Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Official economic statistics, company filings, earnings calls and market data, with sources cited.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
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Works in Claude on the web, desktop and mobile:
https://api.factiq.com/mcpRun this in your terminal
claude mcp add --transport http factiq https://api.factiq.com/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"factiq": {
"url": "https://api.factiq.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"factiq": {
"type": "http",
"url": "https://api.factiq.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://api.factiq.com/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026
The registry name was verified against the domain factiq.com (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 21 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Spec Driven Development, Remote Desktop Commander, dotnet-mcp
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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Turn your agent into a finance and economy analyst. This plugin for Claude (web, desktop, and Cowork), ChatGPT (web and desktop), Claude Code, and Codex gives the agent direct access to FactIQ's warehouse of official statistics — SEC filings, US, China, India, Korea, IMF, World Bank, and more — plus live market data, earnings-call transcripts, executive media appearances, central-bank speeches, minutes, and statements, and satellite-derived data (fire detections, air-quality activity signals, rainfall, nighttime lights, shipping and port activity, reservoir levels). The agent discovers series, runs read-only SQL, computes derived metrics, and returns a sourced answer, chart JSON, or report JSON.
No codebase or hosted database is required — only a free FactIQ account.
Want to contribute? The highest-leverage addition is a domain playbook that teaches the agent a whole class of questions — see Contributing.
FactIQ supports four client paths. The website guides are canonical for app setup and plan requirements, which can change faster than this repository:
| Client | Supported surfaces | Setup guide |
|---|---|---|
| Claude | Web, desktop, and Cowork | factiq.com/claude |
| ChatGPT | Web and desktop app (including Codex in the app) | factiq.com/chatgpt |
| Claude Code | CLI, desktop app, and IDE extensions | factiq.com/claude-code |
| Codex | CLI | factiq.com/codex |
FactIQ is listed in the official Claude directory. Open claude.ai/directory/factiq while signed in to Claude, click Connect, complete the FactIQ sign-in, and start a new chat. You can also find it under Customize → Plugins by searching for FactIQ. For the best experience, use Cowork. The plugin requires a paid Claude plan.
To install from this repository instead, open Customize → Plugins, add defog-ai/factiq-plugin as a personal marketplace, install FactIQ, and complete the browser sign-in. Organizations that approve plugins centrally can mirror this repository as a private marketplace. See the Claude guide for the current steps and organization-policy notes.
FactIQ is listed in the official ChatGPT plugin directory. Open the FactIQ listing while signed in to ChatGPT, click Install plugin, complete the FactIQ sign-in, and start a new chat. Type @FactIQ to select it explicitly. This works on ChatGPT Plus, Pro, Business, Enterprise, and Edu plans, on the web and in the desktop app. On Business, Enterprise, and Edu, a workspace admin may need to allow FactIQ first. The install also covers Codex inside the ChatGPT app; Codex CLI uses the separate setup below.
To install from this repository instead, open Plugins in the ChatGPT desktop app, add defog-ai/factiq-plugin as a marketplace, and install FactIQ from the Personal tab. This path works only in the desktop app, on a Pro, Business, Enterprise, or Edu plan. See the ChatGPT guide for the current plan matrix and troubleshooting steps.
/plugin marketplace add defog-ai/factiq-plugin
/plugin install factiq@factiq /reload-plugins
Run `/reload-plugins` after installing so Claude Code picks up the new skill and MCP server in the current session (otherwise they only appear the next time you start Claude Code).
This adds the FactIQ skill (Claude invokes it automatically for economic/financial data questions) and the bundled FactIQ MCP server. Claude Code namespaces skills installed from plugins, so its manual invocation is:
| Command | Purpose |
|---|---|
/factiq:factiq | Run an analysis and get a sourced answer, chart JSON, or report |
Finally, authenticate the MCP server:
Enable auto-updates
So you always get the latest skill and MCP tools without reinstalling, turn on auto-updates for the marketplace:
Claude Code will then refresh the plugin automatically whenever this marketplace changes.
codex plugin marketplace add defog-ai/factiq-plugin
codex plugin add factiq@factiq
Then authorize the MCP server:
codex mcp login factiq
Complete the browser sign-in (the same FactIQ login: email, Google, or passkey). Start a new Codex thread after installation; the skill auto-invokes for economic/financial data questions.
Update an existing Codex install
To update after this marketplace changes, refresh the configured marketplace name (factiq), then reinstall the plugin:
codex plugin marketplace upgrade factiq
codex plugin add factiq@factiq
</details>
Alternative: install as a standalone MCP server (no plugin)
Add the MCP server directly to your Codex config (~/.codex/config.toml):
[mcp_servers.factiq]
url = "https://api.factiq.com/mcp"
Then codex mcp login factiq. The skill won't auto-invoke without the plugin, but the MCP tools are available for manual use.
For Claude Code without the plugin:
claude mcp add --transport http factiq https://api.factiq.com/mcp
Then authorize with /mcp.
Every FactIQ tool also works without the browser sign-in. The guide at factiq.com/docs/api explains headless access for scripts, CI, Claude Code, and Codex.
https://api.factiq.com/mcp (see .mcp.json), which you sign in to with OAuth. Each tool call sends its arguments (search terms, SQL statements, series IDs, tickers, regions) to that server and returns FactIQ data. FactIQ records connector tool inputs and outputs for reliability and support, as described in the privacy policy.send_feedback sends a short report, written by the agent, to the FactIQ team when a FactIQ result looks wrong. It changes no data. Every other tool only reads data.scripts/ (hs_codes.py, trade_sql.py, series_math.py). They read only their arguments, files you pass them, and the bundled files in scripts/data/, and they print their result. They make no network calls.Once installed and authenticated, ask a question:
/factiq:factiq How has India's trade deficit with China evolved since 2020?
The agent finds the relevant series, runs the SQL, and replies with a sourced answer, chart JSON, or full report, depending on what you ask for. You don't need the slash command: any economic or financial data question in any supported client auto-invokes the skill.
For an earnings question such as "What did Micron management say on its latest call?", the skill checks live transcript coverage first, pins the exact fiscal quarter, and then retrieves bounded management-claim and Q&A-pressure rows for that same call. It keeps spoken remarks separate from formal guidance and SEC filed actuals; the tool does not return a raw transcript.
For a media question such as "How has Jensen Huang discussed export controls outside earnings calls?", the skill checks company-level structured coverage, runs deterministic lexical retrieval with relevance ordering, and uses explicit newest ordering only for a timeline. Results are public-safe paraphrases with timestamped YouTube links, not quotations; the workflow verifies the linked source when exact wording or tone is material. A dedicated playbook also keeps media-vs-earnings comparisons aligned by company, person, topic, and date. The same tool covers documents published by central banks and monetary authorities (the Federal Reserve, the European Central Bank, the Bank of England, the Bank of Japan, the Reserve Bank of India, and others): a question such as "What has the Bank of Japan said about the inflation outlook?" filters by institution or country and reports the meeting or speech date that each document carries.
Your coding agent is the analyst: it finds the data, does the math, and authors a local output. Data access uses the FactIQ MCP server bundled in .mcp.json over one OAuth connection.
┌─────────────────────────────┐
│ Claude / ChatGPT / │ │ Claude Code / Codex │ │ + factiq skill (SKILL.md) │ the agent orchestrates everything └──────────────┬──────────────┘ │ MCP over HTTP (one OAuth connection) ┌──────────────▼──────────────┐ │ FactIQ MCP server │ │ │ │ discover search_datasets, describe_dataset, search_series, │ get_data_catalog │ fetch run_sql (read-only), get_series, get_market_data, │ search_company_filings, search_earnings_transcripts, │ search_media_appearances, search_news └──────────────┬──────────────┘ │ ┌──────────────▼──────────────┐ │ FactIQ data warehouse │ official and derived data sources └─────────────────────────────┘
The reason a single skill can query BLS unemployment, Chinese customs flows, RBI monetary data, and World Bank indicators with the same SQL idioms: every data source in the backend is normalized into the same three core tables, identical in every schema:
| Table | What it holds |
|---|---|
series | The catalog — one row per series: id, title, description, dataset, frequency, units, seasonality, geography, time coverage |
data_points | The values — (series_id, time, value), indexed for fast retrieval |
dimensions | Faceted metadata — (series_id, dimension_type, dimension_code, dimension_name), e.g. partner, flow, commodity, hs_level for trade data |
Our ingestion pipelines do the hard work of flattening each source's bespoke format — BLS flat files, BEA APIs, customs records, RBI releases — into this shape, so the agent learns the model once and it works everywhere. Discovery, pivoting, and filtering follow the same patterns across all ~20 schemas; the recipes live in references/data/sql-guide.md.
| Region | Schemas |
|---|---|
| United States | SEC filings data, BLS (employment, CPI, JOLTS, OEWS), Census (trade incl. HS-level, retail, housing), BEA (GDP, income), EIA (energy), USDA ERS, BTS (transportation), earnings-call transcripts, executive media appearances, Federal Reserve speeches, testimony, statements, minutes, and press-conference transcripts |
| China | NBS macro indicators, GACC customs (HS-level trade) |
| India | MOSPI (CPI, WPI, IIP, GDP), RBI (banking, rates, forex), DGCI&S trade (HS-level), Bengaluru road traffic (2026 onward, that one city only), RBI speeches and press releases |
| South Korea | KCS customs (HS-level trade) |
| European Union | Eurostat Comext monthly trade for all 27 member-state reporters, by CN8 product and partner country; E
Only the beginning is shown; read the rest in the repo