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server for multi-model AI access via Vercel AI Gateway","maintainers":[{"name":"ayatec","email":"ayatec.jp@gmail.com"}],"readme":"# AI Gateway MCP Server\n\n[![npm version](https://img.shields.io/npm/v/@ayatec/ai-gateway-mcp-server)](https://www.npmjs.com/package/@ayatec/ai-gateway-mcp-server)\n[![CI](https://github.com/ayatec/ai-gateway-mcp-server/actions/workflows/ci.yml/badge.svg)](https://github.com/ayatec/ai-gateway-mcp-server/actions/workflows/ci.yml)\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)\n\nVercel AI Gateway を通じて複数の AI プロバイダー・モデルに統一的にアクセスできる MCP サーバー。\nWeb 検索、マルチモデル調査・比較など、LLM を活用した 4 つのツールを提供します。\n\n## 提供ツール\n\n### `ask` -- AI に質問\n\n任意のモデルに質問を送り、回答を得ます。\n\n| パラメータ   | 型     | 必須 | デフォルト       | 説明                                     |\n| ------------ | ------ | ---- | ---------------- | ---------------------------------------- |\n| `question`   | string | Yes  | -                | 質問内容                                 |\n| `model`      | string | No   | `openai/gpt-5.4` | モデル ID                                |\n| `context`    | string | No   | -                | 追加コンテキスト                         |\n| `max_tokens` | number | No   | -                | 最大出力トークン数（省略時はモデル任せ） |\n\n### `search` -- Web 検索\n\n検索対応モデルを使って最新情報を取得します。\n\n| パラメータ   | 型     | 必須 | デフォルト              | 説明                                     |\n| ------------ | ------ | ---- | ----------------------- | ---------------------------------------- |\n| `query`      | string | Yes  | -                       | 検索クエリ                               |\n| `model`      | string | No   | `google/gemini-3-flash` | 検索対応モデル ID                        |\n| `max_tokens` | number | No   | -                       | 最大出力トークン数（省略時はモデル任せ） |\n\n### `research` -- マルチモデル調査・比較\n\n複数モデルに並列クエリし、結果を統合または比較表示します。\n\n| パラメータ             | 型       | 必須 | デフォルト             | 説明                                                |\n| ---------------------- | -------- | ---- | ---------------------- | --------------------------------------------------- |\n| `query`                | string   | Yes  | -                      | 調査クエリ                                          |\n| `mode`                 | string   | No   | `search`               | `search`（Web 検索）または `ask`（Q&A）             |\n| `models`               | string[] | No   | mode に応じた 4 モデル | 2~4 モデル ID の配列                                |\n| `synthesize`           | boolean  | No   | `true`                 | `true`: 統合回答、`false`: 各モデルの回答を並列表示 |\n| `synthesis_model`      | string   | No   | `openai/gpt-5.4`       | 統合に使うモデル（`synthesize:true` 時のみ）        |\n| `max_tokens`           | number   | No   | -                      | 各モデルの最大出力トークン数（省略時はモデル任せ）  |\n| `synthesis_max_tokens` | number   | No   | -                      | 統合の最大出力トークン数（省略時はモデル任せ）      |\n\n**処理フロー:**\n\n1. **Query Stage**: 指定（またはデフォルト）モデルに並列リクエスト\n   - `search` デフォルト: `perplexity/sonar`, `gemini-3-flash`, `gpt-5-mini`\n   - `ask` デフォルト: `gpt-5.4`, `claude-opus-4.6`, `gemini-3.1-pro-preview`, `sonar-reasoning-pro`\n2. **Synthesis Stage** (`synthesize:true`): `openai/gpt-5.4` が全結果を精査・統合し、矛盾点を指摘、ソースを明記\n3. **Comparison** (`synthesize:false`): 各モデルの回答をコスト・レイテンシ付きで並列表示\n\n### `list_models` -- モデル一覧\n\n利用可能なモデルの情報（価格・能力・検索コスト）を表示します。\n\n| パラメータ   | 型     | 必須 | 説明                                                                    |\n| ------------ | ------ | ---- | ----------------------------------------------------------------------- |\n| `provider`   | string | No   | プロバイダーでフィルタ（`openai`, `anthropic`, `google`, `perplexity`） |\n| `capability` | string | No   | 能力でフィルタ（`search`, `reasoning`, `fast`, `cheap`, `code`）        |\n\n## サポートモデル\n\n### OpenAI\n\n| モデル ID              | 入力  | 出力   | 検索 | 特徴                                                                                                     |\n| ---------------------- | ----- | ------ | ---- | -------------------------------------------------------------------------------------------------------- |\n| `openai/gpt-5.4`       | $2.50 | $15.00 | Yes  | OpenAI 最上位。推論・コード・エージェント性能が 5.2 から大幅向上、1.05M コンテキスト、キャッシュ割引 90% |\n| `openai/gpt-5.4-mini`  | $0.75 | $4.50  | Yes  | GPT-5 Mini の上位版。推論・コーディング・ビジョンが大幅向上、400K コンテキスト                           |\n| `openai/gpt-5.4-nano`  | $0.20 | $1.25  | Yes  | GPT-5 Nano の上位版。Web 検索対応で GPT-5 Mini より安い、コーディングも向上                              |\n| `openai/gpt-5.3-codex` | $1.75 | $14.00 | Yes  | エージェント型コード特化版。5.2-codex から 25% 高速化、mid-task steering 対応、Terminal-Bench 最高水準   |\n| `openai/gpt-5-mini`    | $0.25 | $2.00  | Yes  | 低コスト汎用モデル。コーディングに特に強く、推論・検索も対応する万能型                                   |\n| `openai/gpt-5-nano`    | $0.05 | $0.40  | No   | 最安モデル。シンプルな生成・分類向けで推論・検索は非対応                                                 |\n| `openai/gpt-oss-120b`  | $0.10 | $0.50  | No   | OpenAI 公開の OSS モデル。低コストで推論・コード対応、検索非対応                                         |\n\n### Anthropic\n\n| モデル ID                     | 入力  | 出力   | 検索 | 特徴                                                                                        |\n| ----------------------------- | ----- | ------ | ---- | ------------------------------------------------------------------------------------------- |\n| `anthropic/claude-opus-4.6`   | $5.00 | $25.00 | Yes  | Anthropic 最上位。SWE-bench 最強クラスでコーディング精度が突出、1M コンテキスト             |\n| `anthropic/claude-sonnet-4.6` | $3.00 | $15.00 | Yes  | Opus の約 1/2 コストで高品質。エージェント用途やコスパ重視の汎用タスク向け、1M コンテキスト |\n| `anthropic/claude-haiku-4.5`  | $1.00 | $5.00  | Yes  | Anthropic 軽量モデル。低レイテンシで検索・コード対応、高速処理向け                          |\n\n### Google\n\n| モデル ID                              | 入力  | 出力   | 検索 | 特徴                                                                                                 |\n| -------------------------------------- | ----- | ------ | ---- | ---------------------------------------------------------------------------------------------------- |\n| `google/gemini-3-flash`                | $0.50 | $3.00  | Yes  | Google Search grounding 対応で検索精度が高い。コーディングも強く、search デフォルト、1M コンテキスト |\n| `google/gemini-3.1-flash-lite-preview` | $0.25 | $1.50  | No   | 最速クラスのスループット。低コストで推論・知識に強いが検索非対応、preview 版                         |\n| `google/gemini-3.1-pro-preview`        | $2.00 | $12.00 | Yes  | Google 最上位。科学推論・マルチモーダルに強く、Gemini 3 Pro の後継、1M コンテキスト                  |\n\n### Perplexity\n\n| モデル ID                        | 入力  | 出力   | 検索 | 特徴                                                                        |\n| -------------------------------- | ----- | ------ | ---- | --------------------------------------------------------------------------- |\n| `perplexity/sonar`               | $1.00 | $1.00  | Yes  | 検索特化で最安。単発の事実確認やニュース検索に最適、低レイテンシ            |\n| `perplexity/sonar-pro`           | $3.00 | $15.00 | Yes  | 高精度検索。最大 5 回の内部検索で深掘りでき、技術ドキュメントの詳細調査向け |\n| `perplexity/sonar-reasoning-pro` | $2.00 | $8.00  | Yes  | 推論+検索のハイブリッド。根拠付きの分析が必要な複雑な調査向け               |\n\n> 価格は 1M トークンあたり（USD）\n\n## セットアップ\n\n### 1. 環境変数\n\n[Vercel AI Gateway](https://vercel.com/ai-gateway) の API キーを取得し、設定します。\n\n| 変数名                | 必須 | 説明                                    |\n| --------------------- | ---- | --------------------------------------- |\n| `AI_GATEWAY_API_KEY`  | Yes  | Vercel AI Gateway API キー              |\n| `ZERO_DATA_RETENTION` | No   | `true` で Gateway レベルの ZDR を有効化 |\n\n## プライバシー・データ保持\n\n各プロバイダーへのリクエストに、プライバシー保護のための設定を自動付与します。\n\n| プロバイダー   | 対応                                                  |\n| -------------- | ----------------------------------------------------- |\n| **OpenAI**     | `store: false` を全リクエストに付与（データ保存無効） |\n| **Anthropic**  | API 経由はデフォルトで学習不使用                      |\n| **Google**     | 有料 API はデフォルトで学習不使用                     |\n| **Perplexity** | API はデフォルトで Zero Data Retention                |\n\n`ZERO_DATA_RETENTION=true` を設定すると、Vercel AI Gateway レベルの ZDR が有効になり、ZDR 契約済みプロバイダーにのみリクエストがルーティングされます。Perplexity は自前で ZDR を保証しているため Gateway ZDR の適用対象外です。\n\n### 2. MCP 設定\n\n#### npx で使う場合（推奨）\n\n##### Claude Code\n\n```bash\nclaude mcp add ai-gateway npx @ayatec/ai-gateway-mcp-server -e AI_GATEWAY_API_KEY=your-key\n```\n\n##### Claude Desktop / その他の MCP クライアント\n\n```json\n{\n  \"mcpServers\": {\n    \"ai-gateway\": {\n      \"command\": \"npx\",\n      \"args\": [\"@ayatec/ai-gateway-mcp-server\"],\n      \"env\": {\n        \"AI_GATEWAY_API_KEY\": \"your-key\"\n      }\n    }\n  }\n}\n```\n\n#### ローカルビルドで使う場合\n\n開発中のバージョンを使いたい場合や、ソースを修正して使いたい場合はこちら。\n\n```bash\ngit clone https://github.com/ayatec/ai-gateway-mcp-server.git\ncd ai-gateway-mcp-server\ncp .env.example .env\n# .env を編集して API キーを設定\npnpm install\npnpm build\n```\n\n##### Claude Code\n\n```bash\nclaude mcp add ai-gateway node /path/to/ai-gateway-mcp-server/dist/index.js -e AI_GATEWAY_API_KEY=your-key\n```\n\n##### Claude Desktop / その他の MCP クライアント\n\n```json\n{\n  \"mcpServers\": {\n    \"ai-gateway\": {\n      \"command\": \"node\",\n      \"args\": [\"/path/to/ai-gateway-mcp-server/dist/index.js\"],\n      \"env\": {\n        \"AI_GATEWAY_API_KEY\": \"your-key\"\n      }\n    }\n  }\n}\n```\n\n## 開発\n\n### コマンド\n\n```bash\npnpm install        # 依存パッケージインストール\npnpm build          # ビルド\npnpm dev            # ウォッチモードでビルド\npnpm start          # サーバー起動（ビルド後）\npnpm dev:tool       # ツールの手動テスト\npnpm test           # テスト実行\npnpm test:watch     # テスト（ウォッチモード）\npnpm type-check     # 型チェック\npnpm lint           # ESLint実行\npnpm lint:fix       # ESLint自動修正\npnpm format         # Prettier実行\npnpm format:check   # フォーマットチェック\n```\n\n### ローカルテスト\n\n`pnpm dev:tool` で各ツールを個別にテストできます。\n\n```bash\n# ask（デフォルト: gpt-5.4）\npnpm dev:tool ask --question \"TypeScriptの利点は？\"\n\n# ask（モデル指定）\npnpm dev:tool ask --question \"Rustとは？\" --model \"anthropic/claude-sonnet-4.6\"\n\n# search（デフォルト: google/gemini-3-flash）\npnpm dev:tool search --query \"Vercel AI SDK 最新情報\"\n\n# research（4モデル並列検索→統合、デフォルト）\npnpm dev:tool research --query \"WebAssemblyの現状と将来\"\n\n# research（askモード、比較表示）\npnpm dev:tool research --query \"関数型プログラミングの利点\" --mode ask --synthesize false\n\n# research（モデル指定）\npnpm dev:tool research --query \"latest TypeScript features\" --models '[\"openai/gpt-5.4\",\"perplexity/sonar\"]'\n\n# list_models\npnpm dev:tool list_models\npnpm dev:tool list_models --provider openai\npnpm dev:tool list_models --capability search\n```\n\n### リリース\n\n[Changesets](https://github.com/changesets/changesets) でバージョン管理しています。\n\n1. changeset ファイルを作成して main に push\n2. GitHub Actions が自動で CHANGELOG 更新・バージョンバンプ・npm publish\n\n## 技術スタック\n\n- **TypeScript** (ESM, NodeNext, strict)\n- **[Vercel AI SDK](https://ai-sdk.dev/)** -- `gateway` プロバイダーで全モデルに統一アクセス\n- **[MCP SDK](https://modelcontextprotocol.io/)** -- Model Context Protocol サーバー実装\n- **[Zod](https://zod.dev/)** -- スキーマバリデーション\n- **[Vitest](https://vitest.dev/)** -- テスト\n- **[Changesets](https://github.com/changesets/changesets)** -- バージョン管理・CHANGELOG 自動生成\n\n## ライセンス\n\nMIT\n","readmeFilename":"README.md"}