CV Email MCP Server

send_email

Send an email notification to a specified recipient with a custom subject and body. Use it to deliver alerts, updates, or messages directly from your workflow.

Instructions

Send an email notification

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "recipient": "<recipient>",
      "subject": "<subject>",
      "body": "<body>"
    },
    "name": "send_email"
  }
}

Input Schema

Name	Required	Description
`body`	Yes	Email body content
`subject`	Yes	Email subject line
`recipient`	Yes	Email address of the recipient

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 10, 2026

TDQS

C2.8/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry full behavioral disclosure. It states the primary action (send email) but does not disclose whether it actually sends or simulates, authentication requirements, rate limits, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single short sentence, which is concise, but it is also sparse and close to a tautology of the tool name. It doesn't add enough value to be considered well-structured, though it is not verbose.

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?

For a side-effectful tool like sending email, the description is incomplete. It lacks any behavioral context, output expectations, or error handling information. The schema covers parameters but not usage context, and there is no output schema.

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 description coverage is 100%, with each parameter having a clear description. The tool description adds no extra meaning beyond the schema, so the baseline of 3 applies.

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 'Send an email notification' clearly states the action (send) and the resource (email). It is unambiguous and implicitly distinguishes from sibling tools (parse_cv, ask_cv) which deal with CV processing, but lacks specific scope like recipient or purpose.

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?

No guidance is given on when to use this tool versus alternatives. The sibling tools are clearly different, but the description does not mention any context, exclusions, or alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server