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AppleScript を使用して iMessage を送信し、連絡先を管理する MCP サーバー。
このサーバーは、AppleScriptを使用して、モデルコンテキストプロトコル（MCP）を介してmacOSのメッセージアプリと連絡先アプリと連携します。AppleScriptコマンドをTypeScriptサーバーにラップすることで、以下のことが可能になります。
連絡先の表示と検索
連絡先または電話番号にiMessageを送信する
メッセージが送信されたときに確認を受け取る
contacts://allから連絡先にアクセスします
名前、電話番号、メールアドレスなどの連絡先の詳細を表示します
すべてのデータはローカルマシン上に保存されます
search_contacts - 名前、電話番号、またはメールアドレスで連絡先を検索します
検索クエリを受け取り、一致する連絡先を返します
名前、電話番号、メールアドレスを検索
send_message - iMessage を送信する
受信者（電話番号/メール）とメッセージの内容を取得します
ローカルのメッセージアプリから送信
確認またはエラーの詳細を返します
Related MCP server: imessage-rich-search
依存関係をインストールします:
npm installサーバーを構築します。
npm run buildサーバーを使用するように Claude Desktop を構成します。
MacOSの場合: ~/Library/Application Support/Claude/claude_desktop_config.json
{
"mcpServers": {
"imessage": {
"command": "node",
"args": ["/path/to/imessage-server/build/server.js"]
}
}
}Claudeデスクトップを再起動します
次のプロンプトが表示されたら権限を付与します。
連絡先へのアクセス
メッセージアクセス
インストールすると、Claude Desktop と自然に会話できるようになります。
「連絡先を見せて」
「Marissaという名前の連絡先を検索」
「555-0123に10分以内に着くとメッセージを送ってください」
「アリスにiMessageを送って、ランチの予定がまだ合うかどうか聞いてみよう」
すべての操作はローカルマシン上で実行されます
連絡先やメッセージのデータは外部サーバーに送信されません
サーバーは連絡先とメッセージへのアクセスにmacOSの権限を必要とします
メッセージはiMessageアカウントを通じて送信されます
開発とデバッグには、MCP インスペクターを使用します。
npx @modelcontextprotocol/inspector node build/server.jsmacOS（メッセージと連絡先の統合用）
Node.js 18以上
クロードデスクトップ
アクティブなiMessageアカウント
メッセージが送信されない場合は:
メッセージアプリがサインインされているか確認する
権限が付与されていることを確認する
Claude Desktop ログでエラーを探します。
tail -f ~/Library/Logs/Claude/mcp*.logSearch contacts by name, phone, or email
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query |
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 mentions the search functionality but doesn't describe behavioral traits like whether it's read-only, how results are returned (e.g., pagination, format), error handling, or any limitations (e.g., rate limits, authentication needs). This leaves significant gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It covers the basic purpose and parameters but fails to address behavioral aspects like result format, error conditions, or usage context. For a search tool with no structured behavioral data, more detail is needed to ensure the agent can invoke it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with one parameter 'query' documented as 'Search query'. The description adds value by specifying what the query searches ('by name, phone, or email'), which provides context beyond the schema. However, it doesn't detail syntax, examples, or constraints, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('search') and resource ('contacts'), and specifies the searchable fields (name, phone, or email). However, it doesn't explicitly differentiate from the sibling tool 'send_imessage', which appears unrelated but context isn't provided for comparison.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 alternatives or in what context. It simply states what the tool does without mentioning any prerequisites, exclusions, or scenarios where it's preferred over other methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Send an iMessage using Messages app
| Name | Required | Description | Default |
|---|---|---|---|
| recipient | Yes | Phone number or email of the recipient | |
| message | Yes | Message content to send |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Send an iMessage' implies a write/mutation operation, the description doesn't disclose important behavioral aspects: whether this requires specific permissions, if it's synchronous/asynchronous, error conditions, rate limits, or what happens if the recipient isn't in the user's contacts. It mentions 'using Messages app' which provides some implementation context, but lacks operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence with zero wasted words. It's front-loaded with the core functionality and uses straightforward language. Every word earns its place, making it easy for an agent to parse quickly while understanding the essential purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after sending (success/failure indicators, return values), doesn't mention authentication requirements, and provides no error handling context. While the purpose is clear, the operational context needed for reliable tool invocation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with both parameters ('recipient' and 'message') clearly documented in the schema. The tool description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Send') and resource ('an iMessage using Messages app'), making the purpose immediately understandable. It doesn't differentiate from the sibling tool 'search_contacts', but that's reasonable since they perform completely different functions. The description is specific enough to understand what the tool does without being tautological.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance about when to use this tool versus alternatives. There's no mention of prerequisites (like having the Messages app installed or configured), limitations (message length, supported recipients), or comparison with other messaging methods. The agent must infer usage context solely from the tool name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
search_contactssend_imessageScored across 2 tools
The two tools have completely distinct purposes: one searches contacts and the other sends messages. There is no overlap in functionality, making it impossible to confuse them.
Both tools follow a consistent verb_noun pattern (search_contacts, send_imessage) with clear, descriptive names that align with their actions. No deviations or mixed conventions are present.
With only two tools, the server feels thin for an iMessage domain, lacking essential operations like reading messages, managing conversations, or handling attachments. The count is too low for comprehensive coverage.
The toolset is severely incomplete for an iMessage server. It misses core functionalities such as retrieving messages, listing conversations, replying to threads, or deleting messages, leaving significant gaps that will hinder agent workflows.
MCP connector for iMessage & Contacts via a local Mac agent + Vercel relay
Search, read, and write your Apple Notes from ChatGPT/Claude via a local Mac agent + MCP relay.
Mac & Windows: let ChatGPT, Claude & Cursor use your email, calendar, iMessage, Teams, files.
Send and read iMessages from your own Mac and Apple ID — drafts, history and contacts.
