
Lead Qualifier MCP Tool
A lightweight server that uses ChatGPT to qualify leads using the BANT framework (Budget, Authority, Need, Timeline) through a conversational question-by-question approach.
README
🤖 Lead Qualifier MCP Tool
A lightweight MCP tool that uses ChatGPT to qualify leads over BANT mechanism (Budget, Authority, Need, Timeline). And guide users to enter leads informations question by question.
🚀 Features
- 🧠 LLM-powered lead qualification info (BANT) extraction and scoring
- 💬 One field per turn, with conversational flow
- 💾 Fast as in-memory session tracking, can be extended to Redis
- 🔌 Compatible with Dify / Cursor via MCP (
sse
)
⚙️ Setup
Configure ChatGPT apikey in your .env file.
OPENAI_API_KEY=1234
Start your NodeJS server, which is your MCP server.
npm install
npm start
Optional: expose your server using ngrok
ngrok http 3001
Dify Agent Strategy Configuration
{
"lead_qualification": {
"transport": "sse",
"url": "https://24c3-172-235-53-238.ngrok-free.app/sse",
"headers": {},
"timeout": 50,
"sse_read_timeout": 50
}
}
🛠 Example
Tool name: lead-qualifier
Input:
{
"sessionId": "abc123",
"message": "We have a budget of $1000"
}
Output:
{
content: [
{
type: "text",
text: "Are you the main person evaluating tools like this, or is there someone else involved in the decision?"
}
],
isError: false
}
Session:
{
"qualificationMap": {
"budget": "$1000 per month",
"authority": "",
"need": "",
"timeline": ""
},
"scoreMap": {
"budget": 30,
"authority": 0,
"need": 0,
"timeline": 0
},
"totalScore": 30,
"nextField": "authority",
"lastPromptedField": "authority",
"lastPromptedQuestion": "Are you the main person evaluating tools like this, or is there someone else involved in the decision?"
}
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