Because the same server exposes the raw Census, BLS, FRED and World Bank calls underneath the TAM and forecast tools, an estimate can be traced back to the series it rests on — and data_validation exists to say how complete that basis actually was, which is unusual in a category built on confident round numbers. Two practical notes: the scenario and confidence-interval outputs are worth more than the headline figure when the estimate goes into a deck, and each data source that needs an API key stays silent until it has one.
A market-research server in two layers: direct access to eight economic and financial data sources, and analysis tools that draw on them to estimate market size, addressable market and growth. It also ships business-analysis prompt templates for funding and strategy work.
- Raw source access, one tool per API: alphaVantage_getCompanyOverview and alphaVantage_searchSymbols, bls_getSeriesData, census_fetchIndustryData and census_fetchMarketSize, fred_getSeriesObservations, imf_getDataset and imf_getLatestObservation, nasdaq_getDatasetTimeSeries and nasdaq_getLatestDatasetValue, oecd_getDataset and oecd_getLatestObservation, worldBank_getIndicatorData
- tam_calculator projects market value over several years from your inputs; tam_analysis adds scenario analysis and alternative methodologies
- sam_calculator derives Serviceable Addressable Market and Serviceable Obtainable Market from a TAM figure
- market_size and market_size_calculator estimate current size with historical trend and growth projections, drawing across sources
- market_forecasting produces forecasts with scenarios and confidence intervals rather than a single line
- market_segments breaks a market into hierarchical segments with trends, and market_comparison puts several industries side by side across metrics
- industry_search, industry_analysis and industry_data cover finding the right industry and pulling its trends, key players and ESG metrics
- company_financials_retriever fetches financial statements for a public company
- market_opportunities surfaces emerging opportunities with growth potential and risk, and data_validation grades the quality and completeness of the data behind an estimate
- generic_data_query reaches the underlying data services directly when the shaped tools do not fit
Node.js 20.x or later. API keys for the data sources are optional — the server has defaults that work without them — but the sources that require one, such as ALPHA_VANTAGE_API_KEY and FRED_API_KEY, only answer once their key is set. It is installed from the repository: clone, npm install, npm run build, then npm run start:http for HTTP or npm run start:stdio for stdio; a Docker image is the other route. Configuration goes in a .env file copied from .env.example.
One command plus a key — npx -y @gvaibhav/tam-mcp-server, then supply credentials