Federal Reserve Economic Data MCP Server

The Federal Reserve Economic Data (FRED) MCP Server gives AI assistants instant, programmatic access to the full breadth of FRED’s 800 000+ time‑series database. Rather than requiring developers to manually fetch, parse, and cache data from the FRED API, this server exposes three high‑level tools that let a model query, browse, and retrieve series in a single, conversational turn. This solves the common problem of data latency and complexity when integrating large economic datasets into natural‑language workflows.

At its core, the server implements three intuitive tools: , , and . The browse tool lets a user drill down the FRED catalog by category, release, or source, returning concise summaries that are easy to interpret. The search tool accepts natural‑language queries and returns the most relevant series identifiers, while the series tool fetches the actual data points for a chosen series. Because each tool is exposed through MCP, an assistant can chain calls—searching for “US inflation rate” and then immediately retrieving the monthly series—all within a single prompt. This seamless integration eliminates the need for external scripting or manual API calls.

For developers, this server offers several tangible benefits. First, it abstracts away authentication and rate‑limiting concerns: a single API key supplied in the environment is all that’s required. Second, the tools are designed to return lightweight JSON payloads, making it straightforward for downstream processing or visualization. Third, the server’s Docker image and Smithery integration mean that it can be deployed locally or in a cloud environment with minimal friction, ensuring high availability for production assistants. Finally, the server’s open‑source license (AGPL v3) encourages community contributions and transparency.

Typical use cases span finance, economics research, and policy analysis. A data‑science assistant can quickly pull the latest GDP growth series to populate a dashboard, while an economic policy model might browse all employment‑related releases to identify new indicators. In educational settings, students can ask an assistant to “show me the trend of consumer price index” and receive a ready‑to‑plot series without leaving their learning platform. The server’s ability to surface metadata—such as release dates, units, and source notes—also supports rigorous data provenance tracking.

In summary, the FRED MCP Server transforms a vast, static repository of economic time series into an interactive, AI‑friendly resource. By providing well‑structured tools that handle browsing, searching, and retrieval in a single call, it empowers developers to embed authoritative macroeconomic data into conversational agents with minimal overhead and maximal flexibility.