analytics.usa.gov MCP Server
OfficialClick on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@analytics.usa.gov MCP Serverwhat are the top 10 pages today?"
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.
analytics.usa.gov MCP Server
⚠️ DISCLAIMER: This is a proof of concept and is not intended for production use.
Demo MCP Server for AI Community Of Practice
Overview
This project is a demonstration Model Context Protocol (MCP) server for analytics.usa.gov data, designed to showcase how LLMs can interact with government analytics APIs using the MCP standard. The codebase is structured to start simple and build up in capability:
single_report_tool: Provides basic access to a single analytics report at a time, ideal for simple queries and initial integration.
multiple_reports_tools: Adds support for fetching and handling multiple reports, allowing more complex queries and comparisons.
aggregation_tools: Enables aggregation of analytics data over time periods (week, month, year) and by various dimensions (such as source or agency), supporting more advanced analytics and summarization.
Each tool is registered with the MCP server and can be called by an LLM or other MCP-compatible client. The project is intended as a learning and experimentation platform for building and extending MCP-based analytics APIs.
Quick Start (Recommended)
Option 1: Install via uv
uv tool install git+https://github.com/GSA-TTS/usdc-arc-mcp-demo/This will install the MCP server as a CLI tool. You can then run:
usdc-arc-mcp-demoSimple way to connect to Claude
Get the installed tool path:
which usdc-arc-mcp-demoCopy the path into Claude MCP config:
{ "mcpServers": { "usdc-arc-mcp-demo": { "command": "/path/to/usdc-arc-mcp-demo", "args": [], "env": { "DAP_API_KEY": "your-api-key" } } } }
Development Setup
Option 2: Using Hatch or uv
Using Hatch
Install Hatch:
pip install hatchCreate a virtual environment and install dependencies:
hatch env createRun the server:
hatch run usdc-arc-mcp-demoOr:
hatch shell
usdc-arc-mcp-demo
#### Using uv
1. Install [uv](https://github.com/astral-sh/uv):
```sh
pip install uvInstall dependencies:
uv pip install -r requirements.txtOr, for PEP 621 projects:
uv pip install -e .Run the server:
usdc-arc-mcp-demo
Configuration
Set your Regulations.gov API key in a .env file:
DAP_API_KEY=your_api_key_hereProject Structure
src/usdc_arc_mcp_demo/– Main package codetest/– Tests
Linting
This project uses ruff for linting and code style checks.
To lint your code, run:
hatch run ruff check src/Or:
hatch shell
ruff check src/Resources
This server cannot be installed
Resources
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