ai-market-intelligence
AI Market Intelligence MCP
TypeScriptで書かれたローカルMCPサーバーで、シナリオ別にAIモデルを比較します:プログラミング、サポート、ドキュメント、マルチモーダル、エージェント、プライバシー。
この最初のバージョンでできること
モデルのローカルカタログを一覧表示します。
能力、コンテキスト、相対コスト、セルフホスティングの明確な基準でモデルを推奨します。
選択したモデルを比較します。
各シナリオで使用される重みを説明します。
src/catalog.ts のプロフィールは定性的かつ初期段階のものです。公式の価格やベンチマークではありません。購入を決定する前に、お使いのドメインでの評価で推奨事項を検証し、情報源を更新してください。
Related MCP server: LLM Benchmark MCP Server
実行
npm install
npm run build
npm run devMCP Inspectorでテストするには:
npm run inspectVS Codeに接続する
サーバーを使用するプロジェクトで .vscode/mcp.json を作成または更新します:
{
"servers": {
"ai-market-intelligence": {
"command": "node",
"args": ["C:/Users/gabiv/Projects/ai-market-intelligence-mcp/dist/index.js"]
}
}
}npm run build を実行したら、VS Code/Copilot の MCP セクションを開き、サーバーを起動します。トランスポートは stdio であるため、プログラムは stdout にログを書き込むことはありません。
推奨される今後の進化
データとバージョン履歴のためのJSONファイルまたはSQLiteデータベース。
各データの日付とURLを含む公式ソース(価格、コンテキストウィンドウ、制限)のコレクター。
一般的な比較に依存するのではなく、実際のプロンプトとビジネスメトリクスを使用した評価。
チームとサーバーを共有したい場合は、認証付きのHTTPインターフェース。
Available Tools
4 toolscompare_modelsComparar modelosB
Compara até quatro modelos para um cenário específico e mostra a classificação.
Inputs: ids (required), scenario (required).
explain_scenariosExplicar cenáriosA
Explica os cenários avaliados e os pesos usados pelo mecanismo de recomendação.
Inputs: no named parameters.
list_modelsListar modelosB
Lista os perfis de modelos presentes no catálogo local.
Inputs: provider.
recommend_modelRecomendar modeloC
Ordena modelos do catálogo para um cenário, orçamento e requisito de hospedagem própria.
Inputs: scenario (required), limit, budget, requiresSelfHosted.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
TDQS
Scored across 4 tools
The tools are mostly distinct: list_models lists catalog items, recommend_model ranks them, compare_models compares a subset, and explain_scenarios describes the reasoning. However, recommend_model and compare_models could be confused since both rank/compare for a scenario, though compare_models explicitly limits to four.
All tools follow a verb_noun pattern (list_models, recommend_model, compare_models, explain_scenarios). However, the verbs vary in style - 'list', 'recommend', 'compare' are action verbs, while 'explain' is also action but the noun 'scenarios' differs from 'models' - but the pattern is consistent.
With 4 tools, the set is slightly small for a domain that includes model cataloging, recommendation, comparison, and explanation, but it is reasonable for a focused utility. Each tool serves a distinct function and the count is acceptable, though a bit sparse.
The domain appears to be model recommendation and comparison, and the tools cover listing, recommending, comparing, and explaining the logic. However, there is no tool to get details of a single model or to manage the catalog (add/update/delete), which are notable gaps for a complete surface.
Maintenance
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