Cryptocurrency Market Data MCP Server

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get-volume-history

Retrieve historical trading volume data for cryptocurrency pairs to analyze market activity and liquidity trends over time.

Instructions

Get trading volume history over time

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "symbol": "<symbol>"
    },
    "name": "get-volume-history"
  }
}

Input Schema

Name	Required	Description	Default
`symbol`	Yes	Trading pair symbol (e.g., BTC/USDT, ETH/USDT)
`days`	No	Number of days of volume history (default: 7, max: 30)
`exchange`	No	Exchange to use (supported: binance, coinbase, kraken, kucoin, hyperliquid, huobi, bitfinex, bybit, okx, mexc)	binance

Implementation Reference

src/server.py:338-358 (handler)

Handler implementation for the 'get-volume-history' tool. Fetches daily OHLCV data, extracts and formats volume history over the specified number of days.

elif name == "get-volume-history":
    symbol = arguments.get("symbol", "").upper()
    days = min(int(arguments.get("days", 7)), 30)

    # Get daily volume data
    since = int((datetime.now() - timedelta(days=days)).timestamp() * 1000)
    ohlcv = await exchange.fetch_ohlcv(symbol, "1d", since=since)

    volume_data = []
    for candle in ohlcv:
        timestamp, _, _, _, _, volume = candle
        dt = datetime.fromtimestamp(timestamp/1000).strftime('%Y-%m-%d')
        volume_data.append(f"{dt}: {volume:,.2f}")

    return [
        types.TextContent(
            type="text",
            text=f"Daily trading volume history for {symbol} on {exchange_id.upper()}:\n\n" +
                 "\n".join(volume_data)
        )
    ]

src/server.py:200-220 (registration)

Registration of the 'get-volume-history' tool in the @server.list_tools() handler, including description and input schema.

types.Tool(
    name="get-volume-history",
    description="Get trading volume history over time",
    inputSchema={
        "type": "object",
        "properties": {
            "symbol": {
                "type": "string",
                "description": "Trading pair symbol (e.g., BTC/USDT, ETH/USDT)",
            },
            "days": {
                "type": "number",
                "description": "Number of days of volume history (default: 7, max: 30)",
                "default": 7,
                "maximum": 30
            },
            "exchange": get_exchange_schema()
        },
        "required": ["symbol"],
    },
),

src/server.py:203-219 (schema)

Input schema definition for the 'get-volume-history' tool, specifying required 'symbol' and optional 'days' and 'exchange' parameters.

inputSchema={
    "type": "object",
    "properties": {
        "symbol": {
            "type": "string",
            "description": "Trading pair symbol (e.g., BTC/USDT, ETH/USDT)",
        },
        "days": {
            "type": "number",
            "description": "Number of days of volume history (default: 7, max: 30)",
            "default": 7,
            "maximum": 30
        },
        "exchange": get_exchange_schema()
    },
    "required": ["symbol"],
},

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 18, 2025

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves historical data, implying it's read-only, but doesn't mention rate limits, authentication needs, data freshness, or what the output looks like (e.g., format, units). This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a straightforward data retrieval tool, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the returned volume history includes (e.g., time intervals, data format) or address potential complexities like handling missing data. For a tool with three parameters and no structured output information, more context is needed.

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?

The description adds no parameter-specific information beyond what's already in the input schema, which has 100% coverage with detailed descriptions for all three parameters. The baseline score of 3 is appropriate since the schema does the heavy lifting, but the description doesn't compensate or provide additional context.

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

Purpose4/5

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

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('trading volume history over time'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get-historical-ohlcv' or 'get-top-volumes', which might also provide volume-related data, so it doesn't reach the highest score.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'get-historical-ohlcv' or 'get-top-volumes'. It lacks context on use cases, prerequisites, or exclusions, leaving the agent to infer usage based on the name and parameters alone.

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

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