citystack-kumbh
CityStack Agent is a small Python-based tool that helps people find civic services like hospitals during large events — starting with the Kumbh Mela 2027 in Nashik. It uses real-time data and can run on local devices, with Internet.
🏙️ CityStack Agent – Kumbh Nashik 2027
CityStack Agent is a small Python-based tool that helps people find civic services like hospitals during large events — starting with the Kumbh Mela 2027 in Nashik.
It uses real-time data and can run on local devices, with Internet.
This project uses the Model Context Protocol (MCP) — a simple way to define and run local AI tools, like "find hospitals in Nashik", from chat interfaces or other apps. MCP makes it easy to connect real data and actions to AI agents.
✨ What It Can Do
- 🔍 Find nearby hospitals in Nashik using real data
- 🛠️ Works with Claude Desktop (or CLI) as a tool
- ⚙️ Built using Python and the MCP tool server
- 🔗 Connects to live civic data (ArcGIS)
ℹ️ About MCP
MCP (Model Context Protocol) is a lightweight way to define tools that AI models (like Claude or GPT) can call to fetch live data or take actions. This project includes a working MCP tool that looks up hospitals using real-time data.
🚀 How to Run It
1. Clone the Project
git clone https://github.com/ankushdeore/citystack-agent-kumbh-nashik.git
cd citystack-agent-kumbh-nashik
2. Set Up the Environment (with uv)
uv venv
source .venv/bin/activate
uv pip install
3. Start the Server
uv run server.py
4. (Optional) Run Tool Simulator
uv run simulate_citystack.py
🧪 Example Tool: find_civic_resource
Looks up hospitals in Nashik.
Input:
{ "resource_type": "hospital" }
Example Output:
Hospital A – Address 1 📍 (20.000000, 73.750000)
Hospital B – Address 2 📍 (20.005000, 73.760000)
📁 Folder Structure
citystack-agent-kumbh-nashik/
├── server.py # Starts the tool server
├── tools/
│ └── find_civic_resource.py
├── simulate_citystack.py # For testing locally
├── pyproject.toml
├── .gitignore
└── README.md
💻 Claude Desktop Setup
To use this with Claude Desktop, create a claude_config.json file:
{
"mcpServers": {
"citystack-kumbh": {
"command": "uv",
"args": [
"--directory",
"/Users/yourname/path/to/citystack-agent-kumbh-nashik",
"run",
"server.py"
]
}
}
}
Replace the path with your actual project location.
🌐 Deployment Notes
For cloud platforms like Render or Replit:
- Make sure
server.pylistens on0.0.0.0and gets the port from environment:
import os
port = int(os.environ.get("PORT", 8000))
- Start command:
uv run server.py
🔧 MCP Modifications
- ✅ Caching: repeated queries return from memory
- ✅ Privacy: added small random noise to hospital coordinates
🛣️ What's Next
Future Scope:
- 🚽 Toilet finder
- 🚰 Drinking Water finder
- 👮 Nearby police stations
- 📢 Emergency alert system
- 🛐 Cultural site guide
🙏 Credits
- Data: ArcGIS Open Data (https://www.arcgis.com)
- Inspiration: MIT Kumbhathon, CityStack idea, and Decentralized AI research
Recommend MCP Servers 💡
apollographql/apollo-mcp-server
Apollo MCP Server enables AI assistants like Claude Desktop to interact with any GraphQL API by exposing GraphQL operations as AI-accessible tools, facilitating real-time data queries.
devonmojito/ton-blockchain-mcp
An MCP server for natural language interaction with the TON blockchain
@deventerprisesoftware/scrapi-mcp
An MCP server that leverages the ScrAPI service to perform robust web page scraping, extracting content in either HTML or Markdown format, and handling challenges like bot detection and geolocation restrictions.
cfbd-mcp-server
An MCP server that provides access to comprehensive college football statistics and data from the College Football Data API V2, enabling AI assistants like Claude Desktop to query game results, team records, player statistics, and more using natural language.
jonathan-politzki/mcp-writer-substack
An MCP server that allows Claude to access and analyze your writing from platforms like Substack and Medium, providing personalized assistance with writing based on existing content.
mcp-server-for-intercom
An MCP-compliant server enabling AI assistants to access and analyze customer support data from Intercom.