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jiangmuran

DeepVLab Analytics MCP Server

by jiangmuran

DeepVLab Analytics MCP Server

A Model Context Protocol (MCP) server for querying DeepVLab account statistics and model usage analytics.

Features

  • 🔐 Browser Authorization - Automated login and token management.

  • 👤 User Profile - View basic account information and balance.

  • 📊 Usage Analytics - Detailed statistics on model usage, daily trends, and quotas.

  • 💰 Cost Calculator - Estimate and compare costs across different models.

  • 📈 Real-time Data - Fetched directly from DeepVLab API.

Related MCP server: @volter/tunnel-mcp

Quick Start

1. Installation

git clone https://github.com/yourusername/deepvlab-mcp.git
cd deepvlab-mcp
pip install -r requirements.txt

2. Configuration

Add the server to your claude_desktop_config.json:

{
  "mcpServers": {
    "deepvlab-analytics": {
      "command": "python",
      "args": ["/path/to/deepvlab-mcp/server.py"],
      "env": {
        "PYTHONPATH": "/path/to/deepvlab-mcp"
      }
    }
  }
}

Note: Replace /path/to/deepvlab-mcp with your actual absolute path.

3. Usage

Restart Claude Desktop and simply ask:

  • "Login to DeepVLab"

  • "Show my account balance"

  • "Compare costs for Claude 3.5 Sonnet vs GPT-4o"

Available Tools

Tool

Description

login

Launch browser to authorize and get token

get_user_summary

Get user info and balance overview

get_model_rates

List all models and their rates

get_credits_usage

Detailed credit usage stats

get_model_usage

Usage stats per model

get_daily_usage

Daily usage trends

get_quotas

Quota information

calculate_cost

Calculate cost for specific token counts

estimate_batch_cost

Estimate costs for batch requests

compare_model_costs

Compare costs across multiple models

License

MIT

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