What runtime does CodeWeave Mcp require?
Node.js 20 or later. Ollama must also be installed locally to run the embedding model.
@semihkayan
基本信息
Save tokens while coding — your AI agent gets structured code context, not file dumps.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"codeweave-mcp": {
"command": "npx",
"args": [
"@codeweave/mcp"
]
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。
CodeWeave Mcp is an MCP server that gives AI agents structured code intelligence by querying local indexes — AST, call graph, type graph, and hybrid semantic search — instead of dumping entire files into context. It is designed for developers using AI coding assistants like Claude Code and VS Code who want cheaper, more precise code understanding.
Run npx @codeweave/mcp inside your project directory. The setup wizard automatically installs dependencies, configures your MCP client, and indexes your project. After setup, open your project in Claude Code or VS Code and ask questions using the 8 available tools (e.g., semantic_search, get_function_source, get_impact_analysis).
Node.js 20 or later. Ollama must also be installed locally to run the embedding model.
Indexes live on disk in a `.code-context` directory. LanceDB stores vector embeddings; call and type graphs are stored as JSON.
The system degrades gracefully: search falls back to full-text only, and AST-based tools (dependencies, impact analysis, module summary) work without any embedding infrastructure.
It uses the MCP protocol over stdio transport. It works with any MCP-compatible client, including Claude Code, VS Code, and Cursor.
CodeWeave Mcp is under active development. The first run requires a one-time download of Ollama and the embedding model (takes a few minutes).
🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。

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