open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/mcp-llm
Description: MCP server for interacting with LLMs using LlamaIndexTS
Author: Sam McLeod
Latest version: 1.0.6

# MCP LLM
[![smithery badge](https://smithery.ai/badge/@sammcj/mcp-llm)](https://smithery.ai/server/@sammcj/mcp-llm)

An MCP server that provides access to LLMs using the LlamaIndexTS library.

![I put some LLMs in your MCP for your LLMs](legit.png)

<a href="https://glama.ai/mcp/servers/i1gantlfrs">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/i1gantlfrs/badge" alt="mcp-llm MCP server" />
</a>

## Features

This MCP server provides the following tools:

- `generate_code`: Generate code based on a description
- `generate_code_to_file`: Generate code and write it directly to a file at a specific line number
- `generate_documentation`: Generate documentation for code
- `ask_question`: Ask a question to the LLM

![call a llm to generate code](screenshot1.png)
![call a reasoning llm to write some documentation](screenshot2.png)

## Installation

### Installing via Smithery

To install LLM Server for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@sammcj/mcp-llm):

```bash
npx -y @smithery/cli install @sammcj/mcp-llm --client claude
```

### Manual Install From Source

1. Clone the repository
2. Install dependencies:

```bash
npm install
```

3. Build the project:

```bash
npm run build
```

4. Update your MCP configuration

### Using the Example Script

The repository includes an example script that demonstrates how to use the MCP server programmatically:

```bash
node examples/use-mcp-server.js
```

This script starts the MCP server and sends requests to it using curl commands.

## Examples

### Generate Code

```json
{
  "description": "Create a function that calculates the factorial of a number",
  "language": "JavaScript"
}
```

### Generate Code to File

```json
{
  "description": "Create a function that calculates the factorial of a number",
  "language": "JavaScript",
  "filePath": "/path/to/factorial.js",
  "lineNumber": 10,
  "replaceLines": 0
}
```

The `generate_code_to_file` tool supports both relative and absolute file paths. If a relative path is provided, it will be resolved relative to the current working directory of the MCP server.

### Generate Documentation

```json
{
  "code": "function factorial(n) {\n  if (n <= 1) return 1;\n  return n * factorial(n - 1);\n}",
  "language": "JavaScript",
  "format": "JSDoc"
}
```

### Ask Question

```json
{
  "question": "What is the difference between var, let, and const in JavaScript?",
  "context": "I'm a beginner learning JavaScript and confused about variable declarations."
}
```

## License

- [MIT LICENSE](LICENSE)
npm package: @iflow-mcp/mcp-llms-txt-explorer
Description: A Model Context Protocol server for exploring websites with llms.txt files
Author: David Dias
Latest version: 0.2.0

# MCP LLMS.txt Explorer

<a href="https://glama.ai/mcp/servers/lhyj3pva0z">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/lhyj3pva0z/badge" alt="LLMS.txt Explorer MCP server" />
</a>

[![smithery badge](https://smithery.ai/badge/@thedaviddias/mcp-llms-txt-explorer)](https://smithery.ai/server/@thedaviddias/mcp-llms-txt-explorer)

A Model Context Protocol server for exploring websites with llms.txt files. This server helps you discover and analyze websites that implement the llms.txt standard.

## Features

### Resources
- Check websites for llms.txt and llms-full.txt files
- Parse and validate llms.txt file contents
- Access structured data about compliant websites

### Tools
- `check_website` - Check if a website has llms.txt files
  - Takes domain URL as input
  - Returns file locations and validation status
- `list_websites` - List known websites with llms.txt files
  - Returns structured data about compliant websites
  - Supports filtering by file type (llms.txt/llms-full.txt)

## Development

Install dependencies:
```bash
pnpm install
```

Build the server:
```bash
pnpm run build
```

For development with auto-rebuild:
```bash
pnpm run watch
```

## Installation

### Installing via Smithery

To install mcp-llms-txt-explorer for Claude Desktop automatically via [Smithery](https://smithery.ai/server/@thedaviddias/mcp-llms-txt-explorer):

```bash
npx -y @smithery/cli install @thedaviddias/mcp-llms-txt-explorer --client claude
```

### Installing Manually
To use this server:

```bash
# Clone the repository
git clone https://github.com/thedaviddias/mcp-llms-txt-explorer.git
cd mcp-llms-txt-explorer

# Install dependencies
pnpm install

# Build the server
pnpm run build
```

### Configuration with Claude Desktop

To use with Claude Desktop, add the server config:

On MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

```json
{
  "mcpServers": {
    "llms-txt-explorer": {
      "command": "node",
      "args": ["/path/to/llms-txt-explorer/build/index.js"],
    }
  }
}
```

For npx usage, you can use:
```json
{
  "mcpServers": {
    "llms-txt-explorer": {
      "command": "npx",
      "args": ["-y", "@thedaviddias/mcp-llms-txt-explorer"]
    }
  }
}
```

### Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script:

```bash
pnpm run inspector
```

The Inspector will provide a URL to access debugging tools in your browser.

## License

This project is licensed under the MIT License—see the LICENSE file for details.
npm package: @iflow-mcp/mcp-local-file-reader
Description: A Model Context Protocol server for reading local files
Author: Your Name
Latest version: 0.1.0

# MCP Local File Reader

一个基于 Model Context Protocol (MCP) 的本地文件读取服务器，允许 AI 模型安全地访问本地文件系统。

## 功能特点

### 资源 (Resources)
- 列出和访问本地文件系统中的文件
- 支持多种文件类型，包括文本文件和二进制文件
- 自动检测文件 MIME 类型，提供适当的内容处理

### 工具 (Tools)
- `read_file` - 读取指定文件的内容
  - 对文本文件返回完整内容
  - 对二进制文件返回文件信息摘要
- `list_files` - 列出指定目录中的所有文件
  - 返回文件名列表
- `get_file_info` - 获取指定文件的详细信息
  - 返回文件大小、类型、创建时间等元数据

## 安装

```bash
npm install mcp-local-file-reader
```

## 使用方法

### 作为命令行工具

安装后，可以直接在命令行中运行：

```bash
npx mcp-local-file-reader
```
此时会启动一个 MCP node服务器，监听llm对话。

## 与 AI 工具集成

### 在 Windsurf 中使用

在windsurf中，不需要手动启动mcp-local-file-reader，只需要配置即可，windsurf会自动启动mcp-local-file-reader（在windsurf的mcp_config.json中配置，点击refresh刷新服务器）。

1. 在 Windsurf 的 mcp_config.json 配置文件中添加以下配置(FILE_TOOLS_API_KEY暂时还不需要)：

#### 本地化部署

```json
{
  "servers": {
    "file-tools": {
      "command": "cmd",
      "args": [
        "/c",
        "node",
        "path/to/mcp-local-file-reader/build/index.js"
      ],
      "env": {
        "FILE_TOOLS_API_KEY": ""
      }
    }
  }
}
```

#### 使用npm的形式部署

```json
{
  "servers": {
    "file-tools": {
      "command": "cmd",
      "args": [
        "/c",
        "npx",
        "mcp-local-file-reader"
      ],
      "env": {
        "FILE_TOOLS_API_KEY": ""
      }
    }
  }
}
```


点击windsurf对话框的小锤子图标，点击refrsh刷新服务器
官方配置说明：https://docs.codeium.com/windsurf/mcp

2. 重启 Windsurf 以加载新的 MCP 配置

### 在其他 MCP 兼容的 AI 应用中使用

按照特定应用的 MCP 集成指南，添加此服务器作为工具提供者。cursor配置与windsurf中的配置类似，vscode的cline会稍微复杂一些。但是本质都是配置mcp.json，可以类似的配置。

## 开发

安装依赖：
```bash
npm install
```

构建服务器：
```bash
npm run build
```

开发模式（自动重新构建）：
```bash
npm run watch
```

使用 MCP Inspector 测试：
```bash
npm run inspector
```

## 安全注意事项

此服务器允许 AI 模型访问本地文件系统，请谨慎使用并确保：

1. 只允许访问必要的目录
2. 不要暴露敏感文件或目录
3. 在生产环境中使用前，考虑添加额外的安全限制

## 许可证

MIT