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The knowledge harness for AI‑native finance — MCP server for LLMQuant Data.

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<h3 align="center">@llmquant/data-mcp</h3>

The knowledge harness for AI‑native finance. 
 <a href="https://llmquantdata.com">Website</a> · <a href="https://docs.llmquantdata.com">Docs</a> · <a href="./README.zh-CN.md">中文</a>

---

> [!IMPORTANT]
> **New: [Company News](https://docs.llmquantdata.com/en/api/news/browse) and [Polymarket prediction markets](https://docs.llmquantdata.com/en/api/prediction-markets/events) are live.** Browse company updates, discover market events, and track implied probabilities from one MCP server.

Context engineering meets financial data — structured for agent context, not human browsing.

## Table of Contents

- [What It Does](#what-it-does)
- [Available Tools](#available-tools)
- [Try It Out](#try-it-out)
- [Quick Install (Prompt)](#quick-install-prompt)
- [Client Setup](#client-setup)
- [Remote / Hosted MCP](#remote--hosted-mcp)
- [Environment Variables](#environment-variables)
- [Roadmap](#roadmap)
- [See Also](#see-also)
- [Contributing](#contributing)
- [License](#license)

## What It Does

This is an MCP server for [LLMQuant Data](https://llmquantdata.com). It connects any AI agent to financial data — wiki articles, research papers, crypto & equity prices, prediction markets, macro indicators, SEC filings, and more — through the [Model Context Protocol](https://modelcontextprotocol.io).

Configure once — every agent in your stack gets the data.

> [!TIP]
> We're also building **llmquantdata-skills** — a companion set of agent skills that combine these data tools into ready‑made AI‑native financial workflows (equity research, macro analysis, etc.). Stay tuned.

## Available Tools

> [!NOTE]
> The credit model is in **beta** — amounts below may change. Sign up at [llmquantdata.com](https://llmquantdata.com) for free credits, no credit card required.

| Tool | Description | Credit |
|------|-------------|--------|
| `wiki_search` | Semantic search over 50,000+ quant wiki entries | 1 |
| `wiki_read` | Read a wiki article by ID | 0 |
| `paper_search` | Semantic search over 1,200+ research papers | 1 |
| `paper_read` | Read paper sections (intro, methods, conclusion, …) | 0 |
| `crypto_historical_klines` | Crypto OHLCV candlestick data | 1 |
| `crypto_snapshot` | Current crypto price + 24h stats | 0 |
| `polymarket_event_browse` | List or exact-filter finance-scoped Prediction Markets events by keyword, status, tag, asset, volume, and liquidity filters | 1 |
| `polymarket_event_search` | Semantic search over finance-scoped Prediction Markets events | 2 |
| `polymarket_event_read` | Read one Prediction Markets event card with child market previews | 0 |
| `polymarket_market_read` | Read one Prediction Markets market card with outcomes and outcome token ids | 0 |
| `polymarket_price_history` | Hourly or daily implied-probability history for one outcome token | 0 |
| `equity_historical_prices` | US equity daily OHLCV + dividend/split data | 0 |
| `equity_intraday_prices` | US equity 1h regular-session OHLCV bars | 1 |
| `macro_indicator_search` | Browse 50+ curated macro indicators | 0 |
| `macro_indicator_history` | Historical observations for a macro indicator | 1 |
| `macro_indicator_snapshot` | Latest value for a macro indicator | 0 |
| `sec_filing_browse` | Browse SEC 10-K / 10-Q / 8-K filing metadata (each row carries `sectionKeys` = available section codes) | 0 |
| `sec_filing_read` | Read section text from a SEC filing; pass `items` to fetch a batch in one call, omit for all (8-K requires `accession_number` — browse first) | 1 |
| `sec_13f_list_manager_holdings` | List an institutional manager's 13F holdings (covered manager set × at least the last 4 quarters) | 1 |
| `sec_13f_list_ticker_holders` | List institutional holders of a ticker (covered manager set × at least the last 4 quarters) | 1 |
| `sec_13f_list_top_managers` | List the top N smart money managers ranked by 13F reportable value (latest quarter, up to 1000) | 0 |
| `etf_lookup` | ETF fund identity + SEC mapping + top holdings summary (currently supported ETFs) | 0 |
| `etf_holdings` | ETF latest available SEC N-PORT regulatory holdings (currently supported ETFs) | 1* |
| `news_browse` | Browse recent company news by ticker, event, topic, or date | 2 |
| `personal_holdings` | Read the holdings you saved in your LLMQuant Dashboard → Profile (your own account only) | 0 |
| `personal_profile` | Read the financial profile you saved in your LLMQuant Dashboard → Profile (your own account only) | 0 |

* An unsupported ETF ticker returns `200` with an explicit coverage notice and `0` credits — you are only charged the 1 credit when holdings are actually returned.

Prediction Markets tools follow an event-first flow: use `polymarket_event_search` first for natural-language discovery, use `polymarket_event_browse` only for list/exact-filter requests, then read a selected event, read a market, and request price history for an outcome token.

> More data products (company fundamentals, earnings transcripts, etc.) are on the [roadmap](#roadmap).

Four ways to access each data product:

## Try It Out

Launch the [MCP Inspector](https://modelcontextprotocol.io/docs/tools/inspector) to explore tools interactively in your browser:

```bash
export LLMQUANT_API_KEY=your_api_key
npx @modelcontextprotocol/inspector npx -y @llmquant/data-mcp
```

> [!NOTE]
> To persist the key, add `export LLMQUANT_API_KEY=your_api_key` to your `~/.zshrc` or `~/.bashrc`.

> [!TIP]
> You'll need an API key — sign up free at [llmquantdata.com](https://llmquantdata.com).

## Quick Install (Prompt)

The fastest way: drop this prompt into Claude Code, Cursor, Codex CLI, Gemini CLI, or any MCP-enabled agent. The agent will read this README and run the right setup for its runtime.

```text
Install the LLMQuant data-mcp server in this environment by following https://github.com/LLMQuant/data-mcp
```

> [!TIP]
> Make sure `LLMQUANT_API_KEY` is exported in the shell where the agent runs. Get a key at [llmquantdata.com](https://llmquantdata.com).

Prefer to set it up by hand? See [Client Setup](#client-setup) below.

## Client Setup

### Claude Code

```bash
claude mcp add llmquant-data \
  -e LLMQUANT_API_KEY=your_api_key \
  -- npx -y @llmquant/data-mcp
```

### Cursor

Add to `.cursor/mcp.json` (project) or `~/.cursor/mcp.json` (global):

```json
{
  "mcpServers": {
    "llmquant-data": {
      "command": "npx",
      "args": ["-y", "@llmquant/data-mcp"],
      "env": {
        "LLMQUANT_API_KEY": "your_api_key"
      }
    }
  }
}
```

### Codex CLI

```bash
codex mcp add llmquant-data \
  --env LLMQUANT_API_KEY=your_api_key \
  -- npx -y @llmquant/data-mcp
```

### Gemini CLI

```bash
gemini mcp add -s user \
  -e LLMQUANT_API_KEY=your_api_key \
  llmquant-data \
  npx -y @llmquant/data-mcp
```

### Other MCP Clients

Any client supporting stdio transport can use this JSON config:

> [!NOTE]
> We're working on integration guides for more clients. If your agent framework isn't listed, [open an issue](https://github.com/LLMQuant/data-mcp/issues) and we'll add it.

## Remote / Hosted MCP

`@llmquant/data-mcp` keeps local `stdio` as the default setup path. Signed-in LLMQuant users can also generate a hosted Remote MCP connector URL from the dashboard. Hosted connectors are useful when your MCP client supports remote connectors and you do not want to run a local Node.js process.

### Claude custom connectors

In the LLMQuant dashboard, open **Connect** and generate a Remote MCP URL.

```text
https://mcp.llmquantdata.com/u/lqd_mcp_.../mcp
```

Paste the full URL into Claude's custom connector flow. The hosted URL is separate from your local `LLMQUANT_API_KEY` and can be revoked from the dashboard.

> [!IMPORTANT]
> Treat the hosted connector URL like a password. Anyone with the URL can use the connector until you revoke it.

## Environment Variables

| Variable | Required | Default | Description |
|----------|----------|---------|-------------|
| `LLMQUANT_API_KEY` | Yes for stdio | — | User API key for local stdio mode |
| `LLMQUANT_BASE_URL` | No | `https://api.llmquantdata.com` | API base URL |
| `LLMQUANT_API_TIMEOUT_MS` | No | `15000` | Request timeout in ms (max 120000) |

## Roadmap

- [x] Streamable HTTP transport (remote MCP without local Node.js)
- [ ] OAuth connector flow for Claude Connectors Directory
- [ ] More data products — company fundamentals, earnings transcripts
- [ ] Agent skills companion package (**llmquantdata-skills**)
- [ ] Integration guides for more agent frameworks

Have a feature request? [Open an issue](https://github.com/LLMQuant/data-mcp/issues) or email us at **contact@llmquant.com**.

## See Also

- **[Awesome Trading Agents](https://github.com/LLMQuant/awesome-trading-agents)** — community-curated agent recipes that turn `data-mcp` tools into end-to-end research workflows (equity research, macro briefings, smart-money digests).
- **[Documentation](https://docs.llmquantdata.com)** — full API reference, MCP setup guides, and credit policy.

## Contributing

This repository is a **read-only mirror**. We do not accept pull requests.

Found a bug or have a feature request? Please [open an issue](https://github.com/LLMQuant/data-mcp/issues) — we actively triage and respond.

## License

[MIT](./LICENSE)

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