AI for Economists

v1.0.0Knowledge & Memorystable

A curated list of AI tools, libraries, and resources for economics research, teaching, and policy analysis. Maintained by the OpenEcon team.

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What is AI for Economists?

AI for Economists is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to curated list of ai tools, libraries, and resources for economics research, teaching, and policy analysis. maintained by the openecon team.

A curated list of AI tools, libraries, and resources for economics research, teaching, and policy analysis. Maintained by the OpenEcon team.

This server falls under the Knowledge & Memory category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • A curated list of AI tools, libraries, and resources for eco

Use Cases

Economics research tools
Econometrics and causal inference
Policy analysis resources
hanlulong

Maintainer

LicenseCC0-1.0
Languagetypescript
Versionv1.0.0
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux

Installation

Manual Installation

npx awesome-ai-for-economists

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use AI for Economists

Awesome AI for Economists is a curated directory of AI tools, libraries, datasets, and resources specifically assembled for economics researchers, educators, and policy analysts. Maintained by the OpenEcon team, it catalogs 150+ tools spanning economic data access (FRED, World Bank, IMF, Eurostat), causal inference libraries, forecasting models, literature discovery agents, academic writing tools, and policy analysis platforms. Rather than being an MCP server itself, it serves as a reference guide for economists building AI-augmented research workflows, with special coverage of MCP servers that connect to economic databases and the OpenEcon natural-language query interface for 330,000+ economic indicators.

Prerequisites

  • A GitHub account to browse, star, and contribute to the repository
  • Familiarity with Python or R for most of the listed tools and libraries
  • An MCP-compatible AI client (Claude Desktop, Cursor, etc.) if you want to use the MCP-based tools listed in the directory
  • API access to economic data sources (FRED API key, World Bank, etc.) for data-access tools
1

Browse the curated list on GitHub

Visit the repository to explore categorized AI tools for economics. The README is organized by use case, making it easy to find tools for your specific research domain.

# Repository: https://github.com/hanlulong/awesome-ai-for-economists
2

Identify the tools relevant to your workflow

The list covers data access (FRED, World Bank, IMF), causal inference (double ML, synthetic control, DiD), forecasting (time series foundation models, DSGE solvers), literature tools, and policy analysis platforms. Identify which category matches your research need.

3

Set up OpenEcon for natural-language economic data queries

OpenEcon, highlighted by the maintainers, provides natural-language access to 330,000+ economic indicators. It has an MCP server available for integration with AI clients.

# Install the OpenEcon MCP server (check their repo for latest command)
npx -y openecon-mcp

# Or follow the OpenEcon setup guide at their repository
4

Install a causal inference library for econometrics

The list features Python libraries for causal inference. EconML from Microsoft is a commonly referenced option for double machine learning and heterogeneous treatment effects.

pip install econml

# Example: estimate a causal effect with DoubleML
# from econml.dml import DML
5

Contribute or follow updates

Star the repository and watch for updates. The maintainers actively add new tools, including upcoming conference resources (NBER AI meetings 2025-2026) and newly released AI-for-economics research.

AI for Economists Examples

Client configuration

If using an MCP server from the listed tools (e.g., a FRED data MCP server), configure your client as shown. Replace with the specific package name of the tool you choose from the list.

{
  "mcpServers": {
    "economics-data": {
      "command": "npx",
      "args": ["-y", "fred-mcp-server"],
      "env": {
        "FRED_API_KEY": "your_fred_api_key_here"
      }
    }
  }
}

Prompts to try

When using AI tools or MCP servers from this curated list with an AI assistant, prompts like these are effective for economics research.

- "Fetch US GDP growth data from FRED for the past 20 years and plot the trend"
- "Help me implement a difference-in-differences estimator for this policy evaluation dataset"
- "Search for recent papers on AI applications in macroeconomic forecasting"
- "Explain the synthetic control method and show me Python code to implement it"
- "What are the best open-source tools for labor market analysis with satellite data?"

Troubleshooting AI for Economists

A tool from the list is no longer maintained or the link is broken

The repository is community-maintained and some linked projects may become inactive over time. Check the GitHub repository's Issues or Discussions to report broken links. Search for forks or successors of the project on GitHub.

FRED API requests fail with rate limit or authentication errors

FRED requires a free API key from fred.stlouisfed.org/docs/api/api_key.html. Set it as FRED_API_KEY in your environment. The free tier allows 120 requests per 60 seconds — add delays between bulk requests if you hit rate limits.

EconML or other Python packages have dependency conflicts

Use a dedicated virtual environment for economics tools: `python -m venv econ-env && source econ-env/bin/activate`. Many econometrics packages (EconML, linearmodels, statsmodels) require compatible versions of NumPy and SciPy — install them together to let pip resolve compatible versions.

Frequently Asked Questions about AI for Economists

What is AI for Economists?

AI for Economists is a Model Context Protocol (MCP) server that curated list of ai tools, libraries, and resources for economics research, teaching, and policy analysis. maintained by the openecon team. It connects AI assistants to external tools and data sources through a standardized interface.

How do I install AI for Economists?

Follow the installation instructions on the AI for Economists GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.

Which AI clients work with AI for Economists?

AI for Economists works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is AI for Economists free to use?

Yes, AI for Economists is open source and available under the CC0-1.0 license. You can use it freely in both personal and commercial projects.

Browse More Knowledge & Memory MCP Servers

Explore all knowledge & memory servers available in the MCPgee directory. Each server includes setup guides for Claude, Cursor, and VS Code.

Quick Config Preview

{ "mcpServers": { "awesome-ai-for-economists": { "command": "npx", "args": ["-y", "awesome-ai-for-economists"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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