Mailtrap Email Sending

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Every tool has a clearly distinct purpose with no ambiguity. Template management tools (create, delete, list, update) are separate from sandbox operations (get messages, send sandbox email, show message) and production email sending, making misselection unlikely.
Naming Consistency4/5
Mostly consistent with a verb-noun pattern using kebab-case, but there is a minor deviation: 'get-sandbox-messages' and 'show-sandbox-email-message' both retrieve sandbox data with different verbs ('get' vs 'show'), slightly breaking the pattern.
Tool Count5/5
Well-scoped with 8 tools, each earning its place. This covers core email sending workflows (production and sandbox) and template management (CRUD operations), fitting the server's purpose without being overwhelming.
Completeness5/5
Complete coverage for the email sending domain with no obvious gaps. It includes full CRUD for templates, sandbox testing (send, list, view), and production email sending, allowing agents to handle all typical email workflows without dead ends.
Average 3.4/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 2 of 2 community issues answered or closed in the last 6 months
- 49 commits in the last 12 weeks
- Last stable release on August 20, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action but lacks details on permissions, rate limits, response format, or whether this is a read-only operation. For a list operation with zero annotation coverage, this leaves significant gaps.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words or redundancy, making it appropriately front-loaded and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain the return format, pagination behavior beyond schema hints, or how it interacts with sibling tools, leaving the agent with insufficient context for a list operation.
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 description coverage is 100%, so the schema fully documents all three parameters (page, last_id, search). The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'list of messages from the sandbox test inbox', making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'show-sandbox-email-message' which might retrieve a single message, leaving some ambiguity about scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'show-sandbox-email-message' or 'send-sandbox-email', nor does it mention any prerequisites or contextual constraints for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states 'show' implies a read operation, but doesn't disclose behavioral traits like whether it requires authentication, rate limits, error handling (e.g., invalid message_id), or what 'details and content' includes (e.g., headers, body, attachments). This leaves significant gaps for a tool with no annotation coverage.
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 a single, efficient sentence with zero waste. It's front-loaded with the core purpose and includes essential context ('from the sandbox test inbox'), making it appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with full schema coverage and no output schema, the description is minimally adequate. It specifies the resource scope ('sandbox test inbox') but lacks behavioral details (e.g., response format, error cases) and usage guidelines, leaving room for improvement despite the tool's low complexity.
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 has 100% description coverage, with 'message_id' documented as 'ID of the sandbox email message to retrieve'. The description adds no additional parameter semantics beyond this, such as format examples or constraints. Baseline 3 is appropriate when schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'show' and the resource 'sandbox email message details and content', specifying it's from the 'sandbox test inbox'. It distinguishes from siblings like 'get-sandbox-messages' (which likely lists messages) and 'send-sandbox-email' (which sends messages), but doesn't explicitly contrast them in the description text.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid message_id from the sandbox), exclusions, or comparisons to sibling tools like 'get-sandbox-messages' for listing messages first.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations include 'destructiveHint: true', indicating this is a write operation with potential side effects. The description adds that it uses 'Mailtrap Email API' and supports multiple recipients, providing some context beyond annotations. However, it doesn't disclose additional behavioral traits like rate limits, authentication needs, or what 'destructive' entails (e.g., email delivery, no undo). With annotations covering the safety profile, a 3 is appropriate for adding moderate value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: one stating the purpose and one adding a usage detail. It's front-loaded with the core functionality. However, the second sentence could be more informative (e.g., clarifying 'multiple recipients' vs. schema details), slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (8 parameters, destructive operation) and lack of output schema, the description is moderately complete. It covers the basic purpose and API context but lacks details on when to use, behavioral nuances, or return values. With annotations providing some safety info, it's adequate but has clear gaps for a mutation tool.
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 has 100% description coverage, with clear documentation for all 8 parameters (e.g., 'from' as 'Email address of the sender'). The description doesn't add meaning beyond the schema, such as explaining parameter interactions or constraints. According to the rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Send an email to your recipient email address using Mailtrap Email API.' It specifies the action (send), resource (email), and technology (Mailtrap Email API). However, it doesn't explicitly differentiate from sibling tools like 'send-sandbox-email' or 'get-sandbox-messages', which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance: 'You can send emails to multiple recipients at once.' It doesn't specify when to use this tool versus alternatives like 'send-sandbox-email' (e.g., for testing vs. production), nor does it mention prerequisites, exclusions, or context for use. This lack of explicit guidance limits its effectiveness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations include 'destructiveHint: true', which already indicates this is a mutation operation. The description adds minimal behavioral context beyond this, as 'Update an existing email template' implies modification but doesn't detail effects like whether changes are reversible, permission requirements, or rate limits. With annotations covering the destructive nature, the description provides basic but insufficient additional insight.
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 a single, efficient sentence with zero wasted words, front-loading the core action ('Update') and resource. It's appropriately sized for the tool's complexity, making it easy for an agent to parse quickly without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (6 parameters, destructive operation, no output schema), the description is inadequate. It lacks information on return values, error conditions, or how partial updates are handled (e.g., if only some fields are provided). With annotations covering only destructiveness, more context is needed for safe and effective use.
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 has 100% description coverage, with each parameter clearly documented (e.g., 'template_id' as 'ID of the template to update'). The description adds no extra meaning beyond what the schema provides, such as explaining relationships between parameters or usage examples. Baseline 3 is appropriate since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Update') and resource ('an existing email template'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create-template' or 'list-templates' beyond the basic action, missing explicit comparison that would earn a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create-template' for new templates or 'delete-template' for removal. It also doesn't mention prerequisites (e.g., needing an existing template ID) or contextual constraints, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare destructiveHint=true, indicating this is a write operation. The description adds minimal behavioral context beyond that - it confirms creation but doesn't specify what happens on success/failure, whether templates are immediately usable, or any permissions required. No contradiction with annotations exists.
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 a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a creation tool with good schema documentation and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with destructiveHint annotation and no output schema, the description is minimally adequate. It identifies the resource type but doesn't explain what an email template entails in this system, how it's used, or what the creation result looks like. The combination of basic description and annotations provides the essentials but leaves contextual gaps.
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?
With 100% schema description coverage, all parameters are documented in the schema. The description adds no additional parameter information beyond what's already in the schema descriptions. The baseline score of 3 reflects adequate but not enhanced parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('create') and resource ('email template'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update-template' beyond the obvious verb difference, nor does it specify what distinguishes a template from other email-related resources in the system.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like needing to be logged in), when to choose this over 'update-template' for existing templates, or how it relates to email-sending tools like 'send-email' or 'send-sandbox-email'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds minimal behavioral context beyond the readOnlyHint annotation. It doesn't specify whether this returns a paginated list, the format of returned templates, or any rate limits. However, it doesn't contradict the annotation (which correctly indicates a read-only operation).
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 a single, efficient sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core purpose immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with no parameters and no output schema, the description is minimally adequate. However, it lacks details about the return format (e.g., structured list vs. raw data) and doesn't leverage the sibling context to clarify its role in the template management workflow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the description appropriately doesn't need to explain parameters. The baseline for this scenario is 4 since there are no parameters to document.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('all email templates'), making the purpose unambiguous. However, it doesn't differentiate from potential sibling tools like 'get-sandbox-messages' or explain what distinguishes listing templates from other template operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'create-template', 'update-template', or 'delete-template'. It doesn't mention prerequisites, context for listing templates, or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare destructiveHint=true, indicating this is a destructive operation. The description adds value by specifying 'Delete an existing email template,' which reinforces the destructive nature and clarifies the resource type. However, it doesn't provide additional behavioral details like confirmation prompts, error handling, or permissions required beyond what annotations imply.
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 a single, clear sentence with no unnecessary words. It's front-loaded with the core action and resource, making it highly efficient and easy to parse. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's destructive nature (annotations cover this) and simple single-parameter schema, the description is adequate but minimal. It lacks output information (no schema provided) and doesn't address error cases or dependencies on other tools (e.g., needing to list templates first). For a destructive tool, more context would be beneficial.
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 has 100% description coverage, with the 'template_id' parameter fully documented. The description doesn't add any parameter-specific information beyond what the schema provides, such as format examples or constraints. Since the schema coverage is high, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Delete') and resource ('an existing email template'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'update-template' or 'list-templates' in terms of scope or intent, which prevents a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'update-template' or 'list-templates', nor does it mention prerequisites (e.g., needing a valid template_id). It simply states what the tool does without contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds valuable behavioral context beyond the annotations. While annotations only indicate destructiveHint=false (non-destructive), the description clarifies that emails go to a 'test inbox' and won't reach actual recipients, which is crucial for understanding the tool's testing/simulation behavior. No contradiction with annotations exists.
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 a single, efficient sentence that front-loads the key information (sandbox mode, test inbox, no delivery) with zero wasted words. Every element serves a clear purpose in distinguishing this tool's behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with good annotations (destructiveHint=false) and full schema coverage, the description provides sufficient context about the sandbox/testing behavior. The main gap is the lack of output schema, but the description compensates by clarifying the test inbox destination. It adequately covers the tool's purpose and usage 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?
With 100% schema description coverage, all parameters are well-documented in the schema itself. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline of 3 for adequate coverage without extra value.
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 specific action ('send an email') and resource ('in sandbox mode to a test inbox'), with explicit differentiation from normal email sending ('without delivering to your recipients'). It distinguishes from the sibling 'send-email' tool by specifying the sandbox/testing context.
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?
The description explicitly states when to use this tool ('in sandbox mode to a test inbox') and when not to use it ('without delivering to your recipients'), providing clear context for testing versus production email sending. It implicitly contrasts with the sibling 'send-email' tool for actual delivery.
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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