the docker file
هذا الالتزام موجود في:
208
README.md
208
README.md
@@ -1,3 +1,207 @@
|
||||
# MCP_SERCVER_SEARCH
|
||||
# 📚 MCP Documentation Server (Version 1)
|
||||
|
||||
This MCP Server helps you search for some docs like langchain, lammaindex, only using the Query or Prompet
|
||||
This project is an **MCP (Model Context Protocol) Server** designed to help fetch and search the latest documentation for libraries such as **`LangChain`**, **`OpenAI`**, and **`LlamaIndex`**.
|
||||
It allows you to query documentation sources and retrieve clean, plain text using a combination of **`Google Serper API`** for search and **`BeautifulSoup`** for scraping.
|
||||
|
||||
⚡ This is **Version 1 (In Progress)** — future versions will expand with more features and libraries.
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Features
|
||||
|
||||
- 🔍 Search official docs for supported libraries:
|
||||
- [LangChain](https://python.langchain.com/docs)
|
||||
- [OpenAI](https://platform.openai.com/docs)
|
||||
- [LlamaIndex](https://docs.llamaindex.ai/en/stable)
|
||||
- 🌐 Fetch and clean documentation text directly from web pages.
|
||||
- ⚙️ Exposed as an **MCP Tool** via `server.py`.
|
||||
- ⏳ Handles timeouts gracefully to avoid breaking workflows.
|
||||
- 🔑 Configurable using `.env` with your **Serper API Key**.
|
||||
|
||||
---
|
||||
|
||||
## 📂 Project Structure
|
||||
|
||||
```bash
|
||||
documentation/
|
||||
│── services/
|
||||
│ │──── scrape.py
|
||||
│ │──── search.py
|
||||
│
|
||||
│── tools/
|
||||
│ │──── get_docs.py
|
||||
│
|
||||
│──── config.py
|
||||
│──── server.py
|
||||
│──── pyproject.toml
|
||||
│──── .env.example
|
||||
│──── .gitignore
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## ⚡ Setup & Installation
|
||||
|
||||
This project uses [**uv**](https://docs.astral.sh/uv/) for dependency management.
|
||||
|
||||
### 1️⃣Clone the repository
|
||||
|
||||
```bash
|
||||
git clone <your-repo-url>
|
||||
cd documentation
|
||||
```
|
||||
|
||||
### 2️⃣ Create a virtual environment
|
||||
|
||||
```bash
|
||||
uv venv
|
||||
```
|
||||
|
||||
### 3️⃣ Activate the virtual environment
|
||||
|
||||
Linux/macOS:
|
||||
```bash
|
||||
source .venv/bin/activate
|
||||
```
|
||||
Windows (PowerShell):
|
||||
```bash
|
||||
.venv\Scripts\Activate
|
||||
```
|
||||
|
||||
### 4️⃣ Install dependencies
|
||||
|
||||
```bash
|
||||
uv sync
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🔑 Environment Variables
|
||||
|
||||
Copy .env.example → .env and set your Serper API key:
|
||||
```bash
|
||||
SERPER_API_KEY="your_api_key_here"
|
||||
```
|
||||
You can get an API key from [Serper.dev](https://serper.dev/)
|
||||
|
||||
---
|
||||
|
||||
## ▶️ Running the MCP Server
|
||||
|
||||
Start the server with:
|
||||
```bash
|
||||
uv run --with mcp mcp run server.py
|
||||
```
|
||||
This runs the MCP server over stdio, making it available as a tool.
|
||||
|
||||
---
|
||||
|
||||
## 🛠 How It Works
|
||||
|
||||
1. get_docs MCP tool
|
||||
- Input: query + library
|
||||
- Example: query="embedding models", library="openai"
|
||||
- Process:
|
||||
- Builds a site-specific query (site:platform.openai.com/docs embedding models)
|
||||
- Fetches results using Serper API
|
||||
- Scrapes and cleans text from found pages
|
||||
- Output: plain text documentation snippets
|
||||
2. Can be integrated into other MCP-compatible apps for automated documentation search & retrieval.
|
||||
|
||||
---
|
||||
|
||||
## 📌 Notes
|
||||
|
||||
- This is Version 1 — focused on core functionality.
|
||||
- Future improvements:
|
||||
- Support for more libraries/frameworks.
|
||||
- Improved result filtering & ranking.
|
||||
- Error handling & logging improvements.
|
||||
- Possible caching layer for repeated queries.
|
||||
|
||||
---
|
||||
|
||||
## 🐳 Docker Support
|
||||
|
||||
This project also provides a Dockerfile so you can containerize the MCP Documentation Server.
|
||||
|
||||
- Why Docker?
|
||||
- Consistency: run the server with the same environment on any machine.
|
||||
- Isolation: dependencies are fully contained, no need to pollute your local Python environment.
|
||||
- Portability: easy to share or deploy on servers/CI pipelines.
|
||||
- Caching: faster rebuilds thanks to Docker layer caching.
|
||||
|
||||
- When do you need it?
|
||||
- If you want to run the MCP server without installing uv or Python locally.
|
||||
- If you plan to deploy on a server or inside CI/CD pipelines.
|
||||
- If you want a reproducible environment across your team.
|
||||
|
||||
- How to use it?
|
||||
1. Build the image:
|
||||
```bash
|
||||
docker build -t docs-mcp:dev -f Dockerfile .
|
||||
```
|
||||
|
||||
2. Run with your .env file (containing SERPER_API_KEY):
|
||||
```bash
|
||||
docker run --rm -it --env-file .env docs-mcp:dev
|
||||
```
|
||||
|
||||
That’s it — the server will start inside the container and be available to any MCP-compatible client (e.g. Claude Desktop).
|
||||
|
||||
---
|
||||
|
||||
## 💻 Running Locally with Claude Desktop
|
||||
|
||||
You can also connect this MCP Documentation Server directly to Claude Desktop on your machine.
|
||||
|
||||
Steps:
|
||||
|
||||
1. Install Claude Desktop
|
||||
- Make sure Claude Desktop is already installed on your system.
|
||||
|
||||
2. Enable Developer Mode
|
||||
- Open Claude Desktop.
|
||||
- Go to Developer Mode.
|
||||
- Click Add Configuration.
|
||||
This will generate a local file called:
|
||||
|
||||
```bash
|
||||
claude_desktop_config.json
|
||||
```
|
||||
|
||||
3. Edit the Configuration File
|
||||
Open claude_desktop_config.json and add a new entry like this (adjust the paths to match your machine):
|
||||
```json
|
||||
{
|
||||
"mcpServers": {
|
||||
"documentation": {
|
||||
"command": "C:\\Users\\Alawakey\\Desktop\\MCP Server\\documentation\\.venv\\Scripts\\python.exe",
|
||||
"args": ["C:\\Users\\Alawakey\\Desktop\\MCP Server\\documentation\\server.py"],
|
||||
"cwd": "C:\\Users\\Alawakey\\Desktop\\MCP Server\\documentation"
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
- `command`: path to your Python executable inside the virtual environment.
|
||||
- `args`: path to the `server.py` file.
|
||||
- `cwd`: working directory of your project.
|
||||
|
||||
4. Restart Claude Desktop
|
||||
- Fully close Claude Desktop and start it again.
|
||||
|
||||
5. Verify the MCP Server
|
||||
- In Claude Desktop, go to Search and Tools (near the text input).
|
||||
- You should see your MCP server listed under the name you provided (`documentation` in the example above).
|
||||
|
||||
6. Try some queries
|
||||
- Example prompts:
|
||||
```bash
|
||||
how do i implement a chroma db in langchain?
|
||||
```
|
||||
```bash
|
||||
Use get_docs with query="ChatOpenAI" and library="openai"
|
||||
```
|
||||
Claude will ask for permission the first time you use the tool. After granting it, the `get_docs` tool will fetch results from the documentation.
|
||||
|
||||
---
|
||||
المرجع في مشكلة جديدة
حظر مستخدم