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multimodal-imessage-mcp

multimodal-imessage-mcp

by tszaks
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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list_chats_structured

Retrieve recent iMessage conversations as structured JSON, including chat IDs, handles, last message preview, and group status. Optionally filter by recency and limit results.

Instructions

List recent chats as structured JSON with chat IDs, handles, last sender, last message preview, group status, and message counts.

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_chats_structured"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoNumber of conversations to return (default: 20)
hours_agoNoOnly show chats active in the last N hours (optional)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.1

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions output fields and 'structured JSON'; it does not state whether the operation is read-only, how results are ordered, whether default filtering applies, or any rate limits. This is minimal behavioral transparency.

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 a single, focused sentence that front-loads the core action ('List recent chats') and then specifies the output format and fields. Every word contributes value, with no redundancy or filler.

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?

For a simple tool with two optional parameters and no output schema, the description provides the essential return fields, which is reasonably complete. However, the lack of differentiation from the sibling 'list_recent_chats' and the unexplained 'recent' behavior leave clear gaps for fully informed use.

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?

Both parameters are fully described in the input schema (100% coverage), so the description does not need to add parameter details. It also does not add any additional semantics beyond what the schema provides; the baseline 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?

The description clearly states 'List recent chats as structured JSON' and enumerates specific output fields (chat IDs, handles, last sender, last message preview, group status, message counts), which makes the tool's function and return format evident. However, it does not explicitly differentiate this tool from the similarly named sibling 'list_recent_chats', so it stops short of a 5.

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 provides no guidance on when to use this tool versus the sibling 'list_recent_chats' or other chat retrieval tools. There is no mention of alternatives, exclusions, or preferred use cases, leaving the agent without context for selection.

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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