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MCP TradingView Server

Name: MCP TradingView Server
Author: mathieubernardi

by mathieubernardi

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

MCP TradingView Server

Serveur MCP (Model Context Protocol) en Python qui expose les données de marché TradingView à un client MCP — Claude Desktop, claude.ai ou tout autre client compatible. Les données sont récupérées via tvdatafeed (OHLCV) et tradingview-ta (screener).

Outils exposés

Outil MCP	Description
`tv_get_historical_data`	Bougies OHLCV historiques (actions, crypto, forex, futures)
`tv_get_quote`	Dernière bougie + variation % par rapport à la précédente
`tv_get_indicators`	Indicateurs techniques, contexte multi-timeframe et score composite
`tv_screener`	Filtrage par marché, volume et RSI sur un univers prédéfini

`tv_get_indicators` en détail

Indicateurs calculés : RSI, MACD, Bollinger Bands (avec détection de squeeze), EMA, SMA, ATR (avec niveaux de stop long/short), Stochastique, ADX (+DI/−DI), OBV, moyenne et ratio de volume 20 périodes, et détection de divergences RSI.

Trois options désactivées par défaut :

Paramètre	Effet
`include_weekly: true`	Ajoute un contexte hebdomadaire : `weekly_rsi`, `weekly_adx`, `weekly_trend`
`benchmark_symbol: "CW8"`	Calcule la force relative à 1 mois et 3 mois contre ce benchmark
`include_score: true`	Calcule un score technique composite dans `[-1, +1]` et ses sous-scores

Intervalles acceptés : 1, 3, 5, 15, 30, 45 (minutes), 1H, 2H, 3H, 4H, 1D, 1W, 1M.

Portée du screener

tvdatafeed n'expose pas d'API de screener. tv_screener parcourt donc un univers prédéfini en dur dans MARKET_SYMBOLS (src/mcp_tradingview/client.py) et calcule les indicateurs sur chaque symbole via tradingview-ta :

Marché	Univers couvert
`france`	29 symboles Euronext Paris — CAC 40, quelques midcaps tech, ETF éligibles PEA
`america`	20 blue chips Nasdaq / NYSE
`crypto`	8 paires majeures Binance
`forex`	6 paires majeures

L'énumération ScreenerMarket accepte aussi futures, india, brazil, australia, canada, europe et hongkong, mais aucun univers n'est défini pour ces marchés : l'appel retourne une liste vide. Ajouter une entrée dans MARKET_SYMBOLS suffit à les activer.

Related MCP server: tradingview-mcp

Architecture

Client MCP (Claude Desktop, claude.ai…)
    │
    ├── stdio ──► process local
    └── SSE   ──► serveur HTTP (Starlette + uvicorn)
              │
              ├──► tvdatafeed    : bougies OHLCV
              └──► tradingview-ta : screener
                        │
                        └──► cache TTL en mémoire

Prérequis

Python ≥ 3.11
Un compte TradingView est optionnel — l'accès anonyme fonctionne, avec des limites de débit plus strictes.
Le SDK MCP est épinglé en < 2.0.0 : la version 2.x supprime les décorateurs @server.list_tools() / @server.call_tool() et renomme Tool.inputSchema en Tool.input_schema. Une migration est nécessaire avant de lever ce plafond.

Installation

git clone https://github.com/mathieubernardi/tradingview_mcp.git
cd tradingview_mcp

pip install -e ".[dev]"

cp .env.example .env   # puis éditer .env

Configuration

Toutes les variables sont préfixées TV_ et peuvent être passées soit par un fichier .env, soit par l'environnement.

Variable	Défaut	Description
`TV_TV_USERNAME`	(vide)	Identifiant TradingView (optionnel)
`TV_TV_PASSWORD`	(vide)	Mot de passe TradingView (optionnel)
`TV_TRANSPORT`	`stdio`	`stdio` ou `sse`
`TV_HOST`	`127.0.0.1`	Hôte du serveur SSE
`TV_PORT`	`8765`	Port du serveur SSE (1024–65535)
`TV_DEFAULT_EXCHANGE`	`EURONEXT`	Place par défaut si l'appel n'en précise pas
`TV_DEFAULT_N_BARS`	`500`	Nombre de bougies par défaut
`TV_MAX_N_BARS`	`5000`	Plafond du nombre de bougies
`TV_CACHE_TTL_SECONDS`	`60`	Durée de vie du cache mémoire (`0` = désactivé)
`TV_LOG_LEVEL`	`INFO`	`DEBUG`, `INFO`, `WARNING` ou `ERROR`

Le double préfixe de TV_TV_USERNAME / TV_TV_PASSWORD est voulu : le préfixe d'environnement TV_ s'ajoute aux champs tv_username / tv_password.

Lancer le serveur

Deux points d'entrée équivalents : le script console mcp-tradingview et le module python -m mcp_tradingview. Le second ne dépend pas du PATH, ce qui le rend plus fiable sous Windows.

# Linux / macOS — stdio
TV_TRANSPORT=stdio python -m mcp_tradingview

# Linux / macOS — SSE
TV_TRANSPORT=sse python -m mcp_tradingview

# Windows PowerShell — stdio
$env:TV_TRANSPORT = "stdio"; python -m mcp_tradingview

# Windows PowerShell — SSE
$env:TV_TRANSPORT = "sse"; python -m mcp_tradingview

Intégration Claude Desktop (stdio)

Ajouter dans claude_desktop_config.json — ~/Library/Application Support/Claude/ sous macOS, %APPDATA%\Claude\ sous Windows :

{
  "mcpServers": {
    "tradingview": {
      "command": "python",
      "args": ["-m", "mcp_tradingview"],
      "env": {
        "TV_TRANSPORT": "stdio",
        "TV_CACHE_TTL_SECONDS": "60"
      }
    }
  }
}

Si l'environnement Python n'est pas celui par défaut, remplacer "python" par le chemin absolu de l'interpréteur du virtualenv. Pour utiliser un compte TradingView, ajouter TV_TV_USERNAME et TV_TV_PASSWORD dans le bloc env.

En mode stdio, la session TradingView est établie paresseusement au premier appel d'outil : le handshake MCP répond immédiatement et le client ne subit pas de timeout au démarrage.

Intégration SSE

TV_TRANSPORT=sse TV_PORT=8765 python -m mcp_tradingview

Endpoint	Rôle
`GET /sse`	Flux SSE à déclarer côté client MCP
`POST /messages/`	Canal de retour des messages client
`GET /health`	Sonde de vivacité, retourne `ok`

Développement

pytest tests/ -v          # tests
ruff check src/ tests/    # lint
mypy src/                 # type checking (strict)

Limites connues

tvdatafeed est un client non officiel qui s'appuie sur les endpoints web de TradingView : il peut cesser de fonctionner sans préavis.
tv_screener ne balaye pas un marché entier, seulement l'univers prédéfini décrit plus haut.
Sans compte Premium TradingView, les données peuvent accuser un retard de plusieurs minutes.
L'accès anonyme subit des limites de débit sensiblement plus strictes qu'un compte connecté.
Les erreurs d'un outil sont renvoyées au client sous forme de JSON {"error": ..., "tool": ..., "arguments": ...} plutôt que remontées comme erreurs de protocole.

Structure du projet

tradingview_mcp/
├── src/mcp_tradingview/
│   ├── __init__.py      # métadonnées du paquet (__version__)
│   ├── __main__.py      # entrée `python -m mcp_tradingview`
│   ├── config.py        # settings (pydantic-settings, préfixe TV_)
│   ├── models.py        # schémas Pydantic d'entrée / sortie
│   ├── client.py        # client TradingView, indicateurs, cache TTL
│   ├── tools.py         # définition JSON Schema + dispatch des outils
│   └── server.py        # serveur MCP (stdio + SSE) et entrée console
├── tests/
│   └── test_server.py
├── pyproject.toml
├── .env.example
├── .gitignore
├── LICENSE
└── README.md

Licence

Distribué sous licence MIT. Voir le fichier LICENSE.

Available Tools

4 tools

tv_get_historical_dataA

Fetch historical OHLCV (Open, High, Low, Close, Volume) bars for any symbol from TradingView. Supports stocks, crypto, forex, futures.

ParametersJSON Schema

Name	Required	Description	Default
`n_bars`	No	Number of bars to return
`symbol`	Yes	Ticker symbol, e.g. 'BTCUSDT', 'AAPL', 'EURUSD'
`exchange`	No	Exchange name, e.g. 'EURONEXT' (PEA / Paris), 'NASDAQ', 'NYSE', 'BINANCE', 'FX'	EURONEXT
`interval`	No	Chart interval: 1, 3, 5, 15, 30, 45 (min) \| 1H, 2H, 3H, 4H \| 1D, 1W, 1M	1D

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the behavioral disclosure burden. It names the output content (OHLCV bars) and the supported asset classes, but it does not mention bar ordering, exchange-selection caveats for non-EURONEXT symbols, adjustment behavior, or error handling. Some useful transparency exists, but important nuances are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no filler. The primary action is front-loaded, and the second sentence adds useful asset-class scope without bloating the definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple and the schema documents all parameters, so an agent can invoke it. However, with no output schema and no annotations, the description leaves out useful invocation-relevant details such as whether exchange must match the symbol (the default is EURONEXT, which may not work for all symbols) and the ordering/shape of returned bars.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter is already documented. The description adds broad domain context ('Supports stocks, crypto, forex, futures'), but it does not add parameter-specific meaning beyond what the schema provides. The baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Fetch historical OHLCV bars for any symbol from TradingView.' This clearly distinguishes it from sibling tools like tv_get_quote, tv_get_indicators, and tv_screener, which serve different purposes (current quote, derived indicators, screening).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: use this tool when historical OHLCV candle data is needed. It does not explicitly say 'use tv_get_quote for current prices' or 'use tv_get_indicators for computed values,' but the historical bar framing makes the intended use apparent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tv_get_indicatorsA

Compute technical indicators for any symbol. Includes RSI, MACD, Bollinger Bands (+ squeeze detection), EMA, SMA, ATR (+ stop levels), Stochastic, ADX (+DI/-DI), OBV, volume MA20/ratio, RSI divergence flags. Optional: weekly multi-timeframe context (include_weekly=true), relative strength vs benchmark (benchmark_symbol), composite technical score [-1,+1] (include_score=true).

ParametersJSON Schema

Name	Required	Description	Default
`bb_std`	No
`n_bars`	No
`symbol`	Yes
`exchange`	No		EURONEXT
`interval`	No		1D
`bb_length`	No
`macd_fast`	No
`macd_slow`	No
`atr_length`	No
`indicators`	No
`rsi_length`	No
`ema_periods`	No
`macd_signal`	No
`sma_periods`	No
`atr_stop_mult`	No	ATR multiplier for stop_long / stop_short levels
`include_score`	No	Compute composite technical_score [-1,+1] and sub-scores
`include_weekly`	No	Fetch weekly bars for weekly_rsi, weekly_adx, weekly_trend
`benchmark_symbol`	No	Benchmark ticker for RS 1M/3M (e.g. 'CW8'). Empty = skip.
`benchmark_exchange`	No		EURONEXT
`divergence_lookback`	No	Bars window for RSI divergence detection

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full disclosure burden and does add useful behavioral context: RSI divergence flags, Bollinger squeeze detection, ATR stop_long/stop_short levels, the [-1,+1] composite score range, and what each optional flag produces. However, it does not reveal the return shape, that the indicators parameter defaults to ['all'] so every call computes the entire indicator set, or any data-source/error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two dense sentences of roughly 60 words with the core purpose front-loaded and no filler. Parameter names are embedded inline (include_weekly=true, benchmark_symbol, include_score=true), making the text directly actionable for an agent without cross-referencing the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 20-parameter tool with no output schema and no annotations, the description thoroughly covers the feature and option matrix but omits the output contract: what the response contains, how weekly/benchmark/score fields appear in results, and that the default is to compute all indicators. An agent can select the tool confidently but would invoke it without knowing what it returns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, so the description must compensate. It maps the three optional features to their parameter names inline (include_weekly=true, benchmark_symbol, include_score=true) and its indicator inventory aligns with the indicators enum values. The many numeric tuning parameters (macd_fast, atr_length, sma_periods, etc.) are left to their self-explanatory names, which is passable but adds no real semantic depth.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource ('Compute technical indicators for any symbol') and enumerates the full indicator surface: RSI, MACD, Bollinger Bands with squeeze detection, EMA, SMA, ATR with stop levels, Stochastic, ADX, OBV, volume MA20/ratio, and RSI divergence flags. The sibling names (tv_get_historical_data, tv_get_quote, tv_screener) make this tool's distinct role unambiguous even without explicit comparison.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The opening sentence establishes a clear selection context: use this tool when computed indicators are needed, as opposed to raw bars (tv_get_historical_data), a snapshot quote (tv_get_quote), or universe filtering (tv_screener). It stops short of naming those alternatives explicitly or stating when not to use this tool, but the purpose is specific enough that an agent can route correctly.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tv_get_quoteA

Get the latest price quote for a symbol: last OHLCV bar plus percentage change from the previous bar.

ParametersJSON Schema

Name	Required	Description	Default
`symbol`	Yes	Ticker symbol
`exchange`	No		EURONEXT
`interval`	No		1D

TDQS

A3.6/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It usefully discloses the output shape (last OHLCV bar plus percentage change), but it does not mention data delay, exchange handling, or how the interval parameter affects the returned bar. Acceptable but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded, and free of filler. Every phrase earns its place by specifying the object, the timeframe, and the included data.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 3-parameter read tool, the description gives the core return fields, but with no output schema and no annotations it should also clarify interval/exchange behavior and the reference period for the percentage change. Adequate with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33%: only 'symbol' has a description, while 'exchange' and 'interval' are undocumented. The description adds no meaning for exchange or interval and does not compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('get'), names the resource ('latest price quote for a symbol'), and states the exact payload ('last OHLCV bar plus percentage change from the previous bar'). The words 'latest' and 'last bar' clearly distinguish it from tv_get_historical_data and the other siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for obtaining a current snapshot rather than historical data or indicators, but it never explicitly states when to choose this tool over its siblings. There are no exclusions or alternative routing hints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tv_screenerA

Screen stocks, crypto or forex symbols by market, volume, RSI range. Markets include 'france' (Euronext Paris — PEA) and 'america' (Nasdaq / NYSE). Returns top matches with price, volume and RSI data.

ParametersJSON Schema

Name	Required	Description	Default
`limit`	No
`market`	No	Market to screen: 'france' (Euronext Paris / PEA), 'america' (Nasdaq + NYSE), crypto, forex, futures, etc.	france
`max_rsi`	No
`min_rsi`	No
`min_volume`	No	Minimum volume filter
`min_market_cap`	No

TDQS

A3.8/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of explaining behavior. It does disclose output fields ('price, volume and RSI data') and the market coverage for France and America. It does not explain how 'top matches' are ordered, how limit interacts with results, or whether RSI bounds are inclusive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences that front-load the core purpose, then the key market values, then the return data. There is no filler or repetition of schema defaults.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For an optional-parameter screener with no output schema, the description provides enough to invoke it sensibly: what it screens, key market options, and what data is returned. The missing ordering/ranking criteria and the unexplained min_market_cap parameter are gaps, but the tool remains usable with defaults.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33%, so the description must compensate. It adds the 'RSI range' concept and market context, but min_market_cap is completely unexplained and limit is only inferable. The description partially fills the gap but does not fully cover all six parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Screen') with a clear resource ('stocks, crypto or forex symbols') and names the key filtering dimensions. It also distinguishes itself from the sibling tools by focusing on screening/discovery rather than historical data, quotes, or indicators.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied: use this tool to find symbols matching market, volume, and RSI criteria. However, it never explicitly says when NOT to use it or directs the agent to alternatives like tv_get_quote or tv_get_indicators, so routing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

4 tool updatesv0.1.0Sep 6, 2026
- First observedtv_get_historical_data
- First observedtv_get_indicators
- First observedtv_get_quote
- First observedtv_screener

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.9/5.0

Scored 2026-09-06 00:15 across 4 tools

Disambiguation5/5

Each tool targets a distinct data need: historical bars, latest quote, indicator calculation, and symbol screening. The only potential overlap is RSI appearing in indicators and screener, but the intended use (computing vs scanning) is clear.

Naming Consistency4/5

Three tools follow the `tv_get_*` verb-object pattern and all use consistent snake_case with a `tv_` prefix. `tv_screener` is the outlier because it uses a noun instead of an action verb, but it is still recognizable within the family.

Tool Count5/5

Four tools is a reasonable, focused size for a market-data server, and each tool provides broad functionality (multi-symbol historical data, quotes, many indicators, and a screener). None feels redundant or unnecessary.

Completeness4/5

The server covers the core market-data workflow: retrieving history, checking current prices, computing technical analysis, and discovering symbols via screening. Minor gaps such as no dedicated symbol-search or fundamental data endpoint exist, but they are workable around for typical technical-analysis use cases.

Maintenance

ActivityMaintained

ResponsivenessNo issues

Resources

GitHub Repository

Need Help?

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MCP TradingView Server

Outils exposés

tv_get_indicators en détail

Portée du screener

Architecture

Prérequis

Installation

Configuration

Lancer le serveur

Intégration Claude Desktop (stdio)

Intégration SSE

Développement

Limites connues

Structure du projet

Licence

Available Tools

Tool Schema Changelog

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

`tv_get_indicators` en détail