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protonmail-mcp-server

protonmail-mcp-server

by de-Blanck
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

List Proton Mail Folders

proton_list_folders
Read-onlyIdempotent

List all mailbox folders in your Proton Mail account, showing message and unread counts. Use this to discover folders before searching or listing emails.

Instructions

List all mailbox folders in the Proton Mail account with message counts and unread counts.

Use this tool to discover available folders before listing or searching emails.

Args:

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

Returns: A list of folders with path, message count, and unread count.

Examples:

  • "What folders do I have?" -> proton_list_folders()

  • "How many unread emails do I have?" -> proton_list_folders()

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "proton_list_folders"
  }
}

Input Schema

NameRequiredDescriptionDefault
response_formatNoOutput format: 'markdown' or 'json'markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds behavioral details about returned data (message/unread counts) and the response format parameter, enhancing transparency.

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 and well-structured with a clear purpose sentence, Args, Returns, and Examples. It is front-loaded with the key action. Minor room for trimming.

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 simple read-only list tool, the description covers purpose, usage guidance, parameter, and return format. No output schema exists, but the description sufficiently explains what to expect.

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%. The description mentions the parameter in Args but adds minimal meaning beyond the schema's description. Baseline 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?

The description uses specific verbs ('List') and resources ('mailbox folders'), and includes what it returns (message counts, unread counts). It clearly distinguishes from sibling tools which deal with emails, not folders.

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?

Explicitly states to use this tool to discover folders before listing/searching emails, providing clear context for usage. Does not explicitly mention when not to use it, but the sibling tools imply separation.

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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