Use FactIQ when you want an agent citing official statistics instead of recalling them. It replaces a stack of separate government APIs with one connection, and its earnings tools return structured claims rather than raw transcripts. The plugin is open source under MIT and listed in the Claude directory; company data below $1B market cap is not covered.
FactIQ is an MCP plugin from Defog that gives AI agents read-only access to economic and financial data: 37 official sources, 1,464 datasets and 103M time series. It works in Claude, ChatGPT, Claude Code and Codex through one OAuth sign-in, and exposes tools including run_sql, get_series and search_earnings_transcripts.
Maker: Defog · Protocol: MCP · Auth: oauth
Compatible agents: Claude (web, desktop, Cowork), ChatGPT (web and desktop), Claude Code, Codex CLI, any MCP client
Required runtime: Claude, ChatGPT, Claude Code or Codex CLI, A free FactIQ account
About FactIQ
Defog built FactIQ to turn an AI agent into a finance and economy analyst, inside Claude, ChatGPT, Claude Code or Codex. Rather than shipping a chat product, it exposes a warehouse of official statistics through named tools the agent calls directly, spanning government releases, market data, earnings calls and satellite signals. The plugin repository is MIT licensed, and FactIQ is listed in the official Claude directory.
It connects over MCP with HTTP transport to a single endpoint, api.factiq.com/mcp, and authenticates through one OAuth sign-in rather than an API key pasted into a config file. The agent works in two phases: discovery tools locate the right dataset and series, then fetch tools pull the numbers, including read-only SQL against schemas such as the Bureau of Labor Statistics, Census, BEA and SEC EDGAR. Some schemas are deliberately gated, so a query against the transcripts schema returns 403 rather than raw text.
The natural user is someone already working in Claude, ChatGPT, Claude Code or Codex who wants sourced numbers instead of a model's recollection of them. It suits macro research, trade flows by HS commodity, earnings-call analysis and satellite-derived signals such as nighttime lights, shipping activity and reservoir levels. It is a poor fit if you want a hosted dashboard, because there is no UI: the output is whatever the agent renders, from a terminal preview to a local HTML chart.
Access is tiered: the free plan covers global macro, trade, markets and US company financials for listed companies above $1B market cap, and the Research ($250 per month) and Institutional ($1,500 per month) plans buy history depth and breadth rather than extra software. The vendor catalog lists 37 sources, 1,464 datasets and 103M series. Coverage runs deepest across the United States and Asia, and company-level data thins out below the largest listed names.
Key Features
- Two-phase tool design: Splits discovery from retrieval so the agent locates a dataset and series first, then fetches, which cuts the wrong-series errors that plague single-endpoint data APIs.
- Read-only SQL over official schemas: Exposes named schemas including BLS, Census, BEA, EIA and SEC EDGAR, so an agent can compute a derived metric rather than fetch a single prepared number.
- Structured earnings claims: Decomposes calls into a claim graph and separates management statements from analyst hypotheses, so an agent cannot attribute an analyst's framing to the company.
- Satellite-derived series: Carries fire detections, atmospheric signals, vegetation indices and night-time light series for cases where official statistics lag or cannot be trusted.
- One OAuth connection: Authorises through a single browser sign-in from the client rather than distributing an API key into a local config file.
- Gated schemas fail loudly: Admin-only schemas are absent from your catalog and return 403 on access, so an agent gets an error instead of a silently partial answer.
Use Cases
- Pin an earnings claim to the exact quarter: Checks live transcript coverage first, pins the fiscal quarter, then pulls bounded management-claim and Q&A-pressure rows for that same call instead of guessing from memory.
- Trace a trade flow by commodity: Queries monthly imports and exports by HS commodity and partner country from US Census and China customs data, without mixing incompatible preliminary and per-HS datasets.
- Read an economy from orbit: Pulls satellite-derived series such as nighttime lights, shipping and port activity, reservoir levels and crop fires when official statistics lag or are unreliable.
- Build a sourced chart in the terminal: Runs the analysis and returns a terminal preview, report JSON or a bespoke local HTML visualisation, with every figure traceable to its source series.
Install
/plugin marketplace add defog-ai/factiq-plugin
Requirements
- A free FactIQ account at factiq.com (email, Google or passkey)
- Claude app: a paid Claude plan, then connect from claude.ai/directory/factiq
- Claude Code: add the marketplace with /plugin marketplace add defog-ai/factiq-plugin, install factiq, run /reload-plugins
- Authorise the MCP server: run /mcp, select factiq, choose Authenticate
Actions
search_datasets
Finds which datasets in the warehouse cover a topic before any query is written.
/factiq:ask What US datasets cover job openings?query(string) — required: Free-text description of the topic to locate.
get_data_catalog
Returns the live, authoritative catalog of datasets available to your account, including per-dataset descriptions.
/factiq:ask Show me the full data catalogrun_sql
Executes read-only SQL against the warehouse schemas such as bls, census, bea, eia and sec.
-- read-only; the gated transcripts schema is never queryable this way
SELECT * FROM bls WHERE series_id = 'LNS14000000' ORDER BY period DESC LIMIT 12;sql(string) — required: A read-only SQL statement against a permitted schema.
get_series
Fetches the observations for a specific time series once its identifier is known.
/factiq:ask Get the last 5 years of US unemployment series LNS14000000series(string) — required: Series identifier, for example LNS14000000 for US unemployment.
search_earnings_transcripts
Retrieves structured claims and Q&A pressure points from earnings calls; it never returns a raw transcript.
/factiq:ask What did Micron management say on its latest call?search_target(string) — required: One of claims, pressure_points, disclosure_profile or coverage.query(string): Free-text theme to search within the selected target.company_filter(string): Restrict to a company; disclosure_profile takes the first ticker only.quarter_filter(string): Pin the fiscal quarter; ignored by disclosure_profile and coverage.claim_family(string): Group of related claims to filter on.limit(integer): Maximum rows returned.
search_media_appearances
Searches precomputed claims and passage cards from executive podcasts, TV interviews and conference appearances.
/factiq:ask How has this CEO talked about pricing in interviews this year?search_target(string) — required: One of search, claims, passages, pressure_points, appearances or coverage.query(string): Free-text theme; retrieval is strict lexical, then loose, then trigram.
How to Invoke
Exposed as MCP tools over HTTP that the agent calls by name once the plugin is installed and the server authorised. Discovery tools are search_datasets, describe_dataset, search_series and get_data_catalog; fetch tools are run_sql (read-only), get_series, get_market_data, search_earnings_transcripts, search_media_appearances and search_news. A /factiq:ask slash command wraps the whole workflow, and any economic question in a normal session auto-invokes the bundled skill.
Pricing
Free tier covers basic global macro and company data. Research is $250 per month and adds five years of history for S&P 500 companies. Institutional is $1,500 per month with 10 or more years of history and the broadest coverage.
The plugin itself is MIT licensed and free; the subscription buys data depth, not software.
Strengths
- Covers 37 official sources (vendor catalog, 2026-10-21) behind one connection, replacing a pile of separate government APIs each with its own auth and format.
- Separates management speech from analyst framing in earnings data, a distinction most transcript tools collapse and which changes what you can honestly quote.
- MIT licensed plugin with a free account tier, so the integration can be evaluated end to end before any spend.
Weaknesses
- Company financials cover US-listed companies above $1B market cap, so micro-cap and non-US company research falls outside the free plan.
- The Claude app route requires a paid Claude plan, on top of the FactIQ account.
- No hosted interface at all: output is whatever the agent in front of it renders.
Frequently Asked Questions
How much does FactIQ cost in 2026?
A free plan covers global macro, trade, markets data and US company financials above $1B market cap. Research is $250 per month (listed as a waitlist on the pricing page) and the top Institutional plan is $1,500 per month. The plugin code is MIT licensed, so you pay for data depth, not software.
How do I install and set up FactIQ?
In the Claude app, open the FactIQ listing in the Claude directory, click Connect and finish the FactIQ sign-in; this needs a paid Claude plan. In Claude Code, add the marketplace repository, install the factiq plugin, run /reload-plugins, then run /mcp, select factiq and choose Authenticate. Codex users add the same marketplace through the codex plugin commands.
Which agents and LLMs support FactIQ?
The vendor lists Claude (web, desktop and Cowork), ChatGPT (web and desktop), Claude Code and Codex CLI as supported surfaces, and the MCP server speaks HTTP transport so other MCP-capable clients can register it. Once registered, the agent calls the tools by name without further configuration.
What are the best alternatives to FactIQ?
The official source APIs, such as FRED for US macro and SEC EDGAR for filings, are free and authoritative but leave you to handle auth, formats and joins yourself. Commercial terminals cover far more of the market with far deeper history at a different order of price. Pick FactIQ when you specifically want an agent to do the querying.
How does FactIQ compare to querying FRED directly in 2026?
FRED is free, stable and vastly better known, but it is one source with one shape and no earnings, satellite or market data. FactIQ puts many official sources behind a single OAuth connection and adds structured earnings claims and satellite series that FRED does not carry. If your work is purely US macro, FRED is enough; if it crosses sources, FactIQ saves the plumbing.
Hokai guides that mention FactIQ
- Best MCP Servers in 2026, by Job: Browsing, Search, App Actions, Sales Data and Code: The best MCP servers in 2026 by job: browsing, search, app actions, sales data and code. Prices read 4 Nov 2026, how each signs in, and what data it sees.
