Create a reusable email template. Use {{variable}} placeholders for personalisation — they are substituted at send time and previewable via render_template.
| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | HTML body (supports {{variables}}) | |
| name | Yes | Template name | |
| text | No | Plain text fallback body | |
| type | No | Template type (default: marketing) | |
| subject | Yes | Default subject line (supports {{variables}}) | |
| variables | No | Declared variable names used in the template |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark this as a non-read-only write operation; the description adds context beyond annotations by explaining variable substitution at send time and previewability via render_template. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with front-loaded action ('Create a reusable email template') and a follow-up sentence that explains variable behavior and links to a sibling tool. Every sentence earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a create tool with 6 parameters and no output schema, the description covers the core purpose and a key behavioral nuance (variable substitution). It doesn't explain return values, but that's less critical without an output schema; the schema handles parameter details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all six parameters, so the baseline is 3. The description reinforces the {{variable}} placeholder concept but does not add parameter-specific semantics beyond what the schema already documents.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Create a reusable email template', using a specific verb and resource. It distinguishes itself from siblings like render_template by focusing on creation, and introduces the key personalization feature via {{variable}} placeholders.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to create templates) and explicitly names render_template as the tool for previewing, providing a useful alternative. However, it does not explicitly state when not to use it or compare with other creation tools like create_campaign.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.