches become visible. For the list of automations, use list_automations; to start or pause one, toggle_automation.

Reads only; reading a workflow does not enrol anyone or trigger a step. Requires an API key. An automation can be defined but inactive, so check its state rather than assuming it is running.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
automation_idYesAutomation ID (UUID)

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 mark readOnly/idempotent/non-destructive, but the description adds valuable context beyond those hints: 'reading a workflow does not enrol anyone or trigger a step', 'Requires an API key', and the caveat that an automation can be defined but inactive so its state should be checked. This is meaningful behavioral disclosure.

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 efficiently written, front-loaded with the main purpose, and every sentence adds useful context. It avoids redundancy and does not drone on, making it appropriately sized for a simple read tool.

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 one-parameter read-only tool with no output schema, the description is complete: it summarizes the returned content (trigger, steps, settings, counts), gives usage context, notes side-effect-free behavior, and warns about inactive automations. No important gaps remain.

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% with the single automation_id parameter already described as 'Automation ID (UUID)'. The description reinforces what the tool returns but does not add new parameter-level semantics beyond the schema, 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 uses a specific verb and resource: 'Get one automation workflow in full' and details what is included (trigger, steps, enrolment counts). It also distinguishes itself from list_automations by explicitly naming the sibling for listing all automations.

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 states exactly when to use the tool ('to understand exactly what an automation will do to contacts before activating it') and provides clear alternatives: list_automations for listing and toggle_automation for starting/pausing. This gives explicit when/alternative guidance.

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