MCP server de ApocData
Commit 14 oct 2026Proporciona datos estructurados del mercado de acciones A, incluyendo anuncios analizados, fundamentos financieros y flujos de capital, para agentes de IA e investigación.
También conocido como ApocData/ApocData-skill
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- Descargas, 30 días
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- Última versión
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- Último commit
- 14 oct 2026
- Licencia
- Apache-2.0
¿Qué es ApocData MCP?
ApocData es un MCP server. Proporciona datos estructurados del mercado de acciones A, incluyendo anuncios analizados, fundamentos financieros y flujos de capital, para agentes de IA e investigación.
Resumen generado a partir del README del proyecto
Acerca del MCP server de ApocData
ApocData-skill proporciona datos de mercado estructurados diseñados específicamente para agentes de IA e investigación cuantitativa centrada en el mercado de acciones A. Transforma anuncios en PDF sin procesar en formatos legibles por máquinas que contienen resúmenes generados por IA, análisis de sentimiento y niveles de importancia. Esto permite que los modelos de lenguaje extensos razonen sobre eventos financieros sin necesidad de un análisis manual.
El servidor ofrece 46 herramientas y más de 45 endpoints que cubren cotizaciones, estados financieros, flujos de capital, indicadores macroeconómicos y listas dragon-tiger. Es compatible con varios clientes de IA, incluyendo Claude Desktop, Cursor, ChatGPT y agentes como DeepSeek o Kimi. Los usuarios pueden configurarlo mediante npx para entornos compatibles con MCP o utilizar endpoints HTTP directos.
Hay un nivel gratuito disponible para acceso instantáneo sin necesidad de registro, aunque los usuarios pueden registrarse para obtener cuotas más altas y datos históricos más profundos. El servicio incluye grupos de datos específicos como bonos convertibles, sectores y revisiones de límites de precio (limit-up) para proporcionar una visión integral del mercado de renta variable chino.
Qué puedes hacer con él
- 1Realización de análisis de valoración comparativaUn desarrollador puede asignar a un agente la tarea de comparar las métricas de valoración de una acción frente a sus pares de la industria.
- 2Monitoreo de valores de alto riesgoUn agente puede identificar y resumir anuncios materiales recientes de acciones ST para evaluar riesgos potenciales.
- 3Seguimiento de tendencias de movimiento de capitalUn usuario puede solicitar un resumen de qué sectores del mercado están recibiendo la mayor entrada de capital northbound.
Escrito a partir del README del proyecto. Cada caso de uso se verifica con una cita del mismo.
Verificaciones automáticas
Ejecutado 14 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 accesibleapocdata/apocdata-skill is public and reachablegithub.com/apocdata/apocdata-skill ↗Aprobado
- El paquete indica este repositorio como su origenNo verificado
- Procedencia de la compilación (atestación de Sigstore)No verificado
- Licencia de código abierto (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗Aprobado
- Commit o lanzamiento en el último añoLast commit or release 2026-10-14github.com/apocdata/apocdata-skill ↗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 modelo0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersAprobado
- Las herramientas destructivas están etiquetadasNo verificado
- El endpoint remoto responde al handshake de MCPNo verificado
README
Ver en GitHub天启至数 ApocData — A股数据服务 (ApocData A-Share Data Skill)
Let AI read A-share announcements
The A-share announcements and fundamentals database built for AI · parsed · structured · traceable
All-market announcements parsed into structured data: AI summary · category · importance · sentiment, fully traceable to source. Also 45+ endpoints for quotes, financials, capital flows, dragon-tiger lists and macro data. Free tier for instant access; register for higher quotas. Compatible with WorkBuddy, Codex, Hermes, DeepSeek, Kimi, Qwen, Zhipu and any AI agent that supports tool calling.
The SKILL.md in this repository is a capability card that can
be loaded directly into AI agents, letting LLMs query A-share market data
and complete research tasks without any SDK.
Quick Try
Copy-paste and run, no config needed:
curl -s "https://www.apocdata.com/api/blade-dataplatform/open/data/quote?symbol=600519"
{
"code": 200, "success": true,
"data": {
"symbol": "600519", "name": "Kweichow Moutai",
"close": 1528.00, "pct_chg": -0.52,
"volume": 2856321, "delayed_minutes": 15
}
}
Actual response has more fields; above is a simplified example.
Announcement Parsing — from PDF to structured data
Conventional data sources hand you the raw announcement text and leave the reading and parsing to you. ApocData returns the parsed, structured result, ready for an AI agent to consume.
Every announcement carries:
- AI summary (
summary) — the key facts extracted, no need to read the full document - Category (
category) — earnings, dividend, buyback, share increase/decrease, litigation and more, filterable programmatically - Importance level (
importance) — locate the announcements that actually matter - Sentiment (
sentiment) — positive / negative / neutral, to help judge the direction of impact - Source link (
url) — every conclusion traces back to the original announcement
Also returned: title, ann_date, publish_time, keywords, source, and
content (full Markdown body, on includeContent=true).
Covers all-market announcements, including Stock Connect constituents, ST and delisting-risk securities.
Why ApocData?
| ApocData | 数据源A | 数据源B | 数据源C | |
|---|---|---|---|---|
| Announcement parsing | Structured + AI summary + sentiment | Raw text | Raw text | Raw text |
| Access | Free tier, no registration | Paid token | Python env + install | Application approval |
| Setup steps | 0 | 3+ (register → token → config) | 2+ (pip + deps) | Manual review |
| AI Agent native | Skill + MCP | Plugin (legacy) | Not supported | Not supported |
| curl one-liner | Direct | Need SDK | Need SDK | Need SDK |
| A-share endpoints | 45 | 100+ (paywalled) | 100+ (free) | 200+ (paid) |
| MCP support | 46 tools | None | None | None |
Comparison based on publicly available info as of 2026-08.
Core Capabilities
- Announcement parsing — all-market announcements parsed by AI into structured fields
(
title/category/importance/ann_date/summary/sentiment/url), directly usable for reasoning and traceable to the source document (mainstream data sources mostly ship announcements as raw text) - Full-dimension coverage — quotes, financials, valuation, capital flows, limit-up review, dragon-tiger lists, sectors & concepts, convertible bonds, macro indicators and trading calendar: 11 groups, 45+ endpoints, one consistent definition set
- Multiple integration paths — Skill package (one-command install), MCP server (46 tools), plain HTTP endpoints (direct curl), covering every mainstream AI ecosystem
- Traceable — every data point traces back to the original announcement, so AI conclusions can be checked
Table of Contents
- Announcement Parsing
- Why ApocData?
- Core Capabilities
- Overview
- Use Cases
- Data Service Platform
- Installation
- Project Structure
- Basic Usage
- Endpoint Overview
- Editions & Capabilities
- Notes & Compliance
Overview
ApocData is the A-share announcements and data layer built for AI: parsed, structured, traceable. Announcement parsing is the core — every announcement becomes structured data an agent can reason over directly — and around it sits full-dimension coverage of quotes, financials, capital flows, dragon-tiger lists, quantitative factors and macro indicators, designed for AI agents, quantitative research, investment content, and institutional applications.
Use Cases
- "What are the key points in Kweichow Moutai's recent earnings flash?" → key figures extracted as structured fields, traceable to the original announcement
- "Analyse the valuation of 688017 — how does it compare with its peers?" → PE/PB/market cap aggregated with financial metrics and the last 30 sessions
- "Which ST stocks published material announcements in the past 30 days?" → ranked by risk level, each with an AI summary and a source link
- "Which sectors has northbound capital been flowing into?" → Stock Connect plus sector capital flows, with the top inflow sectors summarised automatically
Data Service Platform
Platform URL: https://www.apocdata.com
The data service platform is the unified entry point for ApocData. It provides:
- Open API (free tier) — This is what the Skill connects to. A free trial quota is callable straight away, ideal for quick validation and lightweight usage.
- OpenAPI documentation & SDKs — Python / TypeScript supported.
- Registered & Professional editions (with API key) — Higher quotas, deeper history, lower latency, and richer data fields. See Editions & Capabilities.
The base URL used by this Skill:
https://www.apocdata.com/api/blade-dataplatform/open/data
Installation
Quick Install (recommended)
mkdir -p ~/.claude/skills/apocdata
curl -sL https://gitee.com/apocdata/ApocData-skill/repository/archive/v2.0.5.tar.gz \
| tar xz -C ~/.claude/skills/apocdata --strip-components=1
Restart Claude Code and the skill will be auto-detected.
MCP Install (Claude Desktop / Cursor / ChatGPT)
{
"mcpServers": {
"apocdata": {
"command": "npx",
"args": ["-y", "@apocdata-info/mcp-server"]
}
}
}
OpenAPI Import (GPT Actions / Dify / Coze / n8n)
https://www.apocdata.com/api/blade-dataplatform/open/data/openapi.json
Import and use — free tier, no registration needed.
Alternative: install script
curl -sL https://gitee.com/apocdata/ApocData-skill/raw/main/scripts/install.sh | bash
Project Structure
This Skill uses a multi-file structure for progressive loading — the entry
SKILL.md is a slim router (~180 lines), and detailed endpoint specs are
loaded on demand from the references/ directory:
├── SKILL.md # Entry point (slim router, ~180 lines)
├── README.md # This file (human-facing docs)
├── CHANGELOG.md # Version history
├── references/ # On-demand reference docs (loaded per topic)
│ ├── boundaries.md # Interface boundaries, headers, error codes, cache, freshness
│ ├── group-a-quote.md # A. Quotes & Valuation (10 endpoints)
│ ├── group-b-financial.md # B. Financials & Fundamentals (8 endpoints)
│ ├── group-c-capital.md # C. Capital Flow (7 endpoints)
│ ├── group-d-limitup.md # D. Limit-up & Sentiment (4 endpoints)
│ ├── group-e-events.md # E. Events & Information (3 endpoints)
│ ├── group-f-sector.md # F. Sectors & Concepts (4 endpoints)
│ ├── group-g-convertible.md # G. Convertible Bonds (2 endpoints)
│ ├── group-h-quant.md # H. Quant & Technical (2 endpoints)
│ ├── group-i-macro.md # I. Macro (3 endpoints)
│ ├── group-j-tools.md # J. Tools (1 endpoint)
│ ├── group-k-agent.md # K. Agent Enhanced (2 endpoints)
│ ├── examples.md # Multi-endpoint analysis examples (5 scenarios)
│ └── safety-rules.md # Financial output safety constraints (6 rules)
└── scripts/
└── install.sh # One-line install script
Why multi-file? A simple query like "what's the price of Moutai" only needs the entry SKILL.md + one reference file (~4K tokens), instead of loading the entire 47KB monolith (~15K tokens). This reduces token consumption by 70%+.
Basic Usage
All endpoints are HTTP GET, called with curl:
BASE="https://www.apocdata.com/api/blade-dataplatform/open/data"
# Get real-time quote
curl -s "$BASE/quote?symbol=000001"
# Get stock info (PE/PB/market cap)
curl -s "$BASE/stock?symbol=000001"
# Get comprehensive profile (8 dimensions in one call)
curl -s "$BASE/profile/full?symbol=688017"
Endpoint Overview
| Group | Topic | Endpoints |
|---|---|---|
| A | Quotes & Valuation | 10 |
| B | Financials & Fundamentals | 8 |
| C | Capital Flow | 7 |
| D | Limit-up & Sentiment | 4 |
| E | Events & Information | 2 (+ 1 deprecated) |
| F | Sectors & Concepts | 4 |
| G | Convertible Bonds | 2 |
| H | Quant & Technical | 2 |
| I | Macro | 3 |
| J | Tools | 1 |
| K | Agent Enhanced | 2 |
| Total | 45 active (+ 1 deprecated) |
Editions & Capabilities
ApocData is organized into four editions to match different use cases. All editions share the same API contract; capabilities are filtered by edition whitelist. This Skill defaults to the free-tier open endpoints. Register to unlock higher quotas and more data capabilities.
Edition Lineup
| SKU | Edition | Target Users |
|---|---|---|
| FREE | Free | Individuals / AI agent demos |
| PRO | Professional | Investment research / content creators |
| QUANT | Quant | Quantitative research teams |
| ENT | Enterprise | Institutional embedding / private deployment |
Capability Comparison (selected)
| Capability | Free | Pro | Quant | Enterprise |
|---|---|---|---|---|
| Daily calls | 2,000 | 50,000 | 300,000 | Custom |
| QPS limit | 2 | 10 | 30 | Custom |
| Snapshot latency | 15 min | 1 min | ≤ 30s | Custom (≤ 10s) |
| Daily K depth | 30 days | 5 yrs + adj. | Full | Full |
| Quant factors | — | 20 | Full | Full + custom |
| MCP Tools | 8 | 14 | 18 | 18+ custom |
| Availability SLO | best-effort | 99.0% | 99.5% | 99.9% (contract) |
| Support | Community | Email 48h | Email 24h | Dedicated channel + phone |
Endpoint Verification
Last verified: 2026-08-12 12:21 CST
| Check | Result |
|---|---|
| Core endpoints tested | 12/12 -> HTTP 200 |
| Total active endpoints | 45 (across 11 groups) |
| Avg latency | ~217ms |
| Deprecated | /news (HTTP 410, documented in group-e) |
Verified endpoints: quote, stock, daily, financial, moneyflow, hsgt,
limit-list, announcements, concepts, macro/latest, calendar, profile/full.
Full 45-endpoint coverage is validated via the scenario quick-reference table in SKILL.md.
Notes & Compliance
- Free tier: callable without registration, suited to quick validation and light usage
- Registered users: higher quotas and more data capabilities (see the platform editions page)
- All endpoints are read-only
- Data source: ApocData Cloud (天启云), synced with A-share market data
- Free tier quotes have a ~15-minute delay (see
delayed_minutesin response) - Announcements: T+0 at 08:00; Northbound capital: 20:00
- This Skill is for research assistance only — not investment advice
- Financial output safety constraints are enforced via
references/safety-rules.md
Get Started
Free tier, callable without registration; registered users unlock higher quotas and more data capabilities.
Try free → · Register → · Star on Gitee →
License
See LICENSE for details.
Preguntas sobre ApocData MCP
¿Cómo funciona el análisis de anuncios?
ApocData analiza anuncios sin procesar y los convierte en campos estructurados como resumen de IA, categoría, importancia y sentimiento, dejándolos listos para el razonamiento de la IA.
¿Hay una versión gratuita disponible?
Sí, hay un nivel gratuito disponible para acceso instantáneo y uso ligero, aunque se requiere registro para obtener cuotas más altas.
¿Puedo usar esto con Claude o ChatGPT?
Sí, es compatible con cualquier agente de IA que soporte tool calling, incluyendo Claude, ChatGPT, Qwen, Kimi y DeepSeek.