Hamza-Chergui-Converteo/adk-mcp-servers
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This project demonstrates the implementation of a Model Context Protocol (MCP) server using a SQLite CRM database, integrated with a Google ADK-powered agent.
MCP CRM Example with Google ADK
This repository demonstrates how to build an MCP (Model Context Protocol) server backed by a SQLite CRM database, and how to interact with it using a Gemini-powered agent via the Google Application Development Kit (ADK).
🚀 What is This Project?
- ✅ A ready-to-use MCP server using a SQLite CRM database
- 🤖 A custom Google ADK agent capable of querying, updating, and analyzing CRM data
- 💬 A simulated CLI chat interface to test interactions with the agent
- 🧰 A toolset of 6 MCP tools exposed to the agent (read, write, create, list tables, describe schema, add insights)
🧱 Project Structure
mcp-crm-project/
├── agent.py # Main agent logic (Gemini + ADK)
├── db/
│ ├── setup_db.py # Script to initialize the SQLite database
│ └── crm.db # Auto-generated SQLite CRM database
├── sqlite/ # MCP server adapted from official repo
└── README.md # You're here!
🛠️ Setup Instructions
1. Clone the Repository
git clone https://github.com/Hamza-Chergui-Converteo/adk-mcp-servers.git
cd mcp-crm-project
2. Initialize the SQLite Database
cd db
python setup_db.py
This will create a crm.db file with mock data.
3. Add Your Gemini API Key
In agent.py, replace YOUR_API_KEY with your actual Google API key:
os.environ["GOOGLE_API_KEY"] = "your-key-here"
🧠 Agent Toolset
The MCP server exposes 6 tools accessible by the agent:
🔍 Query Tools
read_query: Run SELECT querieswrite_query: INSERT, UPDATE, DELETEcreate_table: Create new tables
🧾 Schema Tools
list_tables: List all tablesdescribe_table: Get schema of a table
📊 Insight Tools
append_insight: Add business insights tomemo://insights
💬 Start Chatting with the Agent
Simply run:
python agent.py
You’ll enter a CLI chat with the CRM agent. Type your questions or SQL commands (e.g., “list all prospects”, “add a new contact”, etc.). Type exit to quit.
📚 Reference
This project is based on the official MCP servers repository:
🔗 https://github.com/modelcontextprotocol/servers
Feel free to explore it for other backends (Redis, OpenAI, Slack, etc.).