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fastroute

ローカル MCP プラグイン: agent が新しいタスクを受け取ったとき、ローカルにインストールされているすべての skill(ユーザーレベル/プラグインレベル/プロジェクトレベル)から Top-N レコメンドを検索します。推奨のみで実行はしません。

インデックス方法は SkillRouter(arXiv 2603.22455)に由来します: all-field セグメント化マルチベクトル(name+description の1ベクトル + 本文 ~800 文字ごとのチャンクに各1ベクトル)、クエリは各チャンクに対してコサインを計算し、skill のスコアは max-pool を取ります。

ツール

工具

用途

recommend_skills

タスク開始前に最も関連する skill を検索;score、tier(auto/prompt/skip、参考値)、呼び出し名とパスを返します

reindex_skills

skill のインストール/削除後にインデックスを増分再構築します(mtime diff)。セッションの再起動は不要です

Related MCP server: skills-mcp-server

インストール(Claude Code)

claude mcp add fastroute -- node /absolute/path/to/fastroute/dist/index.js

データとモデル

  • データディレクトリ ~/.fastroute(FASTROUTE_DATA_DIR で上書き): fastroute.db、config.json、models/

  • embedding モデル: Xenova/paraphrase-multilingual-MiniLM-L12-v2(q8、約135MB)。ツール初回呼び出し時にオンラインでダウンロードされ、デフォルトは ModelScope ミラー(FASTROUTE_EMBEDDING_HOST で https://huggingface.co に戻せます)。既に ~/.knowyoubetter/models キャッシュがある場合はそれをそのまま再利用します

  • モデルはハード依存です: オフラインかつキャッシュがない場合、ツールはエラーとダウンロード手順を返します。語彙的なフォールバックはありません

  • config.json で上書き可能: chunkSize(800)、autoThreshold(0.9)、promptThreshold(0.6)、topK(5)、userSkillsDir、pluginCacheDir、projectSkillsEnabled

  • chunkSize を変更しても既存のインデックスは自動的に再チャンクされません: ~/.fastroute/fastroute.db を削除してから reindex_skills を呼び出す必要があります

開発

npm install
npm test            # 单测 + 集成(fake embedder,不联网)
npm run test:real   # 真实 embedding 冒烟(首次下载模型)
npm run eval        # distractor 评测:Hit@1/Hit@5/MRR
npm run build
npx @modelcontextprotocol/inspector node dist/index.js

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