MCP 服务器

Bitget Signal

5 crypto market analysis skills for Claude Code, Codex & OpenClaw — macro, on-chain, sentiment, technical & news. Installer deploys skills and registers the public MCP data server.

README

<h1 align="center">bitget-signal — Official Bitget AI Cryptocurrency Market Analysis Skills</h1>

Adds 5 market analysis skills to Claude Code, Codex & OpenClaw — macro policy, on-chain whale flows, sentiment indicators, technical analysis, and market news — powered by Bitget's official data. No account. No API key.

<a href="#quick-start">Quick Start</a> · <a href="#capabilities">Capabilities</a> · <a href="#installation">Installation</a> · <a href="#vs-trading">vs Trading Tools</a> · <a href="#security">Security</a> · <a href="#faq">FAQ</a>

Overview

@bitget-ai/bitget-signal is Bitget's official cryptocurrency market analysis skill package and the Signal Stack of the Bitget Agent Hub. It adds 5 market analysis skills to Claude Code, Codex, and OpenClaw, backed by Bitget's official public MCP data service.

No Bitget account. No API key. Just install and start asking about crypto markets.

Quick Start

Prerequisites

Node.js ≥ 20
Python with pandas and numpy (optional, only for the technical-analysis skill)

One-Line Install

npx @bitget-ai/bitget-signal --target all

After installation, restart your AI tool so the new skills take effect.

Verify Installation

Ask your AI: "What is the current Bitcoin Fear & Greed Index?"

If it returns data, both the skill files and the MCP data server are correctly configured.

Capabilities

Each of the 5 skills connects to a dedicated Bitget official data source. Each skill carries explicit trigger phrases so your AI assistant invokes the right one without you needing to be technical.

Ask Your AI	Skill	Powered By
"How is Fed policy affecting BTC?" · "Is BTC correlated with Nasdaq?"	`macro-analyst`	Fed policy, FOMC news, yield curve, cross-asset correlation (BTC vs Gold/DXY/Nasdaq/S&P/10Y)
"Are whales moving assets on-chain?" · "Is ETF money flowing in or out?"	`market-intel`	On-chain capital flows, ETF data, DeFi TVL, cycle indicators
"Is the market fearful or greedy?" · "Are funding rates positive?"	`sentiment-analyst`	Fear & Greed Index, long/short ratio, OI, funding rates, taker ratio, Reddit signals
"Is BTC RSI overbought?" · "Where's the support level?"	`technical-analysis`	23 indicators across 6 categories (trend, volatility, oscillator, volume, momentum, support/resistance)
"What's important in crypto today?"	`news-briefing`	44 RSS/Atom feeds, social trending boards, narrative synthesis

The technical-analysis skill requires a local Python environment (pandas, numpy). The other four skills do not need Python.

Installation

Step 1: Install Skills

# All supported AI tools (Claude Code + Codex + OpenClaw)
npx @bitget-ai/bitget-signal --target all

# Default — Claude Code only
npx @bitget-ai/bitget-signal

# Specific targets
npx @bitget-ai/bitget-signal --target claude,codex

# Interactive picker
npx @bitget-ai/bitget-signal --interactive

What the installer does, in order:

Copies the five skill folders into your AI tool's skill directory.
Registers the public bitget-signal MCP server (HTTP transport) in your tool's MCP config.

Target	Skill location	MCP config
Claude Code	`~/.claude/skills/`	via `claude mcp add`
Codex	`~/.codex/skills/`	written to `~/.codex/config.toml`
OpenClaw	`~/.openclaw/skills/`	written to `~/.openclaw/config.json`

Step 2: Restart AI Tool

Close and reopen your AI tool to load the new skills and MCP server.

Step 3: Test

Ask your AI: "What is the current Bitcoin Fear & Greed Index?"

Expected: returns the current index value with interpretation.

What's a skill, and what's the MCP server?

bitget-signal is two things bundled:

The five skill files — markdown that teaches your AI assistant what each skill does and when to invoke it. Pure text, no runtime process.
An MCP server registration — your AI host gets pointed at Bitget's public market-data MCP (HTTP transport). When the AI calls a tool, the request goes to the public server and results come back. No proxy through your machine, no credentials needed.

The skills are the prompt; the MCP server is the tools. The installer wires up both in one command.

How It Differs from Trading Tools

	`bitget-signal` (this package)	`bitget-agent-skill` (trading)
Purpose	Analyze market data	Trade on your Bitget account
Requires `bitget-agent-cli`?	No — runs standalone	Yes — must be installed together
Requires API key?	No	Yes (your Bitget credentials)
Triggers on	"Is BTC overbought?" · "Whale flows" · "Fed policy"	"Buy / sell / check positions / cancel order"

Both can be installed side by side — use bitget-signal to analyze, then bitget-agent-skill + bitget-agent-cli to act.

Coming Next: Bitget-Exclusive Signals

Beyond generic skills, bitget-signal will ship signals only Bitget can produce — built directly from Bitget's exchange data:

top-trader-flow — aggregated, anonymised positioning of Bitget's top copy-trading leaders.
derivatives-structure — perp basis, term structure, and funding-rate curve from Bitget's orderbook.
large-flow-detect — whale-sized order detection on Bitget pairs in real time.

These will ship as additional skills inside this same package — no reinstall required.

Security

✅ No credentials required: accesses only public market data — no Bitget account or API key.
✅ MCP server maintained by Bitget: data delivered via Bitget's public MCP service over HTTP.
✅ Skill files have no runtime process: pure Markdown, no local resource consumption.

Migration from Old Package Names

If you previously installed under an older name:

- npm install -g bitget-skill-hub          # deprecated
- npm install -g bitget-ai-analyst         # deprecated
+ npx @bitget-ai/bitget-signal             # canonical name

Also remove the old market-data MCP entry from your AI host config — the new install registers the server under the name bitget-signal.

Updates

Re-running the installer is idempotent: it refreshes the skill files and skips any MCP entry that is already configured.

npx @bitget-ai/bitget-signal --target all

Related Projects

Package	Purpose
bitget-agent-cli	Terminal AI trading tool
bitget-agent-skill	AI reasoning guide for trading
bitget-agent-sdk	SDK for building Bitget trading agents
bitget-agent-mcp	Desktop AI MCP server
agent_hub	Ecosystem entry point

FAQ

What is bitget-signal?

bitget-signal is Bitget's official cryptocurrency market analysis skill package for Claude Code, Codex, and OpenClaw. It provides 5 natural language analysis skills covering macro policy, on-chain flows, sentiment, technical indicators, and market news. No account or API key required.

Can I get Bitget market data without an API key?

Yes. bitget-signal accesses only public market data — no Bitget account or API key required.

How do I install?

Run npx @bitget-ai/bitget-signal --target all, then restart your AI tool.

Does technical analysis need Python?

The technical-analysis skill requires pandas and numpy. The other four skills do not need Python.

Is the data officially from Bitget?

Yes. Market data is provided and maintained by Bitget, delivered via a public MCP service.

Can I use this alongside trading tools?

Absolutely — and recommended. Use bitget-signal to analyze, then bitget-agent-skill + bitget-agent-cli to trade.

What analysis dimensions does this cover?

Five dimensions: macro policy, on-chain intelligence, market sentiment, technical analysis (23 indicators), and market news (44 sources).

How do I verify the skill is working?

After restarting your AI tool, ask: "What is the current Bitcoin Fear & Greed Index?" If it returns data, setup is correct.

How do I update?

See the Updates section above.

Is it free?

Yes. MIT-licensed and free. The data backend is maintained by Bitget at no cost.

License

MIT License — free for personal and commercial use.

Official Bitget Agent Hub tool · Signal Stack. Market analysis content is for informational purposes only and does not constitute investment advice. Cryptocurrency markets carry risk.

Part of the Bitget Agent Hub ecosystem · Built for traders, analysts, and AI enthusiasts.