apple-mail-mcp-server

by wylieswanson

Overview Schema Source Related Servers Discussions Admin

Python

Local

list_rules

Read-onlyIdempotent

List all Apple Mail rules with their names and enabled states.

Instructions

List all Mail.app rules (read-only).

Returns each rule's display name and enabled state. Rule names are NOT guaranteed unique — Mail allows duplicates — and rules have no stable id via AppleScript. This tool is read-only; mutation (enable/disable, create, delete) is tracked as a separate enhancement.

Returns: Dictionary containing the rules list.

Example: >>> list_rules() {"success": True, "rules": [ {"name": "Junk filter", "enabled": True}, {"name": "News From Apple", "enabled": False}, ... ], "count": 2}

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": "list_rules"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.10.2Jul 9, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond the annotations, the description adds meaningful behavioral caveats: rule names are not guaranteed unique and rules have no stable id via AppleScript. This is exactly the kind of context an agent needs to avoid assuming identity or uniqueness.

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 well-structured and front-loaded with the core purpose. The return format and example are useful, and every sentence adds value without unnecessary fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read-only tool with annotations and an output schema, the description is complete. It covers purpose, return shape, example output, and the key caveats about duplicate names and missing stable IDs.

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?

The tool has zero parameters, so the schema already fully covers parameter semantics. The description adds no parameter details, but none are needed; the example output clarifies what the call returns.

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 opens with a specific verb and resource: 'List all Mail.app rules (read-only).' It clearly distinguishes this from mutation siblings by emphasizing read-only behavior and noting that mutation is tracked separately.

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?

The description explicitly frames this as the read-only listing tool and states that mutation (enable/disable, create, delete) is a separate enhancement. It does not name the exact sibling tools to use instead, but the context is clear enough for an agent to route correctly.

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