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TVFetch
by
Tarun Khatri
· GitHub ↗
· v1.0.0
· MIT-0
94
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0
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1
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Install in OpenClaw
/install tvfetch
Description
Fetch TradingView market data — historical OHLCV bars, live price streams, symbol search, technical indicators, and statistical analysis for any symbol (stoc...
Usage Guidance
This skill appears to be what it claims: a reverse-engineered TradingView fetcher with helpful CLI scripts. Before installing or running: 1) Review the included Python code if you can, or run in an isolated virtualenv/container to avoid contaminating your system Python. 2) Be cautious with the optional TV_AUTH_TOKEN — the skill advises copying a JWT from your browser; treat that token like a password and only save it if you trust the code and environment (it will be stored in ~/.tvfetch/.env or keyring). 3) The skill may install dependencies (websocket-client, httpx, pandas, etc.) if you choose to pip install; prefer virtualenv. 4) If you prefer not to expose your TradingView account token, use anonymous mode (default) understanding intraday bar limits. 5) If you want extra assurance, run the scripts in mock mode or inspect network connections the library makes (it targets data.tradingview.com), and avoid running pip install -e unless you reviewed the repository.
Capability Analysis
Type: OpenClaw Skill
Name: tvfetch
Version: 1.0.0
The tvfetch skill is a comprehensive tool for retrieving market data from TradingView via a reverse-engineered WebSocket protocol. It features historical data fetching, live streaming, technical indicators (indicators.py), and statistical analysis (analyze.py). The skill manages sensitive authentication tokens locally in ~/.tvfetch/.env and includes a deployment script (scripts/sync.sh) for multi-agent environments. All behaviors, including network requests to legitimate TradingView endpoints (data.tradingview.com) and local file management for caching, are clearly aligned with the stated purpose and lack evidence of malicious intent, data exfiltration, or unauthorized execution.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description (TradingView OHLCV, streaming, indicators) lines up with included Python library and CLI scripts (fetch.py, stream.py, search.py, indicators, analyzers). Optional auth token, cache, and fallback behavior are plausible for this functionality.
Instruction Scope
SKILL.md directs the agent to run bundled Python scripts, check and write config under ~/.tvfetch, and optionally install the package from the skill directory (pip install -e ${CLAUDE_SKILL_DIR}). It also instructs how to obtain a TradingView auth_token via browser DevTools (document.cookie) which is sensitive but logically tied to increasing intraday limits. The instructions read/write only the skill's config paths and .env files (and may consult keyring), which is within scope for this skill.
Install Mechanism
There is no platform install spec, but SKILL.md recommends pip install -e from the skill directory to enable the library. Installing local Python code is expected to enable the CLI and modules, but note that pip installing editable code will write/execute package metadata on the host — review code before installing or install in an isolated environment.
Credentials
The skill does not require environment variables by default. It supports an optional TV_AUTH_TOKEN (CLI/ENV/.env/keyring) to increase bar limits, and optional TVFETCH_CACHE_PATH/TVFETCH_PROXY. Access to a single service token and local cache path is proportional to the stated functionality. The config will check keyring and .env files for a token — this is reasonable but users should be aware any token stored is a TradingView auth cookie (sensitive).
Persistence & Privilege
always:false and user-invocable:true. A SessionStart hook runs a non-blocking check-config.sh which prints warnings and may create ~/.tvfetch — this is limited scope and does not alter other skills or system-wide settings. The skill writes/reads only its own config/cache paths.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install tvfetch - After installation, invoke the skill by name or use
/tvfetch - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of tvfetch — fetch and analyze market data from TradingView with no API key.
- Fetch historical OHLCV bars, live price streams, search symbols, and compute key technical indicators (RSI, MACD, SMA, EMA, Bollinger Bands, etc.).
- Supports stocks, crypto, forex, futures, indices, and commodities for any TradingView symbol.
- Automatically interprets user intent from natural language and resolves symbols to exchange-prefixed codes.
- Handles anonymous usage limits and guides users to set up authentication for higher data limits.
- Outputs can be shown as tables or downloaded in CSV, JSON, or Parquet formats.
Metadata
Frequently Asked Questions
What is TVFetch?
Fetch TradingView market data — historical OHLCV bars, live price streams, symbol search, technical indicators, and statistical analysis for any symbol (stoc... It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.
How do I install TVFetch?
Run "/install tvfetch" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is TVFetch free?
Yes, TVFetch is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does TVFetch support?
TVFetch is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created TVFetch?
It is built and maintained by Tarun Khatri (@tarun-khatri); the current version is v1.0.0.
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