test_email_webhookSend one signed test payload to the mailbox webhook URL. Returns HTTP status and success/failure. Tests are not retried; live inbound events are durable and retried up to three times. API: POST /api/emails/{address}/webhook/test.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Mailbox slug | |
| domain | Yes | Mailbox domain |
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?
With no annotations provided, the description carries the behavioral transparency burden and does well: it states the payload is signed and one-time, the response includes HTTP status and success/failure, and tests are not retried. It does not disclose potential side effects or prerequisites, but for a testing action the key behavioral traits are covered.
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?
Four short sentences deliver the purpose, return behavior, exceptional retry semantics, and a concrete REST endpoint with zero filler. Important constraints are front-loaded, and the API path reinforces the message without needing a separate schema.
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 two-parameter, no-output-schema tool, the description is quite complete: expected input context (mailbox domain/slug), endpoint, response type, and a key reliability caveat. Minor gaps exist around preconditions—such as whether a webhook URL must already be configured—but these do not prevent effective usage.
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?
Parameter descriptions in the input schema are 100% complete ('Mailbox slug' and 'Mailbox domain'), so the schema already provides the parameter meaning. The description does not add parameter-level detail beyond the schema, but that is acceptable because the schema is fully descriptive.
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 states a precise action ('Send one signed test payload to the mailbox webhook URL') with a clear target resource (the mailbox webhook) and an exact endpoint. It distinguishes itself from live event handling by contrasting the non-retried test behavior with durable live inbound events, so an agent can tell it apart from related webhook tools.
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 use case is clear: this is the tool to email a webhook on demand and get a direct HTTP status result. Although it does not name sibling alternatives like replay_webhook_delivery, the retry distinction gives practical guidance on when a test result should not be treated like a live durable delivery.
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.
While most tools have distinct purposes, several clusters overlap significantly (e.g., check_email, check_email_deliverability, get_email_deliverability, get_domain_email_status; buy_domain, buy_aftermarket, acquire_domain). The descriptions are detailed and help differentiate, but the sheer number of tools makes it challenging for an agent to select the correct one without careful reading.
The dominant pattern is verb_noun with underscores (e.g., create_mailbox, list_domains), but there are notable inconsistencies: destructive actions mix delete/remove/cancel/revoke/unsell, and a few names deviate entirely (search, dns_check, domain_status). The pattern is recognizable but not uniformly applied.
With 122 tools, this vastly exceeds the 50+ threshold for extreme mismatch. Even for a comprehensive domain and email platform, the tool count is overwhelming and will likely hinder agent performance through excessive choice and context bloat.
The server covers a wide range of domains, DNS, email, marketplace, negotiations, transfers, webhooks, tokens, and billing. Minor gaps exist, such as no update operation for mail rules, no direct domain deletion, and limited mailbox configuration beyond forwarding and credentials, but most lifecycle workflows are supported.