Imported from reason-machines/mcp-skills (skills/opennews-mcp-news-aggregation/SKILL.md). Install upstream with npx skills add reason-machines/mcp-skills --skill opennews-mcp-news-aggregation. Copyright stays with the author.

OpenNews MCP News Aggregation

Skill by ara.so — MCP Skills collection.

OpenNews MCP is a Model Context Protocol server providing real-time access to 84+ crypto and financial news sources across 6 categories (News, Listing, OnChain, Meme, Market, Prediction). Every article includes AI-powered impact scores (0-100), trading signals (long/short/neutral), and bilingual summaries.

Installation

Prerequisites

Get your API token from https://6551.io/mcp
Set the token as an environment variable:

export OPENNEWS_TOKEN="your-token-here"

Claude Desktop

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "opennews": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/opennews-mcp",
        "run",
        "opennews-mcp"
      ],
      "env": {
        "OPENNEWS_TOKEN": "your-token-here"
      }
    }
  }
}

Using `claude mcp add`

claude mcp add opennews \
  -e OPENNEWS_TOKEN=your-token-here \
  -- uv --directory /path/to/opennews-mcp run opennews-mcp

OpenClaw

export OPENNEWS_TOKEN="your-token-here"
cp -r openclaw-skill/opennews ~/.openclaw/skills/

Configuration

The server supports both environment variables and a config.json file in the project root. Environment variables take precedence.

Environment Variables

Variable	Required	Default	Description
`OPENNEWS_TOKEN`	Yes	-	API Bearer Token from 6551.io
`OPENNEWS_API_BASE`	No	`https://ai.6551.io`	REST API base URL
`OPENNEWS_WSS_URL`	No	`wss://ai.6551.io/open/news_wss`	WebSocket URL
`OPENNEWS_MAX_ROWS`	No	`100`	Max results per request

config.json

{
  "api_base_url": "https://ai.6551.io",
  "wss_url": "wss://ai.6551.io/open/news_wss",
  "api_token": "your-token-here",
  "max_rows": 100
}

Data Sources Overview

The platform aggregates 84+ sources across 6 engine types:

news (53 sources): Bloomberg, Reuters, Financial Times, CNBC, CoinDesk, Cointelegraph, The Block, Twitter/X, Telegram, and more
listing (9 sources): Binance, Coinbase, OKX, Bybit, Upbit, Robinhood, Hyperliquid listings
onchain (3 sources): Hyperliquid whale trades, large positions, KOL trades
meme (1 source): Twitter meme coin sentiment
market (6 sources): Price changes, funding rates, liquidations, OI changes
prediction (12 sources): AI correlation, smart money, whale positions, insider patterns

Available Tools

Discovery Tools

`get_news_sources`

Retrieves the complete engine tree with all categories and sources.

# Returns hierarchical structure of all 6 engine types and their sources
# Each source includes metadata like description and type

Response structure:

{
  "news": {
    "Bloomberg": {"description": "Bloomberg — top-tier financial news"},
    "CoinDesk": {"description": "CoinDesk — leading crypto media"}
  },
  "listing": {
    "Binance": {"description": "Binance new token listings"}
  },
  "onchain": {
    "Hyperliquid Whale Trade": {"description": "Hyperliquid whale trade alerts"}
  }
}

`list_news_types`

Returns a flat list of all available source codes for filtering.

# Returns array of all source codes across all engine types
# Use these codes in other tool filters

Response:

["Bloomberg", "Reuters", "CoinDesk", "Binance", "Hyperliquid Whale Trade", ...]

Search Tools

`get_latest_news`

Fetch the most recent articles across all sources.

Parameters:

limit (optional, default: 20): Number of articles to return

# Get latest 50 articles
{"limit": 50}

`search_news`

Full-text keyword search across all sources.

Parameters:

keywords (required): Search query string
limit (optional, default: 20): Number of results

# Search for SEC-related news
{"keywords": "SEC regulation", "limit": 30}

`search_news_by_coin`

Filter articles by specific cryptocurrencies.

Parameters:

coins (required): Array of coin symbols (e.g., ["BTC", "ETH"])
limit (optional, default: 20): Number of results

# Get Bitcoin and Ethereum news
{"coins": ["BTC", "ETH"], "limit": 40}

`get_news_by_source`

Filter by specific source within an engine type.

Parameters:

engine_type (required): Engine category (news, listing, onchain, meme, market, prediction)
news_type (required): Specific source code (e.g., Bloomberg, Binance)
limit (optional, default: 20): Number of results

# Get Bloomberg news only
{"engine_type": "news", "news_type": "Bloomberg", "limit": 25}

# Get Binance listings
{"engine_type": "listing", "news_type": "Binance", "limit": 10}

`get_news_by_engine`

Filter articles by engine category.

Parameters:

engine_type (required): Engine category
limit (optional, default: 20): Number of results

# Get all on-chain events
{"engine_type": "onchain", "limit": 30}

# Get all prediction signals
{"engine_type": "prediction", "limit": 50}

`search_news_advanced`

Multi-filter search combining coins, keywords, and engine types.

Parameters:

coins (optional): Array of coin symbols
keywords (optional): Search query
engine_types (optional): Array of engine categories
limit (optional, default: 20): Number of results

# Bitcoin news from Bloomberg and CoinDesk mentioning "ETF"
{
  "coins": ["BTC"],
  "keywords": "ETF",
  "engine_types": ["news"],
  "limit": 30
}

# Whale activity for SOL and ETH
{
  "coins": ["SOL", "ETH"],
  "engine_types": ["onchain"],
  "limit": 20
}

AI-Powered Tools

`get_high_score_news`

Retrieve articles with high AI impact scores.

Parameters:

min_score (optional, default: 80): Minimum impact score (0-100)
limit (optional, default: 20): Number of results

# Get articles with score >= 90
{"min_score": 90, "limit": 15}

# Get articles with score >= 70
{"min_score": 70, "limit": 30}

`get_news_by_signal`

Filter by AI-generated trading signals.

Parameters:

signal (required): Trading signal type (long, short, neutral)
limit (optional, default: 20): Number of results

# Get bullish signals
{"signal": "long", "limit": 25}

# Get bearish signals
{"signal": "short", "limit": 25}

# Get neutral signals
{"signal": "neutral", "limit": 20}

Real-Time Tools

`subscribe_latest_news`

Subscribe to WebSocket live feed with optional filters.

Parameters:

engine_types (optional): Object mapping engine types to source codes
- Key: Engine type (news, listing, onchain, etc.)
- Value: Array of source codes (empty array = all sources in that engine)
coins (optional): Array of coin symbols
has_coin (optional, boolean): Only articles tagged with coins

# Subscribe to Bloomberg and CoinDesk for BTC and ETH
{
  "engine_types": {
    "news": ["Bloomberg", "CoinDesk"]
  },
  "coins": ["BTC", "ETH"],
  "has_coin": True
}

# Subscribe to all listing announcements
{
  "engine_types": {
    "listing": []
  }
}

# Subscribe to whale on-chain activity
{
  "engine_types": {
    "onchain": []
  }
}

WebSocket message format (incoming):

{
  "jsonrpc": "2.0",
  "method": "news.update",
  "params": {
    "id": "article-id",
    "title": "Article title",
    "content": "Full article text",
    "engine_type": "news",
    "news_type": "Bloomberg",
    "coins": ["BTC"],
    "ai_score": 85,
    "ai_signal": "long",
    "summary_en": "English summary",
    "summary_zh": "中文摘要",
    "published_at": "2026-05-16T12:00:00Z"
  }
}

Response Data Structure

All news articles follow this structure:

{
  "id": "unique-article-id",
  "title": "Article headline",
  "content": "Full article text content",
  "engine_type": "news",
  "news_type": "Bloomberg",
  "coins": ["BTC", "ETH"],
  "ai_score": 85,
  "ai_signal": "long",
  "summary_en": "English AI-generated summary",
  "summary_zh": "中文AI生成摘要",
  "published_at": "2026-05-16T10:30:00Z",
  "url": "https://original-source.com/article",
  "metadata": {
    "author": "Jane Doe",
    "tags": ["regulation", "ETF"]
  }
}

Key fields:

ai_score (0-100): AI impact score, higher = more market-moving
ai_signal: Trading direction (long, short, neutral)
coins: Array of related cryptocurrency symbols
engine_type: Category (news, listing, onchain, meme, market, prediction)
news_type: Specific source code

Common Usage Patterns

Pattern 1: Monitor High-Impact News

# Get latest high-impact news (score >= 80)
result = get_high_score_news(min_score=80, limit=10)

# Filter for bullish signals only
bullish = get_news_by_signal(signal="long", limit=15)

# Combine: high-impact bullish Bitcoin news
advanced = search_news_advanced(
    coins=["BTC"],
    engine_types=["news", "prediction"],
    limit=20
)
# Then filter results where ai_score >= 80 and ai_signal == "long"

Pattern 2: Track Specific Assets

# Get all Solana-related news
sol_news = search_news_by_coin(coins=["SOL"], limit=30)

# Get Solana on-chain whale activity
sol_onchain = search_news_advanced(
    coins=["SOL"],
    engine_types=["onchain"],
    limit=15
)

# Get Solana listings across all exchanges
sol_listings = search_news_advanced(
    coins=["SOL"],
    engine_types=["listing"],
    limit=10
)

Pattern 3: Source-Specific Monitoring

# Get all Bloomberg articles
bloomberg = get_news_by_source(
    engine_type="news",
    news_type="Bloomberg",
    limit=25
)

# Get Binance listing announcements
binance_listings = get_news_by_source(
    engine_type="listing",
    news_type="Binance",
    limit=10
)

# Get Hyperliquid whale trades
whale_trades = get_news_by_source(
    engine_type="onchain",
    news_type="Hyperliquid Whale Trade",
    limit=20
)

Pattern 4: Real-Time Alerts

# Subscribe to critical sources for BTC and ETH
subscribe_latest_news(
    engine_types={
        "news": ["Bloomberg", "Reuters", "Financial Times"],
        "listing": ["Binance", "Coinbase"],
        "onchain": []  # All on-chain sources
    },
    coins=["BTC", "ETH"],
    has_coin=True
)

# Subscribe to all prediction signals
subscribe_latest_news(
    engine_types={
        "prediction": []
    }
)

Pattern 5: Thematic Research

# Research regulation topics
regulation_news = search_news(
    keywords="SEC regulation compliance",
    limit=40
)

# ETF-related news with high impact
etf_news = search_news(keywords="ETF", limit=30)
# Filter for ai_score >= 75

# Institutional adoption signals
institutional = search_news(
    keywords="institutional adoption grayscale blackrock",
    limit=25
)

WebSocket Direct Usage

For applications needing direct WebSocket access:

import json
import websockets
import asyncio
import os

async def subscribe_news():
    token = os.getenv("OPENNEWS_TOKEN")
    url = f"wss://ai.6551.io/open/news_wss?token={token}"
    
    async with websockets.connect(url) as ws:
        # Subscribe to specific filters
        subscribe_msg = {
            "jsonrpc": "2.0",
            "id": 1,
            "method": "news.subscribe",
            "params": {
                "engineTypes": {
                    "news": ["Bloomberg", "CoinDesk"],
                    "listing": []
                },
                "coins": ["BTC", "ETH"],
                "hasCoin": True
            }
        }
        
        await ws.send(json.dumps(subscribe_msg))
        
        # Receive confirmation
        response = await ws.recv()
        print(f"Subscription confirmed: {response}")
        
        # Listen for updates
        async for message in ws:
            data = json.loads(message)
            if data.get("method") == "news.update":
                article = data["params"]
                print(f"New article: {article['title']}")
                print(f"AI Score: {article['ai_score']}")
                print(f"Signal: {article['ai_signal']}")

Troubleshooting

Authentication Errors

Problem: 401 Unauthorized or Invalid token

Solution:

Verify token is correct from https://6551.io/mcp
Check environment variable is set: echo $OPENNEWS_TOKEN
Ensure token has no extra spaces or quotes
For Claude Desktop, restart the app after config changes

No Results Returned

Problem: Empty results or []

Solution:

Check if filters are too restrictive (e.g., coin doesn't have recent news)
Increase limit parameter
Verify engine_type and news_type codes with list_news_types
Try broader search (e.g., use get_latest_news first)

WebSocket Connection Issues

Problem: Connection fails or disconnects

Solution:

Verify token is included in URL query parameter
Check network allows WebSocket connections (corporate firewalls)
Implement reconnection logic with exponential backoff
Validate subscription message format matches JSON-RPC 2.0

Rate Limiting

Problem: 429 Too Many Requests

Solution:

Reduce request frequency
Use WebSocket subscriptions instead of polling
Implement request queuing with delays
Contact support for higher rate limits if needed

Unexpected Data Format

Problem: Missing fields or unexpected values

Solution:

Not all articles have coins array (check has_coin filter)
ai_score and ai_signal are always present but may be null
metadata object is optional and varies by source
Always validate fields exist before accessing

Example Integration Workflows

Daily Digest Builder

# Get top 10 highest impact articles from past 24 hours
high_impact = get_high_score_news(min_score=85, limit=10)

# Group by signal
bullish = [a for a in high_impact if a['ai_signal'] == 'long']
bearish = [a for a in high_impact if a['ai_signal'] == 'short']

# Format digest
print("📈 Bullish Signals:")
for article in bullish:
    print(f"  • {article['title']} (Score: {article['ai_score']})")

print("\n📉 Bearish Signals:")
for article in bearish:
    print(f"  • {article['title']} (Score: {article['ai_score']})")

Exchange Listing Tracker

# Get all recent listings
listings = get_news_by_engine(engine_type="listing", limit=50)

# Group by exchange
by_exchange = {}
for article in listings:
    exchange = article['news_type']
    if exchange not in by_exchange:
        by_exchange[exchange] = []
    by_exchange[exchange].append(article)

# Display
for exchange, articles in by_exchange.items():
    print(f"\n{exchange} ({len(articles)} listings):")
    for a in articles:
        coins = ', '.join(a.get('coins', []))
        print(f"  • {coins}: {a['title']}")

Smart Money Tracker

# Combine prediction signals with on-chain data
predictions = get_news_by_engine(engine_type="prediction", limit=30)
onchain = get_news_by_engine(engine_type="onchain", limit=30)

# Filter for high-confidence smart money signals
smart_money = [
    p for p in predictions 
    if p['news_type'] == 'SMART_MONEY_TRADE' and p['ai_score'] >= 80
]

# Cross-reference with whale activity
whale_coins = set()
for article in onchain:
    whale_coins.update(article.get('coins', []))

# Find overlap
for signal in smart_money:
    signal_coins = signal.get('coins', [])
    overlap = set(signal_coins) & whale_coins
    if overlap:
        print(f"⚡ Smart money + whale activity: {', '.join(overlap)}")
        print(f"   {signal['summary_en']}")

About

OpenNews MCP News Aggregation

Installation

Prerequisites

Claude Desktop

Using claude mcp add

OpenClaw

Configuration

Environment Variables

config.json

Data Sources Overview

Available Tools

Discovery Tools

get_news_sources

list_news_types

Search Tools

get_latest_news

search_news

search_news_by_coin

get_news_by_source

get_news_by_engine

search_news_advanced

AI-Powered Tools

get_high_score_news

get_news_by_signal

Real-Time Tools

subscribe_latest_news

Response Data Structure

Common Usage Patterns

Pattern 1: Monitor High-Impact News

Pattern 2: Track Specific Assets

Pattern 3: Source-Specific Monitoring

Pattern 4: Real-Time Alerts

Pattern 5: Thematic Research

WebSocket Direct Usage

Troubleshooting

Authentication Errors

No Results Returned

WebSocket Connection Issues

Rate Limiting

Unexpected Data Format

Example Integration Workflows

Daily Digest Builder

Exchange Listing Tracker

Smart Money Tracker

Use it

Manifest

Reviews

Using `claude mcp add`

`get_news_sources`

`list_news_types`

`get_latest_news`

`search_news`

`search_news_by_coin`

`get_news_by_source`

`get_news_by_engine`

`search_news_advanced`

`get_high_score_news`

`get_news_by_signal`

`subscribe_latest_news`