AI Skill Hub 推荐使用:来当MCP模式 是一款优质的MCP工具。AI 综合评分 7.5 分,在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案,这是一个值得深入了解的选择。
有公台MCP模式器为OpenROAD的导八器。导八为常式为导八为常式。
来当MCP模式 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
有公台MCP模式器为OpenROAD的导八器。导八为常式为导八为常式。
来当MCP模式 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/luarss/openroad-mcp
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"--mcp--": {
"command": "npx",
"args": ["-y", "openroad-mcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 来当MCP模式 执行以下任务... Claude: [自动调用 来当MCP模式 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"__mcp__": {
"command": "npx",
"args": ["-y", "openroad-mcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
A Model Context Protocol (MCP) server that provides tools for interacting with OpenROAD and ORFS (OpenROAD Flow Scripts).
curl -LsSf https://astral.sh/uv/install.sh | shNew to OpenROAD MCP? Check out our Quick Start guide.
For platform-specific setup instructions, see the Cross-Platform Guide.
<details> <summary><b>Claude Code</b></summary>
claude mcp add --transport stdio openroad-mcp -- uvx --from git+https://github.com/luarss/openroad-mcp openroad-mcp
Or add the standard configuration to .claude/settings.json.
</details>
<details> <summary><b>Claude Desktop</b></summary>
Add the standard configuration to: - macOS: ~/Library/Application Support/Claude/claude_desktop_config.json - Windows: %APPDATA%\Claude\claude_desktop_config.json
</details>
<details> <summary><b>Cursor</b></summary>
Add the standard configuration to .cursor/mcp.json.
</details>
<details> <summary><b>GitHub Copilot (VS Code)</b></summary>
Add to .vscode/mcp.json (VS Code 1.99+). Note the different schema — servers key and "type": "stdio" required:
{
"servers": {
"openroad-mcp": {
"type": "stdio",
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
]
}
}
}
</details>
<details> <summary><b>Gemini CLI</b></summary>
Follow the Gemini MCP install guide, using the standard configuration above.
</details>
<details> <summary><b>Windsurf</b></summary>
Add the standard configuration to ~/.codeium/windsurf/mcp_config.json.
</details>
<details> <summary><b>Cline</b></summary>
Add to the Cline MCP settings file: - macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json - Windows: %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json - Linux: ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
{
"mcpServers": {
"openroad-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
],
"disabled": false,
"autoApprove": []
}
}
}
</details>
<details> <summary><b>Roo Code</b></summary>
Add to .roo/mcp.json in your project root (or the equivalent user-level settings file via the Roo Code UI):
{
"mcpServers": {
"openroad-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
],
"disabled": false,
"autoApprove": []
}
}
}
</details>
<details> <summary><b>Continue</b></summary>
Add to ~/.continue/config.json:
{
"experimental": {
"modelContextProtocolServers": [
{
"transport": {
"type": "stdio",
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
]
}
}
]
}
}
</details>
<details> <summary><b>Zed</b></summary>
Add to ~/.config/zed/settings.json:
{
"context_servers": {
"openroad-mcp": {
"command": {
"path": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
]
},
"settings": {}
}
}
}
</details>
<details> <summary><b>JetBrains AI Assistant</b></summary>
Open Settings → Tools → AI Assistant → Model Context Protocol (MCP) and add a new server entry using the standard configuration.
</details>
<details> <summary><b>Amazon Q Developer CLI</b></summary>
Add the standard configuration to ~/.aws/amazonq/mcp.json.
</details>
<details> <summary><b>Augment Code</b></summary>
Add to your VS Code settings.json (User or Workspace scope):
{
"augment.advanced": {
"mcpServers": [
{
"name": "openroad-mcp",
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
]
}
]
}
}
</details>
<details> <summary><b>Warp</b></summary>
Open Settings → AI → MCP Servers → Add New MCP Server and enter: - Name: openroad-mcp - Command: uvx - Args: --from git+https://github.com/luarss/openroad-mcp openroad-mcp
</details>
<details> <summary><b>Amp</b></summary>
amp mcp add openroad-mcp uvx --from git+https://github.com/luarss/openroad-mcp openroad-mcp
</details>
<details> <summary><b>Trae</b></summary>
Add the standard configuration to the MCP section of Trae's user settings (accessible via Settings → MCP).
</details>
<details> <summary><b>Opencode</b></summary>
Add to opencode.json in your project root:
{
"mcp": {
"openroad-mcp": {
"type": "local",
"command": [
"uvx",
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
],
"enabled": true
}
}
}
</details>
<details> <summary><b>Kiro</b></summary>
Open the MCP configuration panel in Kiro and add a new server entry using the standard configuration.
</details>
<details> <summary><b>Kilo Code</b></summary>
Add to .kilocode/mcp.json in your project root:
{
"mcpServers": {
"openroad-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
],
"alwaysAllow": [],
"disabled": false
}
}
}
</details>
<details> <summary><b>Docker</b></summary>
🚧 Work in Progress: Docker deployment via GitHub Container Registry (GHCR) is coming soon.
</details>
<details> <summary><b>MCP Registry</b></summary>
Once published to the MCP Registry, clients can discover and install directly:
uvx openroad-mcp
</details>
```bash
uv venv make sync ```
The basic configuration for all MCP clients:
{
"mcpServers": {
"openroad-mcp": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/luarss/openroad-mcp",
"openroad-mcp"
]
}
}
}
For local development, use:
{
"mcpServers": {
"openroad-mcp": {
"command": "uv",
"args": [
"--directory",
"/path/to/openroad-mcp",
"run",
"openroad-mcp"
]
}
}
}
make test
If the MCP server fails to start:
uv is installed and available in your PATHmake sync常式模式器为有使用的导八器。导八为常式。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ BSD 3-Clause — 宽松协议,可商用修改分发,禁止使用原作者名称进行背书宣传。
总体来看,来当MCP模式 是一款质量良好的MCP工具,在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态,建议收藏备用,结合自身场景选择合适时机引入使用。
| 原始名称 | openroad-mcp |
| 原始描述 | 开源MCP工具: Model Context Protocol (MCP) server for OpenROAD。⭐10 · Python |
| Topics | mcpai-toolsasic-designchip-designedafastmcppython |
| GitHub | https://github.com/luarss/openroad-mcp |
| License | BSD-3-Clause |
| 语言 | Python |
收录时间:2026-05-24 · 更新时间:2026-05-30 · License:BSD-3-Clause · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端