Which integrations are available for this server?

Enables AI agents to query a PostgreSQL database through a secure layer of predefined tools, allowing for the retrieval of employee information, project statuses, and issue priorities without exposing database credentials or allowing direct SQL execution.

How do I use MCP Dummy DB Integration?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@MCP Dummy DB Integration list all employees in the AI department" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

MCP Dummy DB Integration

by muniasamyk

Overview Schema Source Related Servers Discussions Admin

Remote

MCP Agent POC

This project demonstrates a secure, production-ready implementation of the Model Context Protocol (MCP) as a connector layer between AI agents and PostgreSQL databases. The solution enables natural language queries without exposing database credentials to the LLM.

Key Achievement: LLM cannot access database directly - only through predefined MCP tools.

🏗️ Architecture Overview

┌────────────────────────────────────────────────────────┐
│                    USER QUERY                         │
│          "Fetch employees in AI department"           │
└───────────────────┬────────────────────────────────────┘
                    │
                    ▼
┌────────────────────────────────────────────────────────┐
│         PLANNER AGENT (LLM)                           │
│  ✓ Natural Language Understanding                     │
│  ✗ NO database credentials                            │
│  Output: {"tool": "get_employees_by_department",      │
│           "parameters": {"department": "AI"}}         │
└───────────────────┬────────────────────────────────────┘
                    │
                    ▼
┌────────────────────────────────────────────────────────┐
│         EXECUTOR AGENT                                 │
│  ✓ Validates tool request                            │
│  ✓ Maps to allowed operations only                   │
│  ✗ Cannot execute arbitrary SQL                      │
└───────────────────┬────────────────────────────────────┘
                    │
                    ▼
┌────────────────────────────────────────────────────────┐
│         MCP TOOLS LAYER (Sandbox)                     │
│  ✓ get_employees_by_department("AI")                │
│  ✓ get_projects_by_status("Completed")              │
│  ✓ get_issues_by_priority("High")                   │
│  ✗ Cannot run arbitrary SQL                          │
└───────────────────┬────────────────────────────────────┘
                    │
                    ▼
┌────────────────────────────────────────────────────────┐
│         DATABASE CONNECTION (Secure)                  │
│  ✓ Credentials in environment variables             │
│  ✓ Only parameterized queries (SQL injection safe)  │
└───────────────────┬────────────────────────────────────┘
                    │
                    ▼
┌────────────────────────────────────────────────────────┐
│         RESULT TO USER                               │
│    [Secure data retrieval via MCP]                   │
└────────────────────────────────────────────────────────┘

Related MCP server: PostgreSQL MCP Server

🔒 Security Features

Feature	With MCP
DB Credentials	Secure in .env ✅
SQL Access	Predefined tools only ✅
Attack Surface	Limited operations only ✅
Audit Trail	Full logging ✅
Connection Pool	Yes ✅

Project Structure

app/agents/: The brain (Planner, Executor, Orchestrator)
app/mcp/: The tool layer (Connector to DB)
app/database/: Low-level DB connection pool
app/api/: FastAPI routes

Getting Started

1. Setup Env

Copy the example config:

cp .env.example .env

2. Run with Docker

The easiest way to stand it up (Postgres + API):

docker-compose up --build

The API listens on http://localhost:8000.

3. Test It

You can use the swagger UI at /docs or curl:

curl -X POST "http://localhost:8000/api/v1/query" \
     -H "Content-Type: application/json" \
     -d '{"query": "Find all projects that are in progress"}'

Local Dev (No Docker)

If you have Python 3.11+ and a local Postgres running:

pip install -r requirements.txt
Update .env with your DB credentials
python -m app.main

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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