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iMessage MCP

iMessage MCP

by thenavidm
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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search_messages

Read-only

Search iMessage history by text, sender, chat, or date range, including encoded message bodies that plain SQL misses.

Instructions

Search message history by text, sender, chat, or date range. Reads bodies from both the text column and the encoded attributedBody blob, so it finds messages that plain SQL cannot.

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": "search_messages"
  }
}

Input Schema

NameRequiredDescriptionDefault
fromNoFilter by sender handle, partial match.
limitNoMax results (default 50, max 500).
queryNoSubstring to look for, case-insensitive.
sinceNoISO date lower bound.
untilNoISO date upper bound.
chatIdNoRestrict to one chat GUID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), so the description only needs to add beyond that. It does: it discloses that bodies are read from both the text column and the encoded attributedBody blob, explaining why results differ from a naive query. It omits pagination/ordering behavior, but the core behavioral insight is present.

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 sentences, front-loaded with the core purpose, and the second sentence adds genuinely new information rather than padding. Nothing is wasted and the capability claim is tightly scoped.

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 read-only search tool with full annotation coverage and a fully documented schema, the description is nearly complete. With no output schema, a brief note on result shape or ordering would help, but nothing required to invoke it correctly is missing.

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 the schema already documents all six parameters with formats and bounds. The description only restates the filter axes at a high level and adds no syntax, matching rules, or defaults beyond what the schema provides, 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?

States a specific verb and resource ('Search message history') and enumerates the filter dimensions (text, sender, chat, date range), which map cleanly onto the schema. It is clearly distinguishable from list_conversations or get_conversation by its search semantics, though it never names a sibling explicitly.

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

Usage Guidelines3/5

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

Usage is implied — search message history when you need to find messages — and the attributedBody note hints at capability plain SQL lacks, which is a mild routing cue. However there is no explicit when-to-use versus when-not, and no guidance distinguishing it from get_conversation or inbox for retrieving message content.

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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