Employee MCP Server (Mongo + AI Pipeline)
Enables querying administration-style employee data in MongoDB using natural language through various AI providers.
README
Employee MCP Server (Mongo + AI Pipeline)
Architecture is now:
- AI Planner
- Mongo Executor
- AI Analysis Result
No SQL path is used.
MongoDB
Default URI:
mongodb://admin:password@localhost:27017
On startup, the server seeds large dummy administration-style data (1500 employees) into:
- DB:
employee_admin - Collection:
employees
Common model environment
Create .env (or set environment variables):
AI_PROVIDER=nvidia
AI_TIMEOUT_MS=30000
MONGO_URI=mongodb://admin:password@localhost:27017
MONGO_DB_NAME=employee_admin
MONGO_COLLECTION=employees
OLLAMA_HOST=http://127.0.0.1:11434
OLLAMA_MODEL=qwen2.5:3b
OLLAMA_CHAT_PATH=/api/chat
OPENAI_API_KEY=
OPENAI_MODEL=gpt-4.1-mini
OPENAI_BASE_URL=https://api.openai.com
CLAUDE_API_KEY=
CLAUDE_MODEL=claude-3-5-sonnet-20241022
CLAUDE_BASE_URL=https://api.anthropic.com
CLAUDE_MAX_TOKENS=2048
NVIDIA_API_KEY=
NVIDIA_MODEL=google/gemma-4-31b-it
NVIDIA_BASE_URL=https://integrate.api.nvidia.com
NVIDIA_MAX_TOKENS=16384
NVIDIA_TOP_P=0.95
NVIDIA_ENABLE_THINKING=true
Supported providers:
ollamaopenaiclaudenvidia
Run
npm install
node test-client.mjs --tests
Interactive:
node test-client.mjs
Example queries
Who has the highest salary?Who earns the least?What is the difference between highest and lowest salary?What is the average salary?How many employees are there?List employees in Administration
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