Esankhyiki
This repository consists of Source Code for Model Context Protocol (MCP) Pilot Project being undertaken by Ministry of Statistics and Programme Implementation and source code for the same is being shared under MIT License.
What is Esankhyiki?
Esankhyiki is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to this repository consists of source code for model context protocol (mcp) pilot project being undertaken by ministry of statistics and programme implementation and source code for the same is being sha...
This repository consists of Source Code for Model Context Protocol (MCP) Pilot Project being undertaken by Ministry of Statistics and Programme Implementation and source code for the same is being shared under MIT License.
This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- This repository consists of Source Code for Model Context Pr
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx esankhyikiConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Esankhyiki
The eSankhyiki MCP Server is an official pilot project by India's Ministry of Statistics and Programme Implementation (MoSPI) that exposes 25+ national statistical datasets as MCP tools. It covers employment (PLFS), inflation (CPI), industrial production (IIP), GDP (NAS), energy, education (AISHE, UDISE), health (NFHS), gender indicators, and more. Researchers, policy analysts, and data journalists can query live government data through AI assistants without manually navigating the MoSPI portal.
Prerequisites
- Python 3.11 or later
- pip and the ability to install packages from requirements.txt (includes FastMCP 3.3)
- Internet access to reach the MoSPI API or the hosted endpoint at mcp.mospi.gov.in
- An MCP client that supports HTTP transport (e.g., Claude Desktop, Claude Code)
Clone the repository and create a virtual environment
Clone the esankhyiki-mcp repository and set up an isolated Python environment.
git clone https://github.com/nso-india/esankhyiki-mcp.git && cd esankhyiki-mcp && python -m venv venv && source venv/bin/activateInstall dependencies
Install all required Python packages including FastMCP and MoSPI API clients.
pip install -r requirements.txtStart the MCP server
Run the server using FastMCP over HTTP on the default port 8000. For local clients, you can also use stdio transport.
fastmcp run mospi_server.py:mcp --transport http --port 8000Connect via the hosted public endpoint (optional)
MoSPI also hosts a public endpoint. You can point your MCP client directly at it without running the server locally.
claude mcp add esankhyiki-mcp --transport http https://mcp.mospi.gov.in/Add to your local MCP client config
For a locally running instance, configure your MCP client to connect over HTTP.
claude mcp add esankhyiki-mcp --transport http http://localhost:8000/mcpEsankhyiki Examples
Client configuration (HTTP transport)
Connect Claude Desktop or another MCP client to the locally running eSankhyiki server.
{
"mcpServers": {
"esankhyiki": {
"type": "http",
"url": "http://localhost:8000/mcp"
}
}
}Prompts to try
The server exposes four tools in a sequential workflow: list_datasets → get_indicators → get_metadata → get_data. These prompts drive that workflow end-to-end.
- "What statistical datasets are available from MoSPI?"
- "Show me the indicators available for the CPI (Consumer Price Index) dataset."
- "What states and years of data are available for the PLFS employment survey?"
- "Get the latest GDP growth data from the National Accounts Statistics dataset."
- "Fetch inflation data for Maharashtra for 2023 from the CPI dataset."Troubleshooting Esankhyiki
Connection refused when starting the server locally
Ensure you are inside the virtual environment (`source venv/bin/activate`) and that FastMCP 3.3 was installed correctly. Re-run `pip install -r requirements.txt` if in doubt.
get_data returns no results even with valid filters
Always call list_datasets, then get_indicators, then get_metadata in order. The metadata call returns the exact filter key-value pairs that get_data expects. Using filter keys not returned by get_metadata will yield empty results.
OpenTelemetry errors appear in logs at startup
The server emits traces by default. Set OTEL_TRACES_EXPORTER=none to disable telemetry, or start a local OTLP collector at the endpoint configured in OTEL_EXPORTER_OTLP_ENDPOINT (default: http://localhost:4317).
Frequently Asked Questions about Esankhyiki
What is Esankhyiki?
Esankhyiki is a Model Context Protocol (MCP) server that this repository consists of source code for model context protocol (mcp) pilot project being undertaken by ministry of statistics and programme implementation and source code for the same is being shared under mit license. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Esankhyiki?
Follow the installation instructions on the Esankhyiki GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Esankhyiki?
Esankhyiki works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Esankhyiki free to use?
Yes, Esankhyiki is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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