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price-data-mcp

price-data-mcp

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github.com/wesseltlFinance1Updated 12w ago
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About price-data-mcp

price-data-mcp is an MCP server that gives agents current prices and recent candle history for more than 200 coins. It provides market data from Hyperliquid's public info API, without trading signals, forecasts, or order placement.

Key features

  1. 01Fetch a current price by symbol
  2. 02Fetch prices for multiple symbols
  3. 03List supported symbols
  4. 04Retrieve recent OHLCV candles
  5. 05Use market data without trading actions

Use cases

  1. 01Check a coin's current market price
  2. 02Review recent price and volume history
  3. 03Look up supported symbols for an agent

MCP support

The MCP server exposes tools to retrieve individual or multiple prices, list symbols, and fetch recent OHLCV candles for MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
  "mcpServers": {
    "wesseltl-price-data": {
      "command": "uvx",
      "args": [
        "hyperliquid-price-mcp"
      ]
    }
  }
}
Run commanduvx hyperliquid-price-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypihyperliquid-price-mcp0.1.3

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

price-data-mcp

PyPI Python MCP License Deps

Give your AI agent live market prices. An MCP server that lets an agent look up the current price, the full symbol list, and recent price history for 200+ coins.

An LLM's knowledge is frozen at training time, so it can't answer "what's BTC trading at right now?". This closes that gap. It returns market data only. It never gives a trading signal or predicts direction.

What your agent can do with it

You: What's Bitcoin trading at, and how has it moved over the last few hours?

Agent (calls get_price("BTC") and get_candles("BTC", "1h", 6)): Bitcoin is at $65,047. Over the last 6 hours it's held between $65,020 and $65,132 on rising volume.

The agent fetches real numbers instead of guessing from stale training data.

Quickstart

pip install "hyperliquid-price-mcp[mcp]"

Add it to your MCP client (e.g. Claude Desktop's config):

{
  "mcpServers": {
    "market-prices": { "command": "hyperliquid-price-mcp" }
  }
}

Restart your client. The agent now has four tools.

The tools

ToolReturns
get_price("BTC"){"symbol": "BTC", "price": 65047.5, "as_of": 1786204330859}
get_prices(["BTC","ETH"])current price for each, missing ones flagged
list_symbols()every symbol it can price (200+)
get_candles("BTC","1h",100)recent OHLCV history (1m … 1d)

Example candle:

{"open_ms": 1786201200000, "open": 65104.0, "high": 65132.0,
 "low": 65020.0, "close": 65047.0, "volume": 409.43, "trades": 7014}

Also usable from plain Python

from price_data_mcp import prices

prices.get_price("BTC")                # {'symbol': 'BTC', 'price': 65047.5, 'as_of': ...}
prices.get_candles("ETH", "1h", 24)    # last 24 hourly candles
prices.list_symbols()                  # ['AAVE', 'ADA', 'APE', ...]

How it works

Prices come from the public Hyperliquid info API. The core fetching module (price_data_mcp/prices.py) uses the Python standard library only (no dependencies), so it's small and easy to audit. The mcp extra is only needed to run the server.

Tests

python -m unittest discover -s tests     # network is mocked, runs fully offline

Scope

A market-data source for agents. It reports prices and history. It does not give trading signals, predict where the price is going, or place orders.

License

MIT

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.