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Email MCP Server

Email MCP Server

by 123jixinyu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

add_label

Idempotent

Assign a label to an email to categorize and organize it. Compatible with ProtonMail, Gmail, and IMAP accounts by copying or flagging.

Instructions

Add a label to an email. For ProtonMail, this copies the email into the corresponding Labels/ folder. For Gmail and standard IMAP, this sets a keyword flag on the message.

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": {
      "account": "<account>",
      "emailId": "<emailId>",
      "mailbox": "<mailbox>",
      "label": "<label>"
    },
    "name": "add_label"
  }
}

Input Schema

NameRequiredDescriptionDefault
labelYesLabel name to add (e.g., "Important", "Project-X")
accountYesAccount name from list_accounts
emailIdYesEmail ID (UID) from list_emails
mailboxYesMailbox containing the email (must be a real folder)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.3

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses important behavioral details beyond the annotations: for ProtonMail it copies the email to a folder, for Gmail/IMAP it sets a keyword flag. This adds meaningful context about side effects and provider variations, complementing the idempotentHint and destructiveHint annotations.

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?

Two concise sentences, front-loaded with the core action and immediately followed by necessary provider-specific details. Every word earns its place with no redundancy.

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?

The description, combined with full schema coverage and clear annotations, provides sufficient context for a simple mutation tool. It explains the functional impact per provider, and no output schema is required. Minor gaps around return values or error conditions are not essential given the tool's simplicity.

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 coverage is 100% for all four parameters, each with a meaningful description. The tool description adds no additional parameter-level semantics beyond what the schema already provides, so the baseline of 3 is appropriate.

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?

Clearly states 'Add a label to an email' with a specific verb and resource. The provider-specific behavior (ProtonMail folder copy vs Gmail/IMAP keyword flag) distinguishes it from related tools like create_label or remove_label.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context on how the tool behaves across different email providers, helping the agent understand when to use it. However, it does not explicitly mention alternatives or when not to use this tool, so it falls short of full guidance.

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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