MCP server de LLMQuant Data
Commit 27 ago 2026Conecta agentes de IA con datos financieros que incluyen precios de cripto, mercados de acciones, presentaciones de la SEC, indicadores macro y mercados de predicción.
También conocido como LLMQuant/data-mcp
- Stars
- 89
- Herramientas
- 26
- Descargas, 30 días
- —
- Última versión
- —
- Último commit
- 27 ago 2026
- Licencia
- MIT
¿Qué es LLMQuant Data MCP?
LLMQuant Data es un MCP server. Conecta agentes de IA con datos financieros que incluyen precios de cripto, mercados de acciones, presentaciones de la SEC, indicadores macro y mercados de predicción. Expone 26 herramientas, como wiki_search, wiki_read, paper_search.
Resumen generado a partir del README del proyecto
Acerca del MCP server de LLMQuant Data
La función principal de data-mcp es proporcionar inteligencia financiera estructurada a los agentes de IA. Los desarrolladores que crean agentes financieros pueden integrar estas herramientas para acceder a precios de cripto, mercados de acciones de EE. UU., presentaciones de la SEC e indicadores macro. Los datos están estructurados para el contexto de un agente en lugar de para la navegación humana, lo que ayuda a automatizar tareas de investigación complejas.
Los usuarios pueden configurar la conexión localmente usando stdio a través de npx o conectarse mediante una URL remota alojada. Se requiere una LLMQUANT_API_KEY para instalaciones locales. El conjunto de herramientas incluye funciones específicas como crypto_snapshot para precios actuales, polymarket_event_search para mercados de predicción y sec_filing_read para acceder a documentos regulatorios. También ofrece capacidades de búsqueda semántica a través de wiki_search y paper_search para ayudar a los agentes a navegar por entradas de wiki cuantitativas y documentos de investigación.
Qué puedes hacer con él
- 1Investigación de tendencias del mercado criptoUn agente puede obtener precios actuales de criptomonedas y estadísticas de 24 horas.
- 2Análisis de presentaciones regulatorias de la SECUn desarrollador puede instruir a un agente para que lea secciones específicas de un formulario 10-K o 10-Q de una empresa.
- 3Exploración de probabilidades en mercados de predicciónLos agentes pueden buscar eventos relacionados con finanzas en Polymarket para encontrar probabilidades implícitas.
- 4Búsqueda de documentos de investigación cuantitativaUna IA puede realizar búsquedas semánticas en una biblioteca de más de 1,200 documentos de investigación.
Escrito a partir del README del proyecto. Cada caso de uso se verifica con una cita del mismo.
Herramientas de LLMQuant Data MCP 26
Detectado desde el 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 | — |
Mostrar las 26 herramientasMostrar menos herramientas
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 | — |
Configuración
LLMQUANT_API_KEY
| Nombre | Descripción | Tipo |
|---|---|---|
| LLMQUANT_API_KEY | — |
Verificaciones automáticas
Ejecutado 13 nov 2026Informe completo →Aún no verificado. Un servidor necesita una puntuación de 80, ningún hallazgo grave y suficientes datos para que podamos revisarlo. Cómo funcionan las verificaciones · Qué corregir para obtener más puntos
- Repositorio de origen vinculado y accesiblellmquant/data-mcp is public and reachablegithub.com/llmquant/data-mcp ↗Aprobado
- El paquete indica este repositorio como su origenNo verificado
- Procedencia de la compilación (atestación de Sigstore)No verificado
- Licencia de código abierto (OSI)MITspdx.org/licenses/MIT.html ↗Aprobado
- Commit o lanzamiento en el último añoLast commit or release 2026-08-27github.com/llmquant/data-mcp ↗Aprobado
- OpenSSF ScorecardNo verificado
- El nombre del paquete no es similar a un paquete popularNo verificado
- No hay avisos críticos en el paquete ni en sus dependenciasNo verificado
- Sin instrucciones ocultas para el modelo26 tool descriptions and the README read; no override phrases, credential paths or hidden charactersAprobado
- Las herramientas destructivas están etiquetadasNo tool named like delete, drop or execAprobado
- El endpoint remoto responde al handshake de MCPNo verificado
README
Ver en GitHub[!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
Preguntas sobre LLMQuant Data MCP
¿Qué herramientas proporciona LLMQuant Data MCP?
Expone 26 herramientas, incluidas wiki_search, wiki_read, paper_search, paper_read, crypto_historical_klines.
¿Qué tipo de datos financieros puedo consultar?
Puedes acceder a artículos de wiki, documentos de investigación, precios de cripto y acciones, mercados de predicción, indicadores macro, presentaciones de la SEC y más.
¿Puedo usar este servidor sin ejecutar un proceso local de Node.js?
Sí, los usuarios que hayan iniciado sesión pueden generar una URL de conector Remote MCP alojada desde el dashboard de LLMQuant para usarla con clientes que admitan conectores remotos.