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iMessage MCP

iMessage MCP

by duanefields
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

search_messages

Find messages across entire iMessage history by case-insensitive text search, with options to limit results, skip matches, or narrow the search to a single conversation.

Instructions

Search message text across conversations, case-insensitively.

The entire history is searched, not a recent window, so a total of 0 means the text is genuinely not there. The total is a true count of matches; limit bounds only how many are returned.

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": {
      "query": "<query>"
    },
    "name": "search_messages"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of matches to return (default: 20)
queryYesText to look for
offsetNoNumber of matches to skip from the start (default: 0)
chat_guidNoRestrict the search to one conversation (default: all)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that search is case-insensitive, covers full history, and that 'total' is an exact count while 'limit' only affects returned results. This is valuable context that helps the agent interpret results correctly. No contradiction with annotations since none exist.

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 two concise sentences with no wasted words. It front-loads the core purpose and immediately adds critical behavioral details about search scope and result semantics.

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 tool is a read-only search operation, and the description covers the key behavioral aspects: case sensitivity, scope, and result counting. With no output schema, it could mention the structure of returns, but the description is adequate for a search tool with these parameters. Minor gap is lack of detail on return format or sorting.

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%, so all four parameters are documented in the schema. The description adds some value by clarifying the behavior of 'limit' and 'total', but it doesn't explain the meaning of 'offset' or 'chat_guid' beyond what the schema already states. Baseline 3 is appropriate.

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 clearly states that the tool searches message text across conversations with case-insensitivity. It distinguishes from siblings like list_chats and get_messages by emphasizing full-text search across all conversations, though it doesn't directly name a sibling as an alternative.

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?

It provides clear usage context: searching is case-insensitive and covers the entire history, meaning a zero result is definitive. However, it doesn't explicitly state when to use this tool versus alternatives like get_messages or list_chats, which are for reading specific messages or listing conversations.

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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