开源项目 GitHub Topic ai-coding 2026-07-06T12:02 正文 ok 2445 words

zilliztech/claude-context：将整个代码库变成 Claude 编程 Agent 的上下文

英文标题：📦 zilliztech/claude-context

Claude Context 是一个 MCP 插件，通过语义代码搜索让 Claude Code 等 AI 编码代理使用整个代码库作为上下文。它利用向量数据库高效存储并检索相关代码，避免将整个目录加载到 Claude 中，从而降低大型代码库的使用成本。支持 Claude Code、OpenAI Codex CLI、Gemini CLI、Cursor、VS Code 等多种 MCP 客户端。开发者只需配置 Zilliz Cloud 向量数据库和 OpenAI 嵌入模型即可将语义搜索能力接入日常编码工作流。

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中文

🆕 正在寻找 Claude Code 的持久记忆？ 查看 memsearch Claude Code 插件 —— 一个 Markdown 优先的记忆系统，为你的 AI Agent 提供跨会话的长期记忆。

将整个代码库作为 Claude 的上下文

Claude Context 是一个 MCP 插件，为 Claude Code 和其他 AI 编程代理添加语义代码搜索，让它们从你的整个代码库中获得深层上下文。

🧠 将整个代码库作为上下文：Claude Context 使用语义搜索从数百万行代码中找到所有相关代码。无需多轮探索，结果直接进入 Claude 的上下文。

💰 对大型代码库更经济高效：与其每次请求都将整个目录加载到 Claude 中（成本可能非常高），Claude Context 将你的代码库高效存储在向量数据库中，仅将相关代码放入上下文，让成本更可控。

Model Context Protocol (MCP) 允许你将 Claude Context 集成到你喜欢的 AI 编码助手中，例如 Claude Code。

👈 在 Zilliz Cloud 上获取免费向量数据库

Claude Context 需要一个向量数据库。你可以注册 Zilliz Cloud 以获取 API 密钥。

复制你的 Personal Key 以替换配置示例中的 your-zilliz-cloud-api-key。

获取用于嵌入模型的 OpenAI API Key

你需要一个 OpenAI API 密钥用于嵌入模型。可以在 OpenAI 注册获取。

你的 API 密钥类似这样：始终以 sk- 开头。复制密钥，并在下面的配置示例中将其用作 your-openai-api-key。

为 Claude Code 配置 MCP

系统要求：

使用命令行界面添加 Claude Context MCP 服务器：

claude mcp add claude-context
-e OPENAI_API_KEY=sk-your-openai-api-key
-e MILVUS_ADDRESS=your-zilliz-cloud-public-endpoint
-e MILVUS_TOKEN=your-zilliz-cloud-api-key
-- npx @zilliz/claude-context-mcp@latest

更多关于 MCP 服务器管理的信息，请参阅 Claude Code MCP 文档。

其他 MCP 客户端配置

OpenAI Codex CLI

Codex CLI 使用 TOML 配置文件：

创建或编辑 ~/.codex/config.toml 文件。
添加以下配置：

注意：顶级键是 `mcp_servers` 而不是 `mcpServers`。

[mcp_servers.claude-context] command = "npx" args = ["@zilliz/claude-context-mcp@latest"] env = { "OPENAI_API_KEY" = "your-openai-api-key", "MILVUS_TOKEN" = "your-zilliz-cloud-api-key" }

可选：覆盖默认 10s 启动超时

startup_timeout_ms = 20000

保存文件并重启 Codex CLI 以应用更改。

Gemini CLI

Gemini CLI 需要通过 JSON 文件手动配置：

创建或编辑 ~/.gemini/settings.json 文件。
添加以下配置：

{ "mcpServers": { "claude-context": { "command": "npx", "args": ["@zilliz/claude-context-mcp@latest"], "env": { "OPENAI_API_KEY": "your-openai-api-key", "MILVUS_TOKEN": "your-zilliz-cloud-api-key" } } } }

保存文件并重启 Gemini CLI 以应用更改。

Qwen Code

创建或编辑 ~/.qwen/settings.json 文件并添加以下配置：

{ "mcpServers": { "claude-context": { "command": "npx", "args": ["@zilliz/claude-context-mcp@latest"], "env": { "OPENAI_API_KEY": "your-openai-api-key", "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint", "MILVUS_TOKEN": "your-zilliz-cloud-api-key" } } } }

Cursor

前往：Settings -> Cursor Settings -> MCP -> Add new global MCP server

推荐将以下配置粘贴到 Cursor 的 ~/.cursor/mcp.json 文件中。你也可以通过在项目文件夹中创建 .cursor/mcp.json 来安装到特定项目中。更多信息请参阅 Cursor MCP 文档。

{ "mcpServers": { "claude-context": { "command": "npx", "args": ["-y", "@zilliz/claude-context-mcp@latest"], "env": { "OPENAI_API_KEY": "your-openai-api-key", "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint", "MILVUS_TOKEN": "your-zilliz-cloud-api-key" } } } }

Void

前往：Settings -> MCP -> Add MCP Server

将以下配置添加到 Void MCP 设置中：

{ "mcpServers": { "code-context": { "command": "npx", "args": ["-y", "@zilliz/claude-context-mcp@latest"], "env": { "OPENAI_API_KEY": "your-openai-api-key", "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint", "MILVUS_TOKEN": "your-zilliz-cloud-api-key" } } } }

Claude Desktop

添加到 Claude Desktop 配置中：

Windsurf

Windsurf 支持通过 JSON 文件配置 MCP。将以下配置添加到 Windsurf MCP 设置中：

VS Code

Claude Context MCP 服务器可通过 MCP 兼容扩展在 VS Code 中使用。将以下配置添加到 VS Code MCP 设置中：

Cherry Studio

Cherry Studio 允许通过设置界面可视化配置 MCP 服务器。虽然不直接支持手动 JSON 配置，但你可以通过 GUI 添加新服务器：

导航到 Settings → MCP Servers → Add Server。
填写服务器信息：
- Name：claude-context
- Type：STDIO
- Command：npx
- Arguments：["-y", "@zilliz/claude-context-mcp@latest"]
- Environment Variables：
  - OPENAI_API_KEY：your-openai-api-key
  - MILVUS_ADDRESS：your-zilliz-cloud-public-endpoint
  - MILVUS_TOKEN：your-zilliz-cloud-api-key
保存配置以激活服务器。

Cline

Cline 使用 JSON 配置文件管理 MCP 服务器。要集成提供的 MCP 服务器配置：

打开 Cline 并点击顶部导航栏中的 MCP Servers 图标。
选择 Installed 选项卡，然后点击 Advanced MCP Settings。
在 cline_mcp_settings.json 文件中，添加以下配置：

保存文件。

Augment

要在 Augment Code 中配置 Claude Context MCP，可以使用图形界面或手动配置。

A. 使用 Augment Code UI

点击汉堡菜单。
选择 Settings。
导航到 Tools 部分。
点击 + Add MCP 按钮。
输入以下命令：
```
npx @zilliz/claude-context-mcp@latest
```
将 MCP 命名为：Claude Context。
点击 Add 按钮。

B. 手动配置（通过 settings.json）

按 Cmd/Ctrl Shift P 或前往 Augment 面板中的汉堡菜单。
选择 Edit Settings。
在 Advanced 下，点击 Edit in settings.json。
将服务器配置添加到 augment.advanced 对象中的 mcpServers 数组：

"augment.advanced": { "mcpServers": [ { "name": "claude-context", "command": "npx", "args": ["-y", "@zilliz/claude-context-mcp@latest"], "env": { "OPENAI_API_KEY": "your-openai-api-key", "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",

注意： 配置中的 your-openai-api-key、your-zilliz-cloud-public-endpoint 和 your-zilliz-cloud-api-key 需要替换为你自己的实际值。

English / 原文

🆕 Looking for persistent memory for Claude Code? Check out memsearch Claude Code plugin — a markdown-first memory system that gives your AI agent long-term memory across sessions.

Your entire codebase as Claude's context

Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.

🧠 Your Entire Codebase as Context : Claude Context uses semantic search to find all relevant code from millions of lines. No multi-round discovery needed. It brings results straight into the Claude's context.

💰 Cost-Effective for Large Codebases : Instead of loading entire directories into Claude for every request, which can be very expensive, Claude Context efficiently stores your codebase in a vector database and only uses related code in context to keep your costs manageable.

Model Context Protocol (MCP) allows you to integrate Claude Context with your favorite AI coding assistants, e.g. Claude Code.

Get a free vector database on Zilliz Cloud 👈

Claude Context needs a vector database. You can sign up on Zilliz Cloud to get an API key.

Copy your Personal Key to replace your-zilliz-cloud-api-key in the configuration examples.

Get OpenAI API Key for embedding model

You need an OpenAI API key for the embedding model. You can get one by signing up at OpenAI.

Your API key will look like this: it always starts with sk-.
Copy your key and use it in the configuration examples below as your-openai-api-key.

Configure MCP for Claude Code

System Requirements:

Use the command line interface to add the Claude Context MCP server:

claude mcp add claude-context \
  -e OPENAI_API_KEY=sk-your-openai-api-key \
  -e MILVUS_ADDRESS=your-zilliz-cloud-public-endpoint \
  -e MILVUS_TOKEN=your-zilliz-cloud-api-key \
  -- npx @zilliz/claude-context-mcp@latest

See the Claude Code MCP documentation for more details about MCP server management.

Other MCP Client Configurations

OpenAI Codex CLI

Codex CLI uses TOML configuration files:

Create or edit the ~/.codex/config.toml file.
Add the following configuration:

# IMPORTANT: the top-level key is `mcp_servers` rather than `mcpServers`.
[mcp_servers.claude-context]
command = "npx"
args = ["@zilliz/claude-context-mcp@latest"]
env = { "OPENAI_API_KEY" = "your-openai-api-key", "MILVUS_TOKEN" = "your-zilliz-cloud-api-key" }
# Optional: override the default 10s startup timeout
startup_timeout_ms = 20000

Save the file and restart Codex CLI to apply the changes.

Gemini CLI

Gemini CLI requires manual configuration through a JSON file:

Create or edit the ~/.gemini/settings.json file.
Add the following configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Save the file and restart Gemini CLI to apply the changes.

Qwen Code

Create or edit the ~/.qwen/settings.json file and add the following configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Cursor

Go to: Settings -> Cursor Settings -> MCP -> Add new global MCP server

Pasting the following configuration into your Cursor ~/.cursor/mcp.json file is the recommended approach. You may also install in a specific project by creating .cursor/mcp.json in your project folder. See Cursor MCP docs for more info.

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Void

Go to: Settings -> MCP -> Add MCP Server

Add the following configuration to your Void MCP settings:

{
  "mcpServers": {
    "code-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Claude Desktop

Add to your Claude Desktop configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Windsurf

Windsurf supports MCP configuration through a JSON file. Add the following configuration to your Windsurf MCP settings:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

VS Code

The Claude Context MCP server can be used with VS Code through MCP-compatible extensions. Add the following configuration to your VS Code MCP settings:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Cherry Studio

Cherry Studio allows for visual MCP server configuration through its settings interface. While it doesn't directly support manual JSON configuration, you can add a new server via the GUI:

Navigate to Settings → MCP Servers → Add Server.
Fill in the server details:
- Name : claude-context
- Type : STDIO
- Command : npx
- Arguments : ["-y", "@zilliz/claude-context-mcp@latest"]
- Environment Variables :
  - OPENAI_API_KEY: your-openai-api-key
  - MILVUS_ADDRESS: your-zilliz-cloud-public-endpoint
  - MILVUS_TOKEN: your-zilliz-cloud-api-key
Save the configuration to activate the server.

Cline

Cline uses a JSON configuration file to manage MCP servers. To integrate the provided MCP server configuration:

Open Cline and click on the MCP Servers icon in the top navigation bar.
Select the Installed tab, then click Advanced MCP Settings.
In the cline_mcp_settings.json file, add the following configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Save the file.

Augment

To configure Claude Context MCP in Augment Code, you can use either the graphical interface or manual configuration.

A. Using the Augment Code UI

Click the hamburger menu.
Select Settings.
Navigate to the Tools section.
Click the + Add MCP button.
Enter the following command:
```
npx @zilliz/claude-context-mcp@latest
```
Name the MCP: Claude Context.
Click the Add button.

Press Cmd/Ctrl Shift P or go to the hamburger menu in the Augment panel
Select Edit Settings
Under Advanced, click Edit in settings.json
Add the server configuration to the mcpServers array in the augment.advanced object

"augment.advanced": { 
  "mcpServers": [ 
    { 
      "name": "claude-context", 
      "command": "npx", 
      "args": ["-y", "@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  ]
}

Roo Code

Roo Code utilizes a JSON configuration file for MCP servers:

Open Roo Code and navigate to Settings → MCP Servers → Edit Global Config.
In the mcp_settings.json file, add the following configuration:

{
  "mcpServers": {
    "claude-context": {
      "command": "npx",
      "args": ["@zilliz/claude-context-mcp@latest"],
      "env": {
        "OPENAI_API_KEY": "your-openai-api-key",
        "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
        "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
      }
    }
  }
}

Save the file to activate the server.

Zencoder

Zencoder offers support for MCP tools and servers in both its JetBrains and VS Code plugin versions.

Go to the Zencoder menu (...)
From the dropdown menu, select Tools
Click on the Add Custom MCP
Add the name (i.e. Claude Context and server configuration from below, and make sure to hit the Install button

{
    "command": "npx",
    "args": ["@zilliz/claude-context-mcp@latest"],
    "env": {
      "OPENAI_API_KEY": "your-openai-api-key",
      "MILVUS_ADDRESS": "your-zilliz-cloud-public-endpoint",
      "MILVUS_TOKEN": "your-zilliz-cloud-api-key"
    }
}

Save the server by hitting the Install button.

LangChain/LangGraph

For LangChain/LangGraph integration examples, see this example.

Other MCP Clients

The server uses stdio transport and follows the standard MCP protocol. It can be integrated with any MCP-compatible client by running:

npx @zilliz/claude-context-mcp@latest

Open Claude Code
```
cd your-project-directory
claude
```
Index your codebase :
Check indexing status :
```
Check the indexing status
```

Start searching :

Find functions that handle user authentication

🎉 That's it! You now have semantic code search in Claude Code.

Environment Variables Configuration

For more detailed MCP environment variable configuration, see our Environment Variables Guide.

Using Different Embedding Models

To configure custom embedding models (e.g., text-embedding-3-large for OpenAI, voyage-code-3 for VoyageAI), see the MCP Configuration Examples for detailed setup instructions for each provider.

File Inclusion & Exclusion Rules

For detailed explanation of file inclusion and exclusion rules, and how to customize them, see our File Inclusion & Exclusion Rules.

Index a codebase directory for hybrid search (BM25 + dense vector).

Search the indexed codebase using natural language queries with hybrid search (BM25 + dense vector).

Clear the search index for a specific codebase.

Get the current indexing status of a codebase. Shows progress percentage for actively indexing codebases and completion status for indexed codebases.

Our controlled evaluation demonstrates that Claude Context MCP achieves ~40% token reduction under the condition of equivalent retrieval quality. This translates to significant cost and time savings in production environments. This also means that, under the constraint of limited token context length, using Claude Context yields better retrieval and answer results.

For detailed evaluation methodology and results, see the evaluation directory.

🔍 Hybrid Code Search : Ask questions like "find functions that handle user authentication" and get relevant, context-rich code instantly using advanced hybrid search (BM25 + dense vector).
🧠 Context-Aware : Discover large codebase, understand how different parts of your codebase relate, even across millions of lines of code.
⚡ Incremental Indexing : Efficiently re-index only changed files using Merkle trees.
🧩 Intelligent Code Chunking : Analyze code in Abstract Syntax Trees (AST) for chunking.
🗄️ Scalable : Integrates with Zilliz Cloud for scalable vector search, no matter how large your codebase is.
🛠️ Customizable : Configure file extensions, ignore patterns, and embedding models.

Claude Context is a monorepo containing three main packages:

@zilliz/claude-context-core : Core indexing engine with embedding and vector database integration
VSCode Extension : Semantic Code Search extension for Visual Studio Code
@zilliz/claude-context-mcp : Model Context Protocol server for AI agent integration
Embedding Providers : OpenAI, VoyageAI, Ollama, Gemini
Vector Databases : Milvus or Zilliz Cloud(fully managed vector database as a service)
Code Splitters : AST-based splitter (with automatic fallback), LangChain character-based splitter
Languages : TypeScript, JavaScript, Python, Java, C++, C#, Go, Rust, PHP, Ruby, Swift, Kotlin, Scala, Markdown
Development Tools : VSCode, Model Context Protocol

📦 Other Ways to Use Claude Context

While MCP is the recommended way to use Claude Context with AI assistants, you can also use it directly or through the VSCode extension.

Build Applications with Core Package

The @zilliz/claude-context-core package provides the fundamental functionality for code indexing and semantic search.

import { Context, MilvusVectorDatabase, OpenAIEmbedding } from '@zilliz/claude-context-core';

// Initialize embedding provider
const embedding = new OpenAIEmbedding({
    apiKey: process.env.OPENAI_API_KEY || 'your-openai-api-key',
    model: 'text-embedding-3-small'
});

// Initialize vector database
const vectorDatabase = new MilvusVectorDatabase({
    address: process.env.MILVUS_ADDRESS || 'your-zilliz-cloud-public-endpoint',
    token: process.env.MILVUS_TOKEN || 'your-zilliz-cloud-api-key'
});

// Create context instance
const context = new Context({
    embedding,
    vectorDatabase
});

// Index your codebase with progress tracking
const stats = await context.indexCodebase('./your-project', (progress) => {
    console.log(`${progress.phase} - ${progress.percentage}%`);
});
console.log(`Indexed ${stats.indexedFiles} files, ${stats.totalChunks} chunks`);

// Perform semantic search
const results = await context.semanticSearch('./your-project', 'vector database operations', 5);
results.forEach(result => {
    console.log(`File: ${result.relativePath}:${result.startLine}-${result.endLine}`);
    console.log(`Score: ${(result.score * 100).toFixed(2)}%`);
    console.log(`Content: ${result.content.substring(0, 100)}...`);
});

Integrates Claude Context directly into your IDE. Provides an intuitive interface for semantic code search and navigation.

Direct Link : Install from VS Code Marketplace
Manual Search :
- Open Extensions view in VSCode (Ctrl+Shift+X or Cmd+Shift+X on Mac)
- Search for "Semantic Code Search"
- Click Install

Setup Development Environment

Node.js 20.x, 22.x, or 24.x
pnpm (recommended package manager)

Clone repository

git clone https://github.com/zilliztech/claude-context.git cd claude-context

Install dependencies

pnpm install

Build all packages

pnpm build

Start development mode

pnpm dev

On Windows, ensure you have:

Git for Windows with proper line ending configuration
Node.js installed via the official installer or package manager
pnpm installed globally: npm install -g pnpm

Windows PowerShell/Command Prompt

git clone https://github.com/zilliztech/claude-context.git cd claude-context

Configure git line endings (recommended)

git config core.autocrlf false

Install dependencies

pnpm install

Build all packages (uses cross-platform scripts)

pnpm build

Start development mode

pnpm dev

Build all packages (cross-platform)

pnpm build

Build specific package

pnpm build:core pnpm build:vscode pnpm build:mcp

Performance benchmarking

pnpm benchmark
All build scripts are cross-platform compatible using rimraf
Build caching is enabled for faster subsequent builds
Use PowerShell or Command Prompt - both work equally well

Development with file watching

cd examples/basic-usage pnpm dev

Check the /examples directory for complete usage examples:

Basic Usage : Simple indexing and search example

Common Questions:

❓ For detailed answers and more troubleshooting tips, see our FAQ Guide.

🔧 Encountering issues? Visit our Troubleshooting Guide for step-by-step solutions.

📚 Need more help? Check out our complete documentation for detailed guides and troubleshooting tips.

We welcome contributions! Please see our Contributing Guide for details on how to get started.

Package-specific contributing guides:

This project is licensed under the MIT License - see the LICENSE file for details.

zilliztech/claude-context：将整个代码库变成 Claude 编程 Agent 的上下文

中文

将整个代码库作为 Claude 的上下文

为 Claude Code 配置 MCP

其他 MCP 客户端配置

注意：顶级键是 mcp_servers 而不是 mcpServers。

可选：覆盖默认 10s 启动超时

A. 使用 Augment Code UI

B. 手动配置（通过 settings.json）

English / 原文

Your entire codebase as Claude's context

Configure MCP for Claude Code

Other MCP Client Configurations

A. Using the Augment Code UI

Environment Variables Configuration

Using Different Embedding Models

File Inclusion & Exclusion Rules

📦 Other Ways to Use Claude Context

Build Applications with Core Package

Setup Development Environment

Clone repository

Install dependencies

Build all packages

Start development mode

Windows PowerShell/Command Prompt

Configure git line endings (recommended)

Install dependencies

Build all packages (uses cross-platform scripts)

Start development mode

Build all packages (cross-platform)

Build specific package

Performance benchmarking

Development with file watching

注意：顶级键是 `mcp_servers` 而不是 `mcpServers`。