Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@turbosmtp send a test email to john@example.com with subject 'Welcome'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
A simple Node.js MCP (Model Context Protocol) server for sending emails and view statistics using TurboSMTP, designed for easy integration and testing. This server exposes an MCP-compatible API endpoint to allow other services to send emails via TurboSMTP.
Send emails and check statistics via TurboSMTP with a simple MCP API
Easy configuration and setup
Includes a test script for quick validation
Related MCP server: MailPace MCP Server
Node.js (v14 or higher recommended)
A valid TurboSMTP account and credentials
git clone https://github.com/debba/turbosmtp-mcp-server.git
cd turbosmtp-mcp-server
npm installSet your TurboSMTP credentials in the appropriate configuration section of the code (see email-service.js).
You may want to use environment variables or a configuration file for production use.
node mcp-turbosmtp-server.jsThe server will start and expose an MCP API endpoint for sending emails.
You can use the provided test script:
node tests.jsEdit tests.js to set the recipient and message details.
mcp-turbosmtp-server.js — Main MCP server file
email-service.js — Email sending logic using TurboSMTP
tests.js — Script to test turboSMTP features via API
package.json — Project dependencies and scripts
MIT
Retrieve analytics data from TurboSMTP for a specific date range
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No | Filter for analytics data (optional) | |
| from | Yes | Start date for analytics (format: YYYY-MM-DD) | |
| limit | No | Number of results per page (optional) | |
| page | No | Page number (optional) | |
| to | Yes | End date for analytics (format: YYYY-MM-DD) | |
| tz | No | Timezone (optional, e.g., "Europe/Rome", "America/New_York") |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. While 'Retrieve' implies a read operation, the description doesn't disclose important behavioral traits like authentication requirements, rate limits, pagination behavior (implied by page/limit parameters but not explained), error conditions, or what format the analytics data returns.
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?
Single sentence, zero waste, front-loaded with the core purpose. Every word earns its place - specifies what's retrieved, from where, and the primary constraint.
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 6-parameter tool with no annotations and no output schema, the description is inadequate. It doesn't explain what analytics data includes, how results are structured, pagination behavior, authentication needs, or error handling. The agent would struggle to use this effectively without trial and error.
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?
Schema description coverage is 100%, so the schema already documents all 6 parameters thoroughly. The description adds no parameter-specific information beyond implying date range usage through 'for a specific date range', which the schema already covers with 'from' and 'to' parameters. 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve' and resource 'analytics data from TurboSMTP' with scope 'for a specific date range'. It distinguishes from 'send_email' but doesn't explicitly differentiate from 'get_analytics_data_by_id' which likely retrieves data by ID rather than date range.
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?
No guidance on when to use this tool versus alternatives. The description doesn't mention when to use this date-range based retrieval versus 'get_analytics_data_by_id' (likely ID-based retrieval) or when analytics data retrieval is appropriate versus email sending.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Retrieve analytics data from TurboSMTP by specific message ID
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Message ID |
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 'Retrieve' (implying a read operation) but doesn't cover aspects like authentication needs, rate limits, error handling, or what the returned analytics data includes. This leaves significant gaps for a tool that likely accesses external data.
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?
The description is a single, efficient sentence with zero wasted words. It front-loads the key action and resource, making it easy to parse quickly. Every word earns its place by conveying essential information.
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?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'analytics data' entails (e.g., metrics, timestamps, status), potential errors, or dependencies. For a tool interacting with an external service like TurboSMTP, more context is needed to use it effectively.
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 schema description coverage is 100%, with the single parameter 'id' documented as 'Message ID'. The description adds minimal value beyond this by specifying 'by specific message ID', reinforcing the parameter's purpose but not providing additional syntax or format details. This meets the baseline for high schema coverage.
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 the action ('Retrieve analytics data') and resource ('from TurboSMTP by specific message ID'), making the purpose understandable. However, it doesn't explicitly differentiate from its sibling 'get_analytics_data' (which likely retrieves analytics data more broadly), so it falls short of 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.
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 'get_analytics_data' or 'send_email'. It mentions retrieving by 'specific message ID', which implies usage for individual records, but lacks explicit when/when-not instructions or named alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Send an email via TurboSMTP
| Name | Required | Description | Default |
|---|---|---|---|
| from | No | Sender email address (optional, uses configured one if not specified) | |
| html | No | HTML content of the email (optional) | |
| subject | Yes | Email subject | |
| text | Yes | Text content of the email | |
| to | Yes | List of recipient email addresses |
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. While 'Send an email' implies a write operation, it doesn't mention authentication requirements, rate limits, error handling, or what happens upon success (e.g., confirmation, message ID). This leaves significant gaps for an agent to understand the tool's behavior.
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?
The description is extremely concise—a single sentence that directly states the tool's function without any unnecessary words. It's front-loaded and wastes no space, making it easy to parse quickly.
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 mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the tool returns, error conditions, or behavioral nuances. Given the complexity of email sending (which involves delivery status, potential failures, etc.), more context would be needed for an agent to use it effectively.
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% description coverage, providing clear documentation for all 5 parameters. The tool description adds no additional parameter information beyond what's already in the schema, so it meets the baseline expectation without adding extra value.
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 the action ('Send an email') and specifies the service ('via TurboSMTP'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools (which are analytics-related), though this isn't necessary since they serve completely different functions.
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 provides no guidance on when to use this tool versus alternatives, prerequisites, or any contextual constraints. It simply states what the tool does without indicating appropriate scenarios or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0get_analytics_dataget_analytics_data_by_idsend_emailThe tools have some overlap in purpose, as both get_analytics_data and get_analytics_data_by_id retrieve analytics data, which could cause confusion for an agent deciding between them. However, their descriptions clarify that one uses a date range and the other uses a message ID, providing enough distinction to avoid major misselection. The send_email tool is clearly distinct, targeting a different function.
All tool names follow a consistent verb_noun pattern (get_analytics_data, get_analytics_data_by_id, send_email), with clear and predictable naming conventions. There are no deviations in style or format, making it easy for agents to understand and use the tools.
With only 3 tools, this server feels under-scoped for an email service domain like TurboSMTP, which typically involves more operations such as managing contacts, templates, or handling bounces. The count is too low to cover the expected functionality, limiting agent capabilities.
There are significant gaps in the tool surface for an email service. While sending emails and retrieving analytics are covered, essential operations like managing email lists, handling attachments, or configuring settings are missing. This incompleteness will likely cause agent failures in broader email-related tasks.
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