Which integrations are available for this server?

Utilizes Binance as a data source for technical analysis indicators including RSI, MACD, and Moving Averages to score crypto assets. Integrates with the Coinbase CDP Facilitator to handle automated USDC micropayments on the Base network via the x402 protocol. Aggregates sentiment and trending data from Google News to inform the narrative dimension of crypto signal scoring. Provides dedicated signal intelligence, performance tracking, and multi-dimensional analysis for the NEAR protocol. Monitors Reddit for mentions and trending discussions to calculate narrative-based sentiment scores for crypto assets. Delivers composite signal scores and market intelligence dimensions specifically for the SUI ecosystem. Offers intelligence tracking and signal scoring for XRP, incorporating whale movements and technical indicators.

Web3 Signals MCP

Crypto signal intelligence for AI agents. 5 data dimensions, 20 assets, refreshed every 15 minutes.

Version: 0.1.0 Live API: https://web3-signals-api-production.up.railway.app MCP Endpoint: https://web3-signals-api-production.up.railway.app/mcp/sse Dashboard: web3-signals-api-production.up.railway.app/dashboard

What It Is

A signal fusion engine that scores 20 crypto assets from 0-100 by combining 5 independent data agents:

Agent	Weight	Sources
Whale	30%	On-chain flows, exchange movements, large transactions
Technical	25%	RSI, MACD, Moving Averages (Binance)
Derivatives	20%	Funding rate, open interest, long/short ratio
Narrative	15%	Reddit, Google News, CoinGecko trending, LLM sentiment
Market	10%	Price, volume, Fear & Greed Index

Each agent runs every 15 minutes. Scores are fused into a composite signal with directional labels (STRONG BUY to STRONG SELL), momentum tracking, and LLM-generated cross-dimensional insights.

What Problem It Solves

AI agents and trading systems need structured, multi-dimensional crypto intelligence — not raw price feeds. This API delivers scored, opinionated signals that combine what whales are doing, what derivatives markets are pricing, what the crowd is saying, and what technicals show — fused into a single actionable score with an LLM explanation of why.

Target Horizon

Signal refresh: Every 15 minutes
Accuracy evaluation: 24h, 48h windows
Best for: Swing trades (hours to days), portfolio risk monitoring, market regime detection
Not designed for: Sub-minute scalping or HFT

Assets Covered

BTC ETH SOL BNB XRP ADA AVAX DOT MATIC LINK UNI ATOM LTC FIL NEAR APT ARB OP INJ SUI

Connect via MCP

Add to your MCP config (Claude Desktop, Cursor, Windsurf, etc.):

{
  "mcpServers": {
    "web3-signals": {
      "url": "https://web3-signals-api-production.up.railway.app/mcp/sse"
    }
  }
}

Then ask your AI: "What are the current crypto signals?" or "Get me the BTC signal"

MCP Tools

Tool	Description
`get_all_signals`	Full portfolio: 20 scored signals + portfolio summary + LLM insights
`get_asset_signal`	Single asset signal with market context
`get_health`	Agent status, last run times, error counts
`get_performance`	Rolling 30-day accuracy across 24h/48h timeframes
`get_asset_performance`	Per-asset accuracy breakdown

REST API

Endpoints

Endpoint	Description
`GET /signal`	All 20 asset signals with portfolio summary
`GET /signal/{asset}`	Single asset signal (e.g. `/signal/BTC`)
`GET /performance/reputation`	30-day rolling accuracy score
`GET /performance/{asset}`	Per-asset accuracy breakdown
`GET /health`	Agent status and uptime
`GET /analytics`	API usage analytics
`GET /api/history`	Historical signal runs (paginated)
`GET /docs`	OpenAPI documentation
`GET /dashboard`	Live signal intelligence dashboard

Example: Single Asset Signal

curl https://web3-signals-api-production.up.railway.app/signal/BTC

{
  "asset": "BTC",
  "timestamp": "2026-02-24T21:49:42.513414+00:00",
  "signal": {
    "composite_score": 31.7,
    "label": "MODERATE SELL",
    "direction": "sell",
    "dimensions": {
      "whale": {
        "score": 7.9,
        "label": "STRONG SELL",
        "detail": "25 accumulate, 33 sell (ratio 43%); exchange inflow",
        "weight": 0.3
      },
      "technical": {
        "score": 35.2,
        "label": "MODERATE SELL",
        "detail": "RSI 30; MACD bullish; trend bearish",
        "weight": 0.25
      },
      "derivatives": {
        "score": 25.0,
        "label": "STRONG SELL",
        "detail": "L/S 0.69",
        "weight": 0.2
      },
      "narrative": {
        "score": 63.5,
        "label": "MODERATE BUY",
        "detail": "vol 0.97 (106 mentions); LLM neutral; trending; 3 sources",
        "weight": 0.15
      },
      "market": {
        "score": 60.0,
        "label": "MODERATE BUY",
        "detail": "-0.8%; F&G 8 extreme fear",
        "weight": 0.1
      }
    },
    "momentum": "degrading",
    "prev_score": 42.1,
    "llm_insight": "Whale capitulation intensifying — 33 sellers dominating with exchange inflow. Derivatives flipped to strong sell. Divergence: narrative and market fear remain bullish, suggesting classic capitulation setup..."
  },
  "market_context": {
    "regime": "extreme_fear",
    "risk_level": "high",
    "signal_momentum": "degrading"
  }
}

Example: Portfolio Summary

curl https://web3-signals-api-production.up.railway.app/signal

{
  "status": "success",
  "timestamp": "2026-02-24T21:49:42+00:00",
  "data": {
    "portfolio_summary": {
      "top_buys": [
        {"asset": "ETH", "score": 53.2, "label": "NEUTRAL", "conviction": "moderate"},
        {"asset": "SUI", "score": 50.7, "label": "NEUTRAL", "conviction": "moderate"},
        {"asset": "DOT", "score": 49.4, "label": "NEUTRAL", "conviction": "moderate"}
      ],
      "top_sells": [
        {"asset": "SOL", "score": 36.9, "label": "MODERATE SELL"},
        {"asset": "XRP", "score": 34.0, "label": "MODERATE SELL"},
        {"asset": "BTC", "score": 31.7, "label": "MODERATE SELL"}
      ],
      "market_regime": "extreme_fear",
      "risk_level": "high",
      "signal_momentum": "degrading",
      "assets_improving": 0,
      "assets_degrading": 6
    },
    "signals": {
      "BTC": { "composite_score": 31.7, "label": "MODERATE SELL", "..." : "..." },
      "ETH": { "composite_score": 53.2, "label": "NEUTRAL", "..." : "..." }
    }
  }
}

Example: Performance / Reputation

curl https://web3-signals-api-production.up.railway.app/performance/reputation

{
  "status": "active",
  "reputation_score": 72,
  "accuracy_30d": 72.3,
  "signals_evaluated": 840,
  "signals_correct": 607,
  "by_timeframe": {
    "24h": {"total": 280, "hits": 196, "accuracy": 70.0},
    "48h": {"total": 280, "hits": 201, "accuracy": 71.8},
    "7d":  {"total": 280, "hits": 210, "accuracy": 75.0}
  },
  "by_asset": {
    "BTC": 75.0,
    "ETH": 70.0,
    "SOL": 68.5
  },
  "methodology": {
    "direction_extraction": "score >60 = bullish, <40 = bearish, 40-60 = neutral",
    "neutral_threshold": "price move <=2% = correct for neutral signals",
    "scoring": "binary (hit/miss)",
    "window": "30-day rolling",
    "timeframes": ["24h", "48h"],
    "price_source": "CoinGecko"
  }
}

Signal Labels

Score Range	Label	Direction
80-100	STRONG BUY	bullish
60-79	MODERATE BUY	bullish
40-59	NEUTRAL	neutral
20-39	MODERATE SELL	bearish
0-19	STRONG SELL	bearish

Performance Tracking

The system tracks its own signal accuracy — no self-reported claims:

Snapshots captured every 12 hours (1 per asset, max 40/day)
Evaluation at 24h and 48h windows against actual price movement
Direction match: Did the predicted direction (bullish/bearish/neutral) match the actual price move?
Neutral threshold: Price move <=2% counts as correct for neutral signals
Price source: CoinGecko (independent, no API key needed)
Window: 30-day rolling, recalculated every evaluation cycle

Discovery Protocols

Protocol	Endpoint	Standard
x402	`/signal`, `/signal/{asset}`	HTTP 402 Micropayments (Coinbase)
MCP SSE	`/mcp/sse`	Model Context Protocol (Anthropic)
A2A	`/.well-known/agent.json`	Agent-to-Agent (Google)
AGENTS.md	`/.well-known/agents.md`	Agentic AI Foundation
OpenAPI	`/docs`	OpenAPI 3.0

x402 Micropayments

Payment IS authentication. No API keys, no signup, no OAuth.

AI agents pay $0.001 USDC per call on Base mainnet. The x402 protocol handles discovery, payment, and settlement automatically via the Coinbase CDP Facilitator.

Paid Endpoints ($0.001/call)

Endpoint	What you get
`GET /signal`	All 20 signals + portfolio summary + LLM insights
`GET /signal/{asset}`	Single asset signal with 5 dimensions
`GET /performance/reputation`	30-day rolling accuracy score

Free Endpoints

/health, /dashboard, /analytics, /docs, /.well-known/*, /mcp/sse

How it works

Agent calls GET /signal → gets 402 Payment Required with payment instructions
Agent signs USDC payment on Base → retries with PAYMENT-SIGNATURE header
Facilitator verifies payment → endpoint returns data
Settlement happens on-chain in <2 seconds

Agents using x402-compatible clients (Otto, Questflow, Fluora, Oops!402) handle this automatically.

Project Structure

/api                  FastAPI server, dashboard, middleware
/mcp_server           MCP tool definitions (stdio + SSE)
/signal_fusion        Weighted score fusion engine
/whale_agent          On-chain flow tracking
/technical_agent      RSI, MACD, MA analysis
/derivatives_agent    Funding rate, OI, L/S ratio
/narrative_agent      Reddit, News, Trending, LLM sentiment
/market_agent         Price, volume, Fear & Greed
/shared               Storage layer, base agent, profile loader
/orchestrator         15-minute agent runner
README.md
AGENTS.md

Self-Hosting

git clone https://github.com/manavaga/web3-signals-mcp.git
cd web3-signals-mcp

cp .env.example .env
# Edit .env with your API keys

pip install -r requirements.txt
python -m api.server

Environment Variables

Variable	Required	Description
`REDDIT_CLIENT_ID`	Yes	Reddit API credentials
`REDDIT_CLIENT_SECRET`	Yes	Reddit API secret
`ANTHROPIC_API_KEY`	No	Enables LLM insights (Claude Haiku)
`DATABASE_URL`	No	Postgres URL (falls back to SQLite)
`PORT`	No	Server port (default: 8000)

Roadmap

Near-term (building now)

Calibration buckets — Group signals by score range (e.g. 70-80) and track accuracy per bucket. Answers: "When we say 75, how often is that actually bullish?" (needs 24h+ of accuracy data)
Magnitude scoring — Move beyond binary hit/miss to measure how much the predicted move captured vs actual move. (needs 1 week of data)

Medium-term

Confidence-weighted penalties — Penalize high-conviction misses more than low-conviction ones. A "STRONG BUY" that dumps should hurt reputation more than a "MODERATE BUY" that goes flat. (needs calibration data)
Correlation vs BTC baseline — Compare signal accuracy against a naive "just follow BTC" strategy. If we can't beat that, the signal isn't adding value. (needs 30 days of data)

Future

x402 micropayments — Pay-per-signal via HTTP 402
Additional assets — Expand beyond 20
More data sources — Twitter/X, Farcaster, CryptoPanic (currently disabled, pending API access)

License

MIT

Web3 Signals — Crypto Signal Intelligence