tradingview-mcp

TradingView MCP server — real-time market data, technical analysis, screeners & backtesting for Claude, ChatGPT, Cursor & any MCP client. Stocks, crypto, forex & futures across global exchanges. Hosted or self-host.

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TradingView MCP — Market Data & Technical Analysis for AI Assistants

TradingView MCP server — real-time market data, technical indicators, screeners, and backtesting for Claude, ChatGPT, Cursor, Copilot, and any MCP client. Stocks, crypto, forex & futures across global exchanges.
Backtesting + live sentiment + Yahoo Finance + 30+ technical-analysis tools — the most complete TradingView MCP toolkit, all in one server.

[!NOTE]
Independent open-source project — not affiliated with, endorsed by, or associated with TradingView Inc. "TradingView" is a trademark of its respective owner; this project consumes third-party market data and is not a TradingView product.

[!IMPORTANT]
Not financial advice. Nothing produced by this software is investment, financial, legal, tax, or accounting advice. tradingview-mcp is an informational and educational analysis tool. Its outputs, including indicators, scores, signals, "trade setups", entries, stop losses, and targets, are computed from third party market data and are not recommendations to buy, sell, or hold any asset. It does not execute trades, manage money, or guarantee any result. Trading and investing carry a substantial risk of loss, and you can lose some or all of your capital. Always do your own research and consult a licensed professional before making any financial decision. You are solely responsible for your own decisions and for complying with the laws and regulations that apply to you. Market data may be delayed, inaccurate, or incomplete, and is provided without warranty.

[!TIP]
Skip the setup. Use the hosted version. pro.cryptosieve.com gives you all 30+ tools as one connector URL for Claude.ai, ChatGPT, Copilot, and Cursor. No uv, pandas, or Python to wrangle. $9 per month, with a 3 day free trial. Self hosting stays free forever; the hosted plan is just for folks who would rather skip the ops.

⭐ If this tool improves your workflow, please star the repo and consider sponsoring — it keeps the project alive and growing!

🎥 Framework Demo

https://github-production-user-asset-6210df.s3.amazonaws.com/67838093/478689497-4a605d98-43e8-49a6-8d3a-559315f6c01d.mp4

🆕 What's New

Stability & Strategy Expansion (May 2026)

9 backtest strategies (up from 6) — added rsi_pullback, keltner_breakout, and triple_ema, covering trend-pullback, ATR-normalized breakout, and SMA200-filtered EMA cross edges. compare_strategies now ranks the full 9.
Resilience layer — automatic retry + 60-second TTL cache on the TradingView screener provider, eliminating transient "Expecting value" errors on combined_analysis and multi_timeframe_analysis. (PR #32 — merged)
Financial news service rebuild — replaces deprecated Reuters RSS endpoints with Yahoo Finance, MarketWatch, and CNBC. Fixes the long-standing count: 0 bug on financial_news. (PR #33 — merged)
TA throttle — caps concurrent tradingview_ta calls (default 4) + min 0.8s spacing between starts. Prevents parallel bursts of combined_analysis / multi_timeframe_analysis from hitting TradingView's empty-body rate-limit cliff. Tunable via env vars. (PR #34 — merged)
Walk-forward backtesting (walk_forward_backtest_strategy) — train/test split with overfitting verdict (ROBUST / MODERATE / WEAK / OVERFITTED).
Hourly (1h) timeframe support across backtest_strategy, compare_strategies, and walk_forward_backtest_strategy.
Full trade log + equity curve outputs (include_trade_log=True, include_equity_curve=True).

🏗️ Architecture

tradingview-mcp Architecture

✨ Why tradingview-mcp?

Feature	`tradingview-mcp`	Traditional Setups	Bloomberg Terminal
Setup Time	5 minutes	Hours (Docker, Conda...)	Weeks (Contracts)
Cost	Free & Open Source	Variable	$30k+/year
Backtesting	✅ 9 strategies + Walk-forward + Sharpe	❌ Manual scripting	✅ Proprietary
Live Sentiment	✅ Reddit + RSS news	❌ Separate setup	✅ Terminal
Market Data	✅ Live / Real-Time	Historical / Delayed	Live
API Keys	None required	Multiple (OpenAI, etc.)	N/A

🚀 Quick Start (5 Minutes)

Install via pip

pip install tradingview-mcp-server

Claude Desktop Config (`claude_desktop_config.json`)

Note: On macOS, GUI apps like Claude Desktop may not have ~/.local/bin in their PATH. Use the full path to uvx to avoid "command not found" errors.

{
  "mcpServers": {
    "tradingview": {
      "command": "/Users/YOUR_USERNAME/.local/bin/uvx",
      "args": ["--from", "tradingview-mcp-server", "tradingview-mcp"]
    }
  }
}

On Linux, replace /Users/YOUR_USERNAME with /home/YOUR_USERNAME. On Windows, use %USERPROFILE%\.local\bin\uvx.exe.

Codex Plugin Config

This repository also includes mcp-only Codex plugin metadata:

.codex-plugin/plugin.json
.codex-mcp.json

The plugin uses the same PyPI package entrypoint:

{
  "mcpServers": {
    "tradingview": {
      "command": "uvx",
      "args": ["--from", "tradingview-mcp-server", "tradingview-mcp"]
    }
  }
}

After installing or enabling the Codex plugin, restart Codex so the MCP server is loaded in the next session. Depending on your Codex version, codex mcp list may show registered MCP servers, but tool availability should be verified in a fresh Codex session.

Or run from source

git clone https://github.com/atilaahmettaner/tradingview-mcp
cd tradingview-mcp
uv run tradingview-mcp

🛠️ Troubleshooting

🪟 Windows: `MCP error -32001: Request timed out` on first launch

Symptom — you see this in the Claude Desktop logs shortly after adding the config:

[tradingview] Server started and connected successfully
[tradingview] Message from client: initialize ...
[60 seconds later]
[tradingview] notifications/cancelled — reason: "MCP error -32001: Request timed out"

Why it happens: on Windows with Python 3.14, uvx downloads tradingview-mcp-server, creates a fresh virtualenv, and installs dependencies the first time it runs. Because pandas has no prebuilt wheel for Python 3.14 yet, pip falls back to a source build — which typically exceeds Claude Desktop's 60-second MCP initialization timeout.

Fix — pin to Python 3.13 (has prebuilt pandas wheels):

{
  "mcpServers": {
    "tradingview": {
      "command": "uvx",
      "args": ["--python", "3.13", "--from", "tradingview-mcp-server", "tradingview-mcp"]
    }
  }
}

On macOS use the full path to uvx (see the note in Quick Start). On Windows uvx is typically %USERPROFILE%\.local\bin\uvx.exe.

Alternative — pre-install once, then let Claude Desktop reuse the cache:

# Run in a terminal before launching Claude Desktop
uv tool install --python 3.13 tradingview-mcp-server

After the install finishes, start Claude Desktop with the normal config and the server will come up instantly (cache is already warm).

Credit: @wyh4444 for the original report in #24.

⚠️ Error Envelope Format

Tools that have adopted the structured error format return either their normal payload or an error envelope:

{"error": {"code": "ALL_BATCHES_FAILED", "message": "All 5 batches failed; first error: JSONDecodeError(...)", "batches_attempted": 5, "batches_failed": 5, "first_error": "..."}}

Why: the previous [] / {"error": "Analysis failed: ..."} strings made it impossible to distinguish "no matches today" from "upstream rate-limit cliff." The new envelope is programmatically branchable by code.

Currently adopted by: top_gainers, top_losers, rating_filter, volume_breakout_scanner, smart_volume_scanner. More tools will follow in subsequent PRs.

Detecting an error:

result = volume_breakout_scanner(exchange="KUCOIN")
if isinstance(result, dict) and "error" in result:
    code = result["error"]["code"]
    if code == "ALL_BATCHES_FAILED":
        # Wait + retry, raise alert, fall back to single-batch call, etc.
        ...
else:
    for row in result:
        ...

Stable codes are defined in core/errors.py.

📱 Use via Telegram, WhatsApp & More (OpenClaw)

Connect this server to Telegram, WhatsApp, Discord and 20+ messaging platforms using OpenClaw — a self-hosted AI gateway. Tested & verified on Hetzner VPS (Ubuntu 24.04).

How It Works

OpenClaw routes Telegram messages to an AI agent. The agent uses trading.py — a thin Python wrapper — to call tradingview-mcp functions and return formatted results. No MCP protocol needed between OpenClaw and the server; it's a direct Python import.

Telegram → OpenClaw agent (AI model) → trading.py (bash) → tradingview-mcp → Yahoo Finance

Quick Setup

# 1. Install UV and tradingview-mcp
curl -LsSf https://astral.sh/uv/install.sh | sh && source ~/.bashrc
uv tool install tradingview-mcp-server

# 2. Configure OpenClaw channels
cat > ~/.openclaw/openclaw.json << 'EOF'
{
  channels: {
    telegram: {
      botToken: "YOUR_BOT_TOKEN_HERE",
    },
  },
}
EOF

# 3. Configure gateway + agent
openclaw config set gateway.mode local
openclaw config set acp.defaultAgent main

# 4. Set your AI model (choose ONE option below)
openclaw configure --section model

# 5. Install the skill + tool wrapper
mkdir -p ~/.agents/skills/tradingview-mcp ~/.openclaw/tools
curl -fsSL https://raw.githubusercontent.com/atilaahmettaner/tradingview-mcp/main/openclaw/SKILL.md \
  -o ~/.agents/skills/tradingview-mcp/SKILL.md
curl -fsSL https://raw.githubusercontent.com/atilaahmettaner/tradingview-mcp/main/openclaw/trading.py \
  -o ~/.openclaw/tools/trading.py && chmod +x ~/.openclaw/tools/trading.py

# 6. Start the gateway
openclaw gateway install
systemctl --user start openclaw-gateway.service

Choose Your AI Model

OpenRouter is not required — use whichever provider you have a key for:

Provider	Model ID for OpenClaw	Get Key
OpenRouter (aggregator — access to all models)	`openrouter/google/gemini-3-flash-preview`	openrouter.ai/keys
Anthropic (Claude direct)	`anthropic/claude-sonnet-4-5`	console.anthropic.com
Google (Gemini direct)	`google/gemini-2.5-flash`	aistudio.google.com
OpenAI (GPT direct)	`openai/gpt-4o-mini`	platform.openai.com

# Examples — set your chosen model:
openclaw config set agents.defaults.model "openrouter/google/gemini-3-flash-preview"  # via OpenRouter
openclaw config set agents.defaults.model "anthropic/claude-sonnet-4-5"               # Anthropic direct
openclaw config set agents.defaults.model "google/gemini-2.5-flash"                   # Google direct

⚠️ Important: Prefix must match your provider. google/... needs a Google API key. openrouter/... needs an OpenRouter key.

⚠️ Common Mistakes

Symptom	Cause	Fix
`Unrecognized keys: mcpServers`	`mcpServers` not supported in this version	Remove from config, use bash wrapper
`No API key for provider "google"`	Used `google/model` but only have OpenRouter key	Use `openrouter/google/model` instead
`which agent?` loop	`acp.defaultAgent` not set	`openclaw config set acp.defaultAgent main`
Gateway won't start	`gateway.mode` missing	`openclaw config set gateway.mode local`

Test Your Bot

Once running, send your Telegram bot:

market snapshot
backtest RSI strategy for AAPL, 1 year
compare all strategies for BTC-USD

👉 Full OpenClaw Setup Guide →

Unlike basic screeners, this framework deploys specialized AI agents that debate findings in real-time:

🛠️ Technical Analyst — Bollinger Bands (±3 proprietary rating), RSI, MACD
🌊 Sentiment & Momentum Analyst — Reddit community sentiment + price momentum
🛡️ Risk Manager — Volatility, drawdown risk, mean-reversion signals

Output: STRONG BUY / BUY / HOLD / SELL / STRONG SELL with confidence score

🔧 All 30+ MCP Tools

📊 Backtesting Engine

Tool	Description
`backtest_strategy`	Backtest 1 of 9 strategies with institutional metrics (Sharpe, Calmar, Expectancy). Supports `1d` and `1h` timeframes; optional full trade log + equity curve.
`compare_strategies`	Run all 9 strategies on the same symbol and rank by performance.
`walk_forward_backtest_strategy`	Train/test split walk-forward validation with overfitting verdict (ROBUST / MODERATE / WEAK / OVERFITTED).

9 Strategies to Test:

rsi — RSI oversold/overbought mean reversion
bollinger — Bollinger Band mean reversion
macd — MACD golden/death cross
ema_cross — EMA 20/50 Golden/Death Cross
supertrend — ATR-based Supertrend trend following 🔥
donchian — Donchian Channel breakout (Turtle Trader style)
rsi_pullback — Dip-buy in confirmed uptrend (SMA50>SMA200 + RSI<40 entry) 🆕
keltner_breakout — ATR-normalized breakout (EMA20 + 2·ATR upper band) 🆕
triple_ema — EMA 20/50 cross gated by SMA200 trend filter 🆕

🆕 strategies require period='1y' or '2y' so the SMA200 trend filter can complete its warmup.

Metrics you get: Win Rate, Total Return, Sharpe Ratio, Calmar Ratio, Max Drawdown, Profit Factor, Expectancy, Best/Worst Trade, vs Buy-and-Hold, with realistic commission + slippage simulation.

Example prompt: "Compare all 9 strategies on MSFT for 2 years"
→ #1 triple_ema:        +15.1% | Sharpe:  0.0 | WR: 100%
→ #2 keltner_breakout:  +14.3% | Sharpe:  4.7 | WR:  40%
→ #3 bollinger:         +12.2% | Sharpe:  4.1 | WR:  64%
→ Buy & Hold:            -2.1%

💰 Yahoo Finance — Real-Time Prices (New in v0.6.0)

Tool	Description
`yahoo_price`	Real-time quote: price, change %, 52w high/low, market state
`market_snapshot`	Global overview: S&P500, NASDAQ, VIX, BTC, ETH, EUR/USD, SPY, GLD

Supports: Stocks (AAPL, TSLA, NVDA), Crypto (BTC-USD, ETH-USD, SOL-USD), ETFs (SPY, QQQ, GLD), Indices (^GSPC, ^DJI, ^IXIC, ^VIX), FX (EURUSD=X), Turkish (THYAO.IS, SASA.IS)

🧠 AI Sentiment & Intelligence

Tool	Description
`market_sentiment`	Reddit sentiment across finance communities (bullish/bearish score, top posts)
`financial_news`	Live RSS headlines from Yahoo Finance, MarketWatch, CNBC, CoinDesk, CoinTelegraph
`combined_analysis`	Power Tool: TradingView technicals + Reddit sentiment + live news → confluence decision. Now backed by retry + 60s cache for resilience against transient screener errors.

📈 Technical Analysis Core

Tool	Description
`get_technical_analysis`	Full TA: RSI, MACD, Bollinger, 23 indicators with BUY/SELL/HOLD
`get_multiple_analysis`	Bulk TA for multiple symbols at once
`get_bollinger_band_analysis`	Proprietary ±3 BB rating system
`get_stock_decision`	3-layer decision engine (ranking + trade setup + quality score)
`screen_stocks`	Multi-exchange screener with 20+ filter criteria
`scan_by_signal`	Scan by signal type (oversold, trending, breakout...)
`get_candlestick_patterns`	15 candlestick pattern detector
`get_multi_timeframe_analysis`	Weekly→Daily→4H→1H→15m alignment analysis

🌍 Multi-Exchange Support

Exchange	Tools
Binance	Crypto screener, all pairs
KuCoin / Bybit+	Crypto screener
NASDAQ / NYSE	US stocks (AAPL, TSLA, NVDA...)
EGX (Egypt)	`egx_market_overview`, `egx_stock_screener`, `egx_trade_plan`, `egx_fibonacci_retracement`
Turkish (BIST)	Via TradingView screener

💬 Example AI Conversations

You: "Give me a full market snapshot right now"
AI: [market_snapshot] → S&P500 -3.4%, BTC +0.1%, VIX 31 (+13%), EUR/USD 1.15

You: "What is Reddit saying about NVDA?"
AI: [market_sentiment] → Strongly Bullish (0.41) | 23 posts | 18 bullish

You: "Backtest RSI strategy on BTC-USD for 2 years"
AI: [backtest_strategy] → +31.5% return | 100% win rate | 2 trades | B&H: -5%

You: "Which of the 9 strategies worked best on MSFT in the last 2 years?"
AI: [compare_strategies] → triple_ema #1 (+15.1%, WR 100%), keltner_breakout #2 (+14.3%), macd last (-23.4%)

You: "Run walk-forward backtest on supertrend for SPY"
AI: [walk_forward_backtest_strategy] → Verdict: ROBUST (avg robustness 0.92) | OOS return +8.5%

You: "Analyze TSLA with all signals: technical + sentiment + news"
AI: [combined_analysis] → BUY (Technical STRONG BUY + Bullish Reddit + Positive news)

💖 Support the Project

This framework is free and open source, built in spare time. If it saves you hours of research or helps you make better decisions, please consider sponsoring:

Tier	Monthly	What You Get
☕ Coffee	$5	Heartfelt gratitude + name in README
🚀 Supporter	$15	Above + priority bug fixes
💎 Pro	$30	Above + priority feature requests

Every sponsor directly funds new features like Walk-Forward Backtesting, Twitter/X sentiment, and managed cloud hosting.

📋 Roadmap

TradingView technical analysis (30+ indicators)
Multi-exchange screener (Binance, KuCoin, MEXC, EGX, US stocks)
Reddit sentiment analysis
Live financial news (Yahoo / MarketWatch / CNBC / CoinDesk / CoinTelegraph)
Yahoo Finance real-time prices
Backtesting engine (9 strategies + Sharpe / Calmar / Expectancy)
Walk-forward backtesting (overfitting detection)
Resilience layer (retry + TTL cache) on screener provider
Hourly (1h) backtesting timeframe
Twitter/X market sentiment
Paper trading simulation
Managed cloud hosting (no local setup)

📄 License

MIT License — see LICENSE for details.

Disclaimer: This tool is for educational and research purposes only. It does not constitute financial advice. Always do your own research before making investment decisions.

Repository

atilaahmettaner

atilaahmettaner/tradingview-mcp

Created

August 8, 2025

Updated

June 22, 2026

Language

Python