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multimodal-imessage-mcp

multimodal-imessage-mcp

by tszaks
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

get_conversation

Retrieve the full iMessage thread with a specific contact or number, displaying text and attachment indicators. Filter results by time to find recent messages quickly.

Instructions

Get full conversation thread with a specific contact or phone number, optionally filtered by time. Shows text content and indicates attachments.

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": "get_conversation"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of messages to retrieve (default: 100)
contactNoContact name or phone number
hours_agoNoOptional: Only show messages from the last N hours (e.g., 12 for last 12 hours, 24 for last day)
phone_numberNoPhone number alias for contact. Kept for compatibility with clients that call this tool using phone_number.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.1

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It mentions output includes text content and attachment indicators, and implies read-only behavior via 'get', but does not detail permissions, rate limits, or any side effects. This partial disclosure merits a mid-range score.

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 concise (two sentences) and front-loaded with the main purpose. It avoids redundancy and captures the core functionality efficiently.

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

Completeness3/5

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

Given the sibling tools include similar functions like get_conversation_by_chat_id, the description does not clarify the unique value or conditions for using this tool over others. It also leaves ambiguity about whether 'full thread' implies all messages or a summary, and does not mention output format. This incomplete context warrants a mid-range score.

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?

All four parameters have descriptive comments in the schema (100% coverage). The descriptions add meaning, such as clarifying 'phone_number' as an alias for 'contact' and explaining the purpose of 'hours_ago'. This exceeds the baseline for full coverage.

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 clearly states the tool retrieves a full conversation thread with a specific contact or phone number, optionally filtered by time. It distinguishes itself from siblings like 'read_recent_messages' and 'search_messages' by specifying the retrieval scope and criteria.

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

Usage Guidelines2/5

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

The description does not provide explicit guidance on when to use this tool versus alternatives (e.g., get_conversation_by_chat_id, search_messages). It only states what the tool does, leaving the user to infer the appropriate context.

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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