ApocData MCP server
Commit 14. Okt. 2026Liefert strukturierte A-Aktien-Marktdaten, einschließlich geparster Ankündigungen, Fundamentaldaten und Kapitalflüssen, für AI Agents und Research.
Auch bekannt als ApocData/ApocData-skill
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- 14. Okt. 2026
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- Apache-2.0
Was ist ApocData MCP?
ApocData ist ein MCP server. Liefert strukturierte A-Aktien-Marktdaten, einschließlich geparster Ankündigungen, Fundamentaldaten und Kapitalflüssen, für AI Agents und Research.
Zusammenfassung generiert aus dem README des Projekts
Über ApocData MCP server
Der ApocData-skill bietet strukturierte Marktdaten, die speziell für AI Agents und quantitative Research mit Fokus auf den A-Aktienmarkt entwickelt wurden. Er transformiert rohe PDF-Ankündigungen in maschinenlesbare Formate, die KI-generierte Zusammenfassungen, Sentiment-Analysen und Wichtigkeitsstufen enthalten. Dies ermöglicht es Large Language Models, über Finanzereignisse zu schlussfolgern, ohne dass ein manuelles Parsing nötig ist.
Der Server bietet 46 Tools und über 45 Endpoints, die Kurse, Finanzdaten, Kapitalflüsse, Makroindikatoren und Dragon-Tiger-Listen abdecken. Er ist mit verschiedenen AI Clients kompatibel, darunter Claude Desktop, Cursor, ChatGPT sowie Agents wie DeepSeek oder Kimi. Nutzer können ihn via npx für MCP-kompatible Umgebungen einrichten oder direkte HTTP-Endpoints nutzen.
Ein Free Tier steht für den sofortigen Zugriff ohne Registrierung zur Verfügung, wobei Nutzer sich für höhere Quoten und tiefere historische Daten registrieren können. Der Service umfasst spezifische Datengruppen wie Wandelanleihen, Sektoren und Limit-up-Reviews, um einen umfassenden Überblick über den chinesischen Aktienmarkt zu bieten.
Was du damit machen kannst
- 1Durchführung von Vergleichsanalysen der BewertungEin Entwickler kann einen Agent beauftragen, die Bewertungskennzahlen einer Aktie mit denen ihrer Branchenkollegen zu vergleichen.
- 2Überwachung von Hochrisiko-WertpapierenEin Agent kann aktuelle wesentliche Ankündigungen von ST-Aktien identifizieren und zusammenfassen, um potenzielle Risiken zu bewerten.
- 3Verfolgung von Kapitalbewegungs-TrendsEin Nutzer kann eine Zusammenfassung darüber anfordern, welche Marktsektoren die meisten Northbound-Kapitalzuflüsse verzeichnen.
Geschrieben aus dem README des Projekts. Jeder Use Case wurde gegen ein Zitat daraus geprüft.
Automatisierte Checks
Geluften am 14. 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 erreichbarapocdata/apocdata-skill is public and reachablegithub.com/apocdata/apocdata-skill ↗Bestanden
- Paket nennt dieses Repository als QuelleNicht geprüft
- Build-Provenienz (Sigstore-Attestierung)Nicht geprüft
- Open Source Lizenz (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗Bestanden
- Commit oder Release im letzten JahrLast commit or release 2026-10-14github.com/apocdata/apocdata-skill ↗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 Modell0 tool descriptions and the README read; no override phrases, credential paths or hidden charactersBestanden
- Destruktive Tools sind markiertNicht geprüft
- Remote-Endpoint beantwortet den MCP-HandshakeNicht geprüft
README
Auf GitHub ansehen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.
ApocData MCP Fragen
Wie funktioniert das Parsing der Ankündigungen?
ApocData parst Rohdaten aus Ankündigungen in strukturierte Felder wie KI-Zusammenfassungen, Kategorien, Wichtigkeit und Sentiment, sodass sie direkt für das Reasoning von KIs bereitstehen.
Gibt es eine kostenlose Version?
Ja, es gibt einen Free Tier für den sofortigen Zugriff und leichte Nutzung, wobei für höhere Quoten eine Registrierung erforderlich ist.
Kann ich das mit Claude oder ChatGPT nutzen?
Ja, es ist mit jedem AI Agent kompatibel, der Tool Calling unterstützt, einschließlich Claude, ChatGPT, Qwen, Kimi und DeepSeek.