
Stockmatrix Mcp
io.github.MongLong0214由 GitHub 账号 MongLong0214 发布v0.5.0更新于 Oct 24, 2026
Korean stock market theme lifecycle analysis (TLI) — rankings, stock lookup, predictions & prompts
概览
让助手基于 TLI 生命周期评分分析韩国股市投资主题,提供排名、个股查询、主题对比与预测。
- 可以做什么
- 通过 StockMatrix API 提供 11 个工具用于韩国市场主题分析:按生命周期阶段获取主题排名、AI 优化的市场概览、每日或每周评分变动与阶段转换、2 至 5 个主题的并排对比,以及基于历史相似匹配的上涨、见顶、降温预测。还可按关键词、公司名或六位代码搜索主题与个股,进行个股到主题的反向查询,返回详细评分构成、30 天评分历史与 TLI 方法论文档。另有 4 个工作流提示词打包多工具分析,2 个只读资源提供方法论与当日排名。
- 适用场景
- 适合希望以对话方式了解韩国股市主题而非原始行情的人:跟踪哪些 KOSPI/KOSDAQ 主题正在兴起或见顶、检查持仓个股是否属于热门主题、比较不同主题,或回顾主题近一个月的动能。
- 运行要求
- 以 npm 包 stockmatrix-mcp 通过 stdio 在本地运行,使用 npx 启动,因此需要 Node.js 以及访问 StockMatrix API 的网络。未声明需要身份验证。可选环境变量 STOCKMATRIX_API_URL 可覆盖默认 API 基础地址。文档面向 Claude Desktop、Cursor、Windsurf、VS Code 等桌面 MCP 客户端。
安装
在 SourceWeft 中
- 打开 控制台中的 Stockmatrix Mcp,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
stockmatrix-mcp
Official MCP server for StockMatrix (https://stockmatrix.co.kr).
Ask about Korean stock market themes in natural conversation with AI. Track 200+ KOSPI/KOSDAQ investment themes, get daily movers, look up which themes a stock belongs to, compare themes side-by-side, and see predictions — all through Claude, Cursor, or any MCP-compatible AI agent.
Powered by TLI (Theme Lifecycle Index) — a Bayesian-optimized scoring algorithm combining search interest, news momentum, market volatility, and stock activity into a 0-100 score with lifecycle stage classification.
11 tools + 4 one-click workflow prompts + live resources. Try the market_briefing slash command for an instant Korean market overview.
Quick Start
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
Cursor / Windsurf
Add to .cursor/mcp.json or .windsurf/mcp.json:
VS Code / Claude Code
Add to .vscode/mcp.json:
Try Asking
After setup, just ask in natural language:
Available Tools
get_theme_ranking
Get theme rankings by lifecycle stage with limit and sort options.
get_market_summary
Get an AI-optimized market overview with top themes (includes themeId for chaining).
get_theme_changes
Get daily or weekly score movers, stage transitions, and newly emerging themes.
compare_themes
Compare 2-5 themes side-by-side with scores, stocks, sparklines, and similarity.
get_predictions
Get themes predicted to rise, peak, or cool based on historical analog matching.
search_themes
Search themes by keyword, stock name, or stock code.
search_stocks
Search stocks by company name or 6-digit code, with related theme preview. Automatically performs stock-to-theme lookup for 6-digit codes.
get_stock_themes
Reverse lookup — every theme a stock belongs to, ranked by theme score, each with lifecycle stage and the stock's relevance. Answers "is my stock in a hot theme?"
get_theme_detail
Get detailed analysis: score breakdown (4 components), stage, prediction, stocks, news, comparisons.
get_theme_history
Get 30-day score history for trend analysis.
get_methodology
Get TLI algorithm documentation — scoring, stages, stabilization, comparison, prediction, data sources, and more.
Tip: Use
section=scoringto get just the scoring algorithm and save context tokens.
Workflow Prompts
One-click slash commands (in Claude Desktop, Cursor, and other MCP clients) that run complete multi-tool analyses for you — the fastest way to get real value:
Resources
Attachable read-only context (no tool call needed):
Scoring Algorithm
TLI scores (0-100) are a weighted sum of 4 components, optimized via Bayesian Optimization:
Scores are stabilized through Cautious Decay (3-signal majority vote), Bollinger Band Clamp (limits daily change), and Age-adaptive EMA (newer themes react faster).
Lifecycle Stages
Stage transitions require 2 consecutive days of the same candidate (hysteresis) and follow Markov transition constraints.
Data Coverage
- 200+ themes across KOSPI & KOSDAQ
- Daily updates — scores, news, stock mappings
- Stock ↔ theme lookup — by company name, 6-digit code, or reverse (stock → all its themes)
- AI market summary for first-call overview
- Predictions with historical analog matching
- Workflow prompts — one-click multi-tool analyses
- Sources: Naver DataLab, Naver Finance, Naver News
Configuration
License
MIT
Links
来源:mcp/README.md,提交 8eb2c73
工具
0版本历史
1- v0.5.0最新Sep 16, 2026
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