financeanalytics-data

US Fiscal Data

quantgeekdev

by quantgeekdev

Access and analyze US Treasury financial data, including 10 year treasury graphs, historical yields, and bond prices usi

Integrates with the US Treasury's Fiscal Data API to fetch, analyze, and generate reports on treasury statements and historical financial data.

github stars

17

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

No API key neededAuto-cached historical dataReal US Treasury API integration

best for

  • / Financial analysts tracking government cash flows
  • / Researchers studying federal treasury operations
  • / Developers building finance applications with treasury data

capabilities

  • / Fetch daily treasury statements for specific dates
  • / Access 30 days of historical treasury data
  • / Generate formatted treasury reports
  • / Query US government financial records
  • / Analyze treasury cash flows and balances

what it does

Connects to the US Treasury's Fiscal Data API to fetch daily treasury statements, access historical financial data, and generate formatted reports.

about

US Fiscal Data is a community-built MCP server published by quantgeekdev that provides AI assistants with tools and capabilities via the Model Context Protocol. Access and analyze US Treasury financial data, including 10 year treasury graphs, historical yields, and bond prices usi It is categorized under finance, analytics data.

how to install

You can install US Fiscal Data in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

US Fiscal Data is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Overview

The Fiscal Data MCP Server demonstrates a practical implementation of an MCP server that connects to the US Treasury's Fiscal Data API. It showcases:

  • Tools for fetching specific treasury statements
  • Resources for historical data access
  • Prompts for generating formatted reports

Quick Start

1. Install and Use with Claude Desktop

Add this configuration to your Claude Desktop config file:

MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "fiscal-data": {
      "command": "npx",
      "args": ["fiscal-data-mcp"]
    }
  }
}

2. Example Interactions

Once configured, you can interact with the server through Claude:

Human: Can you get the treasury statement for the 20th of September 2023?

Features

1. Daily Treasury Statements

Fetch treasury data for specific dates using the get_daily_treasury_statement tool:

// Example usage through Claude
Human: Get the treasury statement for 2024-03-01
Assistant: I'll fetch that information for you using the treasury statement tool.

2. Historical Data Resource

Access 30 days of historical treasury data through the resource system:

  • Automatically cached for 1 hour
  • Updates on demand
  • Provides formatted JSON data

3. Report Generation

Generate formatted treasury reports using the daily_treasury_report prompt:

// Example usage through Claude
Human: Generate a treasury report for 2024-03-01
Assistant: I'll use the daily treasury report prompt to create a formatted report...

FAQ

What is the US Fiscal Data MCP server?
US Fiscal Data is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for US Fiscal Data?
This profile displays 62 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.762 reviews
  • Fatima Jain· Dec 20, 2024

    Strong directory entry: US Fiscal Data surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Li Srinivasan· Dec 8, 2024

    US Fiscal Data reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Liam Gonzalez· Dec 8, 2024

    I recommend US Fiscal Data for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Dhruvi Jain· Dec 4, 2024

    I recommend US Fiscal Data for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Dev Agarwal· Nov 27, 2024

    US Fiscal Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Zara Harris· Nov 27, 2024

    Strong directory entry: US Fiscal Data surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Oshnikdeep· Nov 23, 2024

    Strong directory entry: US Fiscal Data surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Fatima Ghosh· Nov 11, 2024

    I recommend US Fiscal Data for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Hassan Kim· Oct 18, 2024

    Strong directory entry: US Fiscal Data surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Anika Rahman· Oct 18, 2024

    US Fiscal Data is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

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