"A server for obtaining economic data and reports from reputable sources like FRED and CBOE" matching MCP tools:

• fred_macro_series

  CIPHER x402 — Paid Solana & Crypto Tools

  Fetch a Federal Reserve Economic Data (FRED) series by ID — e.g. 'DGS10' (10Y yield), 'WALCL' (Fed balance sheet), 'T10Y2Y' (yield curve). Returns cleaned latest observations. Priced at $0.005 USDC on Base (x402). Pass a signed x402 v2 authorization as the '_payment' argument to unlock the paid response. Without it, the tool returns the 402 accept-list for your wallet to sign.

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• example_plans

  PlanExe

  Returns a curated list of example plans with download links for reports and zip bundles. Use this to preview what PlanExe output looks like before creating your own plan. Especially useful when the user asks what the output looks like before committing to a plan. No API key required.

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• list_prebuilds

  mcp-server

  Lists pre-configured reports (prebuilds) available for a connector. **What is a prebuild?** A prebuild is a standardized report maintained by Quanti for a given connector (e.g., Campaign Stats for Google Ads). It defines the BigQuery table structure (columns, types, metrics) and the associated API query. **When to use this tool:** - When the user asks "what reports are available for [connector]?" - When the user doesn't know which data or metrics exist for a connector - BEFORE get_schema_context, to explore available reports for a connector - To understand the data structure before writing SQL **Difference with get_schema_context:** - list_prebuilds → discover which reports/tables EXIST for a connector (catalog) - get_schema_context → get the actual BigQuery schema for the client project (effective data) **Response format:** Returns a JSON with for each prebuild: its ID, name, description, BigQuery table name, and the list of fields (name, type, description, is_metric). Fields marked is_metric=true are aggregatable metrics (impressions, clicks, cost...), others are dimensions (date, campaign_name...). **SKU examples**: googleads, meta, tiktok, tiktok-organic, amazon-ads, amazon-dsp, piano, shopify-v2, microsoftads, prestashop-api, mailchimp, kwanko

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• GetFredSeriesData

  Fintel Discovery — Financial Intelligence for AI Agents

  Fetch time-series observation data from FRED for a specific economic series. Returns date + value pairs with series metadata (title, units, frequency). Use SearchFredSeries first if you don't know the series ID. Use this tool when: - You need historical macro data (rates, inflation, GDP, unemployment) - You want to provide macro context alongside advisor or fund data - You are comparing economic conditions across time periods - You need the current value of a key economic indicator Pass observation_start / observation_end to limit the date range. Pass frequency to aggregate (e.g. 'm' for monthly, 'q' for quarterly). Requires FRED_API_KEY environment variable (free at fred.stlouisfed.org). Source: Federal Reserve Bank of St. Louis FRED API.

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• ask_us_capital_markets

  AskNeedl

  Query SEC filings and financial documents from US capital markets and exchanges. This tool searches through 10-K annual reports, 10-Q quarterly reports, 8-K current reports, proxy statements, earnings call transcripts, investor presentations, and other SEC-mandated filings from US companies. Use for questions about US company financials, executive compensation, business operations, or regulatory disclosures. Limited to official SEC filings and related documents only.

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• list_holdings_reports

  Pensiata - Bulgarian Pension Fund Analytics

  List available markdown holdings reports for Bulgarian pension funds. Reports contain detailed portfolio holdings data extracted from official PDF filings and converted to structured markdown with metadata (allocation %, exposure, top holdings). Use this tool to discover what reports are available before loading specific ones with `read_holdings_report`. Filter by manager, fund type, or date range.

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• tf_economic_data

  terminalfeed

  Fetches latest FRED economic indicators: Fed funds rate, CPI, unemployment rate, GDP growth. Cache TTL 1h. Use when the agent needs current US macro indicators. For deeper macro (treasury yields, forex, commodities, indices) use tf_premium_macro.

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• ga4_get_account

  Google Analytics (unofficial)

  Lists all GA accounts and GA4 properties the user can access, including web and app data streams. Use this to discover propertyId, appStreamId, measurementId, or firebaseAppId values for reports.

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• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or due_diligence_report instead. Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• get_series_observations

  FRED Economic Data

  Get time series observations (data points) for a FRED series. Returns the actual data values for an economic indicator over time. Use search_series first to find the series_id, or use well-known IDs like UNRATE, GDP, CPIAUCSL, FEDFUNDS, MORTGAGE30US. For state unemployment, use state abbreviation + 'UR' (e.g. WAUR for Washington, CAUR for California). Results are sorted most-recent-first. For long series (e.g. daily data since 1954), use start_date/end_date to narrow the window or increase the limit up to 10000. Args: series_id: FRED series identifier (e.g. 'UNRATE', 'GDP', 'CPIAUCSL'). start_date: Optional start date in YYYY-MM-DD format (e.g. '2020-01-01'). end_date: Optional end date in YYYY-MM-DD format (e.g. '2024-12-31'). limit: Maximum observations to return (default 1000, max 10000).

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• datagovmy_get_transit_stops

  hithereiamaliff-mcp-datagovmy

  Get transit stops from GTFS data. IMPORTANT: For transit stop queries like "Show me bus stops for Rapid Penang", use this tool directly with the provider name. The tool supports common names like "rapid penang", "rapid kuantan", "ktmb", or "mybas johor" which will be automatically mapped to the correct provider and category. No need to use list_transport_agencies first.

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• get_signal_narratives

  SupplyMaven MCP Server

  Get plain-language explanations of active predictive signals. Each narrative explains the mechanism behind a signal — why the predictor leads the target, what economic logic connects them, and what the current reading implies. Designed for non-quantitative users who want to understand the 'why' behind each signal without reading F-statistics. Returns trigger context, predictor value, direction, and a narrative paragraph suitable for reports and briefings.

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• list_data_sources

  Indicate

  Step 2 — List data sources available within a tenant. (In the Indicate system a data source is called a 'data product'.) Examples: Google Analytics, Facebook Ads, vioma, Booking.com. Returns each data source's 'id', 'displayName', and 'semantic_context_id'. → Pass the chosen 'id' as 'data_source_id' and 'semantic_context_id' to list_metrics.

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• search_series

  FRED Economic Data

  Search for FRED economic data series by keyword. Use this to find series IDs for economic indicators. For example, search 'unemployment rate' to find UNRATE, or 'gross domestic product' to find GDP. Returns series metadata including ID, title, frequency, units, and date range. Common series: UNRATE (unemployment), GDP (gross domestic product), CPIAUCSL (consumer price index), FEDFUNDS (federal funds rate), MORTGAGE30US (30-year mortgage rate), MEHOINUSA672N (median household income). Args: search_text: Keywords to search for (e.g. 'unemployment rate', 'GDP', 'inflation'). limit: Maximum number of results to return (default 10, max 1000).

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• analyze_record

  Senzing

  Get the Senzing JSON analyzer script with commands to validate and analyze mapped data files client-side. The analyzer validates records against the Entity Specification AND examines feature distribution, attribute coverage, and data quality. Returns the Python script (no dependencies) with instructions. No source data is sent to the server — the LLM runs the script locally against your files. REQUIRED parameter: `workspace_dir` (a writable directory where the script and any reports are saved). Do NOT assume /tmp exists (some environments like Kiro do not provide it). Typical values: Linux `/tmp` or `~/sz-workspace`; macOS `~/sz-workspace`; Kiro/sandboxed an explicit path under your home.

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• get_signal_narratives

  supply-chain-intelligence

  Get plain-language explanations of active predictive signals. Each narrative explains the mechanism behind a signal — why the predictor leads the target, what economic logic connects them, and what the current reading implies. Designed for non-quantitative users who want to understand the 'why' behind each signal without reading F-statistics. Returns trigger context, predictor value, direction, and a narrative paragraph suitable for reports and briefings.

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• zone_profile

  ENTIA Entity Verification MCP

  Get the complete socioeconomic profile for any Spanish postal code — income, unemployment, population, and business density. Use when a user asks 'what's the economic level of this area?', 'is this a good zone to open a business?', 'what's the average income in 28001?', 'how many businesses are in this postal code?', or needs economic context for real estate, investment, or market analysis. Covers all 11,241 Spanish postal codes with data from 4 official sources: - AEAT (Agencia Tributaria): gross/average annual income, net monthly salary, tax declarations, social security contributions - SEPE (Servicio Publico de Empleo): registered unemployment, unemployment-to-declarations ratio - INE (Padron Municipal 2025): population by municipality and sex - INE (DIRCE): business count by CNAE sector ENTIA computes: Economic Capacity Index ICE (1-10) and Economic Segment (BAJO / MEDIO / ALTO / PREMIUM). This is the most granular open economic data available for Spain at postal code level.

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• get_credit_spread_benchmark

  Stratalize Finance Intelligence

  Live investment grade and high yield credit spread benchmarks from FRED ICE BofA indices — OAS by rating tier, TED spread, 2s10s Treasury spread, and distress signal. Updates daily. For credit analysts and fixed income PMs. Live source. Returns HTTP 503 (no charge) if upstream source unavailable for >50% of fields. | x402 SLA: $0.10 USDC per call. Returns HTTP 503 (no charge) when upstream data sources unavailable. data_source field discloses provenance (fred_api/fred_csv/fred_mixed).

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• SearchFredSeries

  Fintel Discovery — Financial Intelligence for AI Agents

  Search the Federal Reserve Bank of St. Louis FRED database for economic data series by keyword. Returns series ID, title, frequency, units, seasonal adjustment, and date range. Use this tool when: - You need to find the right FRED series ID before fetching data - You want to discover what macro data is available for a topic - You are looking for interest rates, inflation, GDP, unemployment, or money supply series to provide macro context for financial analysis Common series IDs (use GetFredSeriesData after finding one): - DGS10: 10-Year Treasury Yield - CPIAUCSL: Consumer Price Index (CPI-U) - UNRATE: Unemployment Rate - GDP: Gross Domestic Product - FEDFUNDS: Federal Funds Rate - M2SL: M2 Money Supply Requires FRED_API_KEY environment variable (free at fred.stlouisfed.org). Source: Federal Reserve Bank of St. Louis FRED API.

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• contacts-create_research

  Saber

  Start a contact research job — AI gathers insights from LinkedIn and other sources asynchronously; use contacts.get_research to poll for results

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