Volume Wall Detector MCP
# Volume Wall Detector MCP Server 📊
> 🔌 **Compatible with Cline, Cursor, Claude Desktop, and any other MCP Clients!**
>
> Volume Wall Detector MCP works seamlessly with any MCP client
<p align="center">
<img src="vld-logo.png" width="300" alt="VLD Logo">
</p>
The Model Context Protocol (MCP) is an open standard that enables AI systems to interact seamlessly with various data sources and tools, facilitating secure, two-way connections.
The Volume Wall Detector MCP server provides:
* Real-time stock trading volume analysis
* Detection of significant price levels (volume walls)
* Trading imbalance tracking and analysis
* After-hours trading analysis
* MongoDB-based data persistence
## Prerequisites 🔧
Before you begin, ensure you have:
* MongoDB instance running
* Stock market API access
* Node.js (v20 or higher)
* Git installed (only needed if using Git installation method)
## Volume Wall Detector MCP Server Installation ⚡
### Running with NPX
```bash
npx -y volume-wall-detector-mcp@latest
```
### Installing via Smithery
To install Volume Wall Detector MCP Server for Claude Desktop automatically via Smithery:
```bash
npx -y @smithery/cli install volume-wall-detector-mcp --client claude
```
## Configuring MCP Clients ⚙️
### Configuring Cline 🤖
1. Open the Cline MCP settings file:
```bash
# For macOS:
code ~/Library/Application\ Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
# For Windows:
code %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
```
2. Add the Volume Wall Detector server configuration:
```json
{
"mcpServers": {
"volume-wall-detector-mcp": {
"command": "npx",
"args": ["-y", "volume-wall-detector-mcp@latest"],
"env": {
"TIMEZONE": "GMT+7",
"API_BASE_URL": "your-api-url-here",
"MONGO_HOST": "localhost",
"MONGO_PORT": "27017",
"MONGO_DATABASE": "volume_wall_detector",
"MONGO_USER": "admin",
"MONGO_PASSWORD": "password",
"MONGO_AUTH_SOURCE": "admin",
"MONGO_AUTH_MECHANISM": "SCRAM-SHA-1",
"PAGE_SIZE": "50",
"TRADES_TO_FETCH": "10000",
"DAYS_TO_FETCH": "1",
"TRANSPORT_TYPE": "stdio",
"PORT": "8080"
},
"disabled": false,
"autoApprove": []
}
}
}
```
### Configuring Cursor 🖥️
> **Note**: Requires Cursor version 0.45.6 or higher
1. Open Cursor Settings
2. Navigate to Open MCP
3. Click on "Add New Global MCP Server"
4. Fill out the following information:
* **Name**: "volume-wall-detector-mcp"
* **Type**: "command"
* **Command**:
```bash
env TIMEZONE=GMT+7 API_BASE_URL=your-api-url-here MONGO_HOST=localhost MONGO_PORT=27017 MONGO_DATABASE=volume_wall_detector MONGO_USER=admin MONGO_PASSWORD=password MONGO_AUTH_SOURCE=admin MONGO_AUTH_MECHANISM=SCRAM-SHA-1 PAGE_SIZE=50 TRADES_TO_FETCH=10000 DAYS_TO_FETCH=1 npx -y volume-wall-detector-mcp@latest
```
### Configuring Claude Desktop 🖥️
Create or edit the Claude Desktop configuration file:
#### For macOS:
```bash
code "$HOME/Library/Application Support/Claude/claude_desktop_config.json"
```
#### For Windows:
```bash
code %APPDATA%\Claude\claude_desktop_config.json
```
Add the configuration:
```json
{
"mcpServers": {
"volume-wall-detector-mcp": {
"command": "npx",
"args": ["-y", "volume-wall-detector-mcp@latest"],
"env": {
"TIMEZONE": "GMT+7",
"API_BASE_URL": "your-api-url-here",
"MONGO_HOST": "localhost",
"MONGO_PORT": "27017",
"MONGO_DATABASE": "volume_wall_detector",
"MONGO_USER": "admin",
"MONGO_PASSWORD": "password",
"MONGO_AUTH_SOURCE": "admin",
"MONGO_AUTH_MECHANISM": "SCRAM-SHA-1",
"PAGE_SIZE": "50",
"TRADES_TO_FETCH": "10000",
"DAYS_TO_FETCH": "1",
"TRANSPORT_TYPE": "stdio",
"PORT": "8080"
}
}
}
}
```
## License
MIT TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: analyze-stock focuses on data analysis, fetch-order-book retrieves order book data, and fetch-trades gets trade history. There is no overlap in functionality, making it easy for an agent to select the right tool without confusion.
The naming is mostly consistent with a verb-noun pattern (analyze-stock, fetch-order-book, fetch-trades), using kebab-case throughout. The minor deviation is that analyze-stock uses 'analyze' while the others use 'fetch', but this is reasonable given the different actions.
With only 3 tools, the set feels thin for a server named 'Volume Wall Detector MCP', which suggests a focus on volume analysis in trading. While the tools cover basic data fetching and analysis, more tools might be expected for comprehensive volume detection or trading operations.
The tools provide core data retrieval (order book, trades) and analysis, but there are notable gaps for a volume-focused detector, such as tools for real-time volume alerts, historical volume trends, or integration with trading actions. The surface is functional but incomplete for advanced volume analysis workflows.