FRED MCP Server Integration

What does “FRED” MCP Server do?

The Federal Reserve Economic Data (FRED) MCP Server is an open-source implementation of the Model Context Protocol (MCP) that allows AI assistants and development tools to connect directly to the vast economic and financial datasets provided by the Federal Reserve Bank of St. Louis’ FRED API. By acting as a bridge between AI clients and external data, the FRED MCP Server enables powerful workflows such as querying time-series data, accessing economic indicators, and retrieving historical financial information. This integration empowers developers and AI agents to automate research, provide data-driven insights, and support analytical tasks using up-to-date federal economic data—all within the context of their applications or LLM-based agents.

List of Prompts

No prompt templates are mentioned in the repository or its documentation.

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List of Resources

• FRED Economic Data Series
  Provides access to over 800,000 US and international time-series economic data series from the Federal Reserve Bank of St. Louis.
• Economic Indicators
  Exposes commonly referenced economic indicators (GDP, CPI, unemployment rates, etc.) as structured data resources.
• Historical Financial Data
  Enables retrieval of historical prices, interest rates, and other financial series for longitudinal analysis.
• Metadata for Series
  Supplies metadata (source, frequency, units, etc.) for each data series, allowing for better contextualization and filtering.

List of Tools

• query_series
  Enables querying specific FRED data series by their ID, returning the latest or historical data points for analysis.
• search_series
  Allows searching for FRED series based on keywords, categories, or metadata filters, helping users discover relevant datasets.
• get_series_info
  Retrieves metadata and descriptive information about a given FRED series, such as its description, frequency, and units.

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Use Cases of this MCP Server

• Economic Research Automation
  Automate the retrieval of up-to-date economic indicators and time-series for use in economic analysis and reporting.
• Financial Application Integration
  Integrate FRED data into dashboards, trading platforms, or analytics tools to provide real-time economic context.
• AI-Driven Data Analysis
  Enable LLMs or AI agents to answer questions or generate reports using authoritative economic data pulled directly from FRED.
• Academic and Policy Studies
  Streamline the process of gathering historical data for research, econometric studies, and policy analysis.
• Data Enrichment for Visualizations
  Power data visualizations and business intelligence reports with reliable, up-to-date macroeconomic data.

How to set it up

Windsurf

1. Ensure Node.js is installed on your machine.
2. Locate the Windsurf configuration file (usually windsurf.config.json).
3. Add the FRED MCP Server to your mcpServers section with the following JSON:

   {
     "fred-mcp-server": {
       "command": "npx",
       "args": ["@stefanoamorelli/fred-mcp-server@latest"]
     }
   }
   

4. Save the file and restart Windsurf.
5. Verify the setup by checking that the FRED MCP Server is listed as an available tool.

Claude

1. Install Node.js if not already present.
2. Open the Claude Desktop or Claude configuration file.
3. Add this entry to your MCP servers section:

   {
     "fred-mcp-server": {
       "command": "npx",
       "args": ["@stefanoamorelli/fred-mcp-server@latest"]
     }
   }
   

4. Save changes and restart Claude.
5. Confirm that the server is active in the Claude UI.

Cursor

1. Make sure Node.js is installed.
2. Open Cursor’s configuration panel or config file.
3. Insert the following under the mcpServers object:

   {
     "fred-mcp-server": {
       "command": "npx",
       "args": ["@stefanoamorelli/fred-mcp-server@latest"]
     }
   }
   

4. Save and relaunch Cursor.
5. Verify FRED MCP is available as a tool.

Cline

1. Install Node.js.
2. Edit Cline’s main config file to include:

   {
     "fred-mcp-server": {
       "command": "npx",
       "args": ["@stefanoamorelli/fred-mcp-server@latest"]
     }
   }
   

3. Save and restart Cline.
4. Check that the server appears in the MCP tool list.

Securing API Keys

Store your FRED API key as an environment variable to keep it secure:

{
  "fred-mcp-server": {
    "command": "npx",
    "args": ["@stefanoamorelli/fred-mcp-server@latest"],
    "env": {
      "FRED_API_KEY": "your_fred_api_key_here"
    },
    "inputs": {}
  }
}

Replace "your_fred_api_key_here" with your actual API key. This prevents hardcoding sensitive information in configuration files.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "fred-mcp-server": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “fred-mcp-server” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the tables, the FRED MCP Server provides core MCP features such as tools and resources, but lacks prompt templates and explicit support for advanced features like sampling. The documentation is clear, installation is straightforward, and API key security is addressed. Overall, it’s a solid and practical MCP server for economic data integration.

MCP Score