fred-economic-intelligence-mcp
An MCP server that provides economic intelligence using FRED data, including series search, metadata, observations, comparisons, and a curated macroeconomic knowledge graph with GraphRAG, digital twin simulation, and explainability.
README
FRED Agentic Economic Intelligence MCP
An open-source, MCP-native economic intelligence server built on the Federal Reserve Economic Data API. The project combines deterministic FRED tools with a curated economic knowledge graph, graph-enhanced retrieval, explainability, an Economic Digital Twin, scenario simulation, and a LangGraph-compatible multi-agent workflow.
Capabilities
- FRED series search, metadata, observations, comparison, snapshots, and calendar-aware growth calculations
- MCP tools for economic graph queries and evidence retrieval
- Curated macroeconomic knowledge graph with transparent edges and confidence metadata
- Lightweight GraphRAG using graph traversal plus local evidence retrieval
- Economic Digital Twin with growth, inflation, labor, policy, housing, and financial-condition states
- Directional scenario simulation with propagation traces and explicit limitations
- Explainability through data provenance, domain attribution, graph paths, and citations
- Supervisor-led multi-agent workflow compatible with LangGraph
- Deterministic fallback mode that does not require an LLM API key
Important scope statement
This is a research-grade decision-support project. The digital twin and scenario engine are transparent directional models, not validated causal macroeconomic forecasts or investment advice.
Install
uv sync
Create a .env file locally:
FRED_API_KEY=your_fred_api_key
Never commit the .env file.
Run
uv run python -m fred_economic_intelligence_mcp.server
Or:
uv run fred-economic-intelligence-mcp
Main MCP tools
FRED data
health_checksearch_seriesget_series_metadataget_series_observationscompare_serieslatest_snapshotcalculate_growth_rate
Agentic intelligence
query_economic_graphretrieve_economic_evidencebuild_economic_digital_twinsimulate_economic_scenarioexplain_economic_signalrun_agent_workflow
Normalized signal convention
Digital-twin inputs use values from -1.0 to 1.0:
- positive: indicator increased or strengthened
- negative: indicator decreased or weakened
- zero: neutral or unavailable
The twin applies indicator-specific interpretation. For example, increases in unemployment or initial claims contribute negatively to labor-market strength.
Example:
{
"CPIAUCSL": 0.25,
"UNRATE": 0.40,
"PAYEMS": -0.10,
"HOUST": -0.30,
"T10Y2Y": -0.50
}
Scenario shocks
Supported MVP shocks:
policy_rate_changeunemployment_changeinflation_change
Example:
{
"policy_rate_change": -0.5
}
Test
uv run pytest -v --cov=fred_economic_intelligence_mcp --cov-report=term-missing
Open-source release
Before publishing, ensure .env, .venv, .coverage, caches, and Git internals are excluded from the archive and repository.
<!-- mcp-name: io.github.prithvi1029/fred-economic-intelligence -->
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