ApocData MCPサーバー
コミット 2026年10月14日Aシェア市場の構造化データ(解析済みのアナウンスメント、財務ファンダメンタルズ、資金フローなど)をAIエージェントやリサーチ向けに提供します。
別名 ApocData/ApocData-skill
- スター
- 104
- ツール
- —
- ダウンロード数(30日間)
- —
- 最新バージョン
- —
- 最終コミット
- 2026年10月14日
- ライセンス
- Apache-2.0
ApocData MCPとは
ApocDataはMCPサーバーです。 Aシェア市場の構造化データ(解析済みのアナウンスメント、財務ファンダメンタルズ、資金フローなど)をAIエージェントやリサーチ向けに提供します。.
プロジェクトのREADMEから生成された概要
ApocData MCP server について
ApocData-skillは、Aシェア市場に特化した、AIエージェントおよび計量リサーチ向けに設計された構造化市場データを提供します。生のPDFアナウンスメントを、AIが生成した要約、センチメント分析、重要度レベルを含む、マシンリーダブルな形式に変換します。これにより、大規模言語モデルは手動での解析を行うことなく、金融イベントに基づいた推論が可能になります。
このMCP serverは、株価、財務、資金フロー、マクロ指標、龍虎榜(dragon-tiger lists)をカバーする46個のツールと45以上のエンドポイントを提供します。Claude Desktop、Cursor、ChatGPT、およびDeepSeekやKimiなどのエージェントを含む、さまざまなAIクライアントと互換性があります。ユーザーは、MCP対応環境ではnpx経由でセットアップするか、直接HTTPエンドポイントを使用できます。
登録なしですぐに利用できる無料ティアが用意されていますが、より高いクォータや詳細な履歴データを利用する場合は登録が可能です。本サービスには、転換社債、セクター、ストップ高レビューなどの特定のデータグループが含まれており、中国株式市場の包括的なビューを提供します。
できること
- 1比較バリュエーション分析の実行開発者はエージェントに対し、特定の銘柄のバリュエーション指標を同業他社と比較するよう指示できます。
- 2高リスク証券のモニタリングエージェントがST銘柄(特別注意銘柄)からの最近の重要なアナウンスメントを特定・要約し、潜在的なリスクを評価できます。
- 3資金移動トレンドの追跡どの市場セクターに北向資金(Northbound capital)が最も流入しているか、その要約をリクエストできます。
プロジェクトの README から作成されています。すべてのユースケースは、その引用と照らし合わせて確認されています。
自動チェック
実行日 2026年11月14日完全なレポート →まだ検証されていません。サーバーには80点のスコア、重大な問題がないこと、および検証に必要な十分なデータが必要です。 チェックの仕組み · 点数を上げるための改善点
- ソースリポジトリがリンクされており、アクセス可能apocdata/apocdata-skill is public and reachablegithub.com/apocdata/apocdata-skill ↗合格
- パッケージがこのリポジトリをソースとして指定未チェック
- ビルドの来歴 (Sigstore 証明)未チェック
- オープンソースライセンス (OSI)Apache-2.0spdx.org/licenses/Apache-2.0.html ↗合格
- 過去1年以内にコミットまたはリリースありLast commit or release 2026-10-14github.com/apocdata/apocdata-skill ↗合格
- OpenSSF Scorecard未チェック
- パッケージ名が有名なパッケージに酷似していない未チェック
- パッケージおよびその依存関係に重大な勧告なし未チェック
- モデルへの隠れた指示がない0 tool descriptions and the README read; no override phrases, credential paths or hidden characters合格
- 破壊的なツールがラベル付けされている未チェック
- リモートエンドポイントが MCP ハンドシェイクに応答未チェック
README
GitHubで見る天启至数 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のよくある質問
アナウンスメントの解析はどのように行われますか?
ApocDataは、生の発表資料をAIによる要約、カテゴリ、重要度、センチメントなどの構造化されたフィールドに解析し、AIが推論しやすい形式に変換します。
無料版はありますか?
はい、即時アクセスや軽量な利用が可能な無料ティアがあります。ただし、より高いクォータを利用するには登録が必要です。
ClaudeやChatGPTで使用できますか?
はい、Claude、ChatGPT、Qwen、Kimi、DeepSeekなど、ツール呼び出しをサポートするあらゆるAIエージェントと互換性があります。