LLMQuant Data MCP server
Commit 27. Aug. 2026Verbindet AI Agents mit Finanzdaten, einschließlich Krypto-Preisen, Aktienmärkten, SEC-Filings, Makroindikatoren und Prediction Markets.
Auch bekannt als LLMQuant/data-mcp
- Stars
- 89
- Tools
- 26
- Downloads, 30 Tage
- —
- Neueste Version
- —
- Letzter Commit
- 27. Aug. 2026
- Lizenz
- MIT
Was ist LLMQuant Data MCP?
LLMQuant Data ist ein MCP server. Verbindet AI Agents mit Finanzdaten, einschließlich Krypto-Preisen, Aktienmärkten, SEC-Filings, Makroindikatoren und Prediction Markets. Er stellt 26 Tools bereit, etwa wiki_search, wiki_read, paper_search.
Zusammenfassung generiert aus dem README des Projekts
Über LLMQuant Data MCP server
Die Hauptfunktion von data-mcp ist die Bereitstellung strukturierter Finanzintelligenz für AI Agents. Entwickler, die Finanz-Agents bauen, können diese Tools integrieren, um auf Krypto-Preise, US-Aktienmärkte, SEC-Filings und Makroindikatoren zuzugreifen. Die Daten sind für den Agent-Kontext und nicht für das menschliche Browsen strukturiert, was die Automatisierung komplexer Research-Aufgaben erleichtert.
Nutzer können die Verbindung lokal über stdio via npx aufbauen oder sich über eine remote gehostete URL verbinden. Für lokale Installationen ist ein LLMQUANT_API_KEY erforderlich. Das Toolset enthält spezifische Funktionen wie crypto_snapshot für aktuelle Preise, polymarket_event_search für Prediction Markets und sec_filing_read für den Zugriff auf regulatorische Dokumente. Zudem bietet es semantische Suchfunktionen über wiki_search und paper_search, um Agents bei der Navigation durch Quant-Wiki-Einträge und Research Papers zu unterstützen.
Was du damit machen kannst
- 1Recherche von Krypto-MarkttrendsEin Agent kann aktuelle Kryptowährungs-Preise und 24-Stunden-Statistiken abrufen.
- 2Analyse von SEC-RegulierungsunterlagenEin Entwickler kann einen Agent anweisen, spezifische Abschnitte eines 10-K oder 10-Q Filings eines Unternehmens zu lesen.
- 3Exploration von Wahrscheinlichkeiten in Prediction MarketsAgents können nach finanzbezogenen Events auf Polymarket suchen, um implizite Wahrscheinlichkeiten zu finden.
- 4Suche in quantitativen Research PapersEine KI kann semantische Suchen in einer Bibliothek von über 1.200 Research Papers durchführen.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
LLMQuant Data MCP tools 26
Erkannt aus dem READMEwiki_searchwiki_readpaper_searchpaper_readcrypto_historical_klinescrypto_snapshotpolymarket_event_browsepolymarket_event_searchpolymarket_event_readpolymarket_market_readpolymarket_price_historyequity_historical_prices
| wiki_search | — | |
| wiki_read | — | |
| paper_search | — | |
| paper_read | — | |
| crypto_historical_klines | — | |
| crypto_snapshot | — | |
| polymarket_event_browse | — | |
| polymarket_event_search | — | |
| polymarket_event_read | — | |
| polymarket_market_read | — | |
| polymarket_price_history | — | |
| equity_historical_prices | — |
Alle 26 Tools anzeigenWeniger Tools anzeigen
equity_intraday_pricesmacro_indicator_searchmacro_indicator_historymacro_indicator_snapshotsec_filing_browsesec_filing_readsec_13f_list_manager_holdingssec_13f_list_ticker_holderssec_13f_list_top_managersetf_lookupetf_holdingsnews_browsepersonal_holdingspersonal_profile
| equity_intraday_prices | — | |
| macro_indicator_search | — | |
| macro_indicator_history | — | |
| macro_indicator_snapshot | — | |
| sec_filing_browse | — | |
| sec_filing_read | — | |
| sec_13f_list_manager_holdings | — | |
| sec_13f_list_ticker_holders | — | |
| sec_13f_list_top_managers | — | |
| etf_lookup | — | |
| etf_holdings | — | |
| news_browse | — | |
| personal_holdings | — | |
| personal_profile | — |
Konfiguration
LLMQUANT_API_KEY
| Name | Beschreibung | Typ |
|---|---|---|
| LLMQUANT_API_KEY | — |
Automatisierte Checks
Geluften am 13. Nov. 2026Vollständiger Bericht →Noch nicht verifiziert. Ein Server benötigt einen Score von 80, keine kritischen Befunde und genug Daten für unsere Prüfung. Wie die Checks funktionieren · Was du für mehr Punkte verbessern kannst
- Source Repository verknüpft und erreichbarllmquant/data-mcp is public and reachablegithub.com/llmquant/data-mcp ↗Bestanden
- Paket nennt dieses Repository als QuelleNicht geprüft
- Build-Provenienz (Sigstore-Attestierung)Nicht geprüft
- Open Source Lizenz (OSI)MITspdx.org/licenses/MIT.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-08-27github.com/llmquant/data-mcp ↗Bestanden
- OpenSSF ScorecardNicht geprüft
- Package-Name ähnelt keinem populären PackageNicht geprüft
- Keine kritischen Advisories im Paket oder seinen AbhängigkeitenNicht geprüft
- Keine versteckten Anweisungen an das Modell26 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNo tool named like delete, drop or execBestanden
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehen[!IMPORTANT] New: Company News and Polymarket prediction markets 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
- Available Tools
- Try It Out
- Quick Install (Prompt)
- Client Setup
- Remote / Hosted MCP
- Environment Variables
- Roadmap
- See Also
- Contributing
- License
What It Does
This is an MCP server for LLMQuant Data. 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.
Configure once — every agent in your stack gets the data.
[!TIP] LLMQuant Skills is live. It combines these tools into ready‑made financial workflows for equity research, macro analysis, and more. Install the catalog or enable first-party Skills in the Agent Playground.
Available Tools
[!NOTE] The credit model is in beta — amounts below may change. Sign up at 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.
Four ways to access each data product:
Try It Out
Launch the MCP Inspector to explore tools interactively in your browser:
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_keyto your~/.zshrcor~/.bashrc.
[!TIP] You'll need an API key — sign up free at 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.
Install the LLMQuant data-mcp server in this environment by following https://github.com/LLMQuant/data-mcp
[!TIP] Make sure
LLMQUANT_API_KEYis exported in the shell where the agent runs. Get a key at llmquantdata.com.
Prefer to set it up by hand? See Client Setup below.
Client Setup
Claude Code
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):
{
"mcpServers": {
"llmquant-data": {
"command": "npx",
"args": ["-y", "@llmquant/data-mcp"],
"env": {
"LLMQUANT_API_KEY": "your_api_key"
}
}
}
}
Codex CLI
codex mcp add llmquant-data \
--env LLMQUANT_API_KEY=your_api_key \
-- npx -y @llmquant/data-mcp
Gemini CLI
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:
{
"mcpServers": {
"llmquant-data": {
"command": "npx",
"args": ["-y", "@llmquant/data-mcp"],
"env": {
"LLMQUANT_API_KEY": "your_api_key"
}
}
}
}
[!NOTE] We're working on integration guides for more clients. If your agent framework isn't listed, open an issue 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.
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
- 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 catalog (LLMQuant/skills)
- Integration guides for more agent frameworks
Have a feature request? Open an issue or email us at contact@llmquant.com.
See Also
- Awesome Trading Agents — community-curated agent recipes that turn
data-mcptools into end-to-end research workflows (equity research, macro briefings, smart-money digests). - Documentation — 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 — we actively triage and respond.
License
LLMQuant Data MCP Fragen
Welche Tools bietet LLMQuant Data MCP?
Er stellt 26 Tools bereit, darunter wiki_search, wiki_read, paper_search, paper_read, crypto_historical_klines.
Welche Art von Finanzdaten kann ich abrufen?
Du kannst auf Wiki-Artikel, Research Papers, Krypto- und Aktienkurse, Prediction Markets, Makroindikatoren, SEC-Filings und mehr zugreifen.
Kann ich diesen Server nutzen, ohne einen lokalen Node.js-Prozess auszuführen?
Ja, angemeldete Nutzer können im LLMQuant-Dashboard eine gehostete Remote MCP Connector URL generieren, um sie mit Clients zu nutzen, die Remote Connectors unterstützen.