tickdb-unified-realtime-marketdata-api: TickDB: AI-native real time stock API and market data API for US/HK/CN stocks, forex, futures, crypto, indices

by TickDB · MCP Server · ★ 916

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 67/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentscli-toolcommoditiesfinancial-analysisfinancial-dataforexfuturesindicesmarket-datamcp

Quick Facts

Stars916
Forks16
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score67/100
Open Issues2
Last Updated2026-11-06
Created2026-01-11
Platformscli, mcp, python
Est. Tokens~15k

About tickdb-unified-realtime-marketdata-api

TickDB — Unified Real-time Market Data API for Forex, Stocks, Crypto One connection for Forex, Precious Metals, Indices, US Stocks, HK Stocks, A-Shares, and Crypto 开源工具集 · 完整 API 文档 + AI Skill + MCP 服务端实现 语言版本: 🇨🇳 简体中文 • 🇹🇼 繁體中文 • 🇺🇸 English 📚 在线文档 • 🌐 官网 • 🤖 AI 接入 ↓ 🎯 什么是 TickDB? TickDB 是面向开发者、AI 代理和多市场金融应用的 AI 原生实时行

Compatible Skills

These tools work well together with tickdb-unified-realtime-marketdata-api for enhanced workflows:

  • mcp_massive — semantic(0.54)+rare_topics+same_lang+similar_pop+shared_platform (68%)
  • DeepEye — semantic(0.19)+complementary+same_lang+similar_pop+shared_platform (57%)
  • hhxg-top-hhxg-python — semantic(0.18)+complementary+rare_topics+same_lang+similar_pop+shared_platform (56%)
  • anysearch-skill — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • grok-bridge — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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