OKX MCP Server
OKX MCP サーバー
OKX 取引所からリアルタイムの暗号通貨価格データを提供するモデル コンテキスト プロトコル サーバー。
特徴
このMCPサーバーはOKX APIに接続し、シンプルなツールインターフェースを通じて暗号通貨の価格情報を提供します。包括的なエラー処理、リクエストログ、OKX API経由のレート制限機能も備えています。
ツール
get_candlesticks
OKX 上の任意の銘柄の履歴ローソク足 (OHLCV) データを取得します。
入力:
instrument: 文字列(必須) - 銘柄ID(例:"BTC-USDT")bar: 文字列(オプション) - 時間間隔(例:"1m"、"5m"、"1H"、"1D")、デフォルトは"1m"limit: 数値(オプション) - 返されるローソク足の数(最大100)、デフォルトは100
出力: JSON オブジェクトの配列。各オブジェクトには次のものが含まれます。
timestamp: ローソク足のISOタイムスタンプopen:始値high:最高価格low:最低価格close:終値volume:取引量volumeCurrency: 通貨換算での取引量
使用例:
[
{
"timestamp": "2025-03-07T17:00:00.000Z",
"open": "87242.8",
"high": "87580.2",
"low": "86548.0",
"close": "87191.8",
"volume": "455.72150427",
"volumeCurrency": "39661166.242091111"
}
]get_price
OKX のあらゆる銘柄の最新価格と 24 時間市場データを取得します。
入力:
instrument: 文字列(必須) - 銘柄ID(例:"BTC-USDT")
出力: 次の内容を含む JSON オブジェクト:
instrument: 要求された楽器IDlastPrice: 最新の取引価格bid: 現在の最高入札価格ask: 現在の最良売値high24h: 24時間最高価格low24h: 24時間最安値volume24h: 24時間取引量timestamp: データのISOタイムスタンプ
使用例:
{
"instrument": "BTC-USDT",
"lastPrice": "65432.1",
"bid": "65432.0",
"ask": "65432.2",
"high24h": "66000.0",
"low24h": "64000.0",
"volume24h": "1234.56",
"timestamp": "2024-03-07T17:22:28.000Z"
}Related MCP server: OKX MCP Server
発達
依存関係をインストールします:
npm installサーバーを構築します。
npm run build自動リビルドを使用した開発の場合:
npm run watchインストール
Claude Desktop または VSCode で使用するには、MCP 設定にサーバー構成を追加します。
macOS (VSCode):
~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonmacOS (Claude デスクトップ):
~/Library/Application Support/Claude/claude_desktop_config.jsonWindows (VSCode):
%APPDATA%/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.jsonWindows (Claude デスクトップ):
%APPDATA%/Claude/claude_desktop_config.json構成:
{
"mcpServers": {
"okx": {
"command": "node",
"args": ["/path/to/okx-mcp-server/build/index.js"],
"disabled": false,
"autoApprove": []
}
}
}エラー処理
サーバーは包括的なエラー処理を実装します。
ネットワークエラーはキャプチャされ、コンテキストとともに返されます
無効な機器IDは適切なエラーメッセージを返します
APIレート制限はaxiosタイムアウト設定を通じて尊重されます
すべてのエラーはデバッグのために記録されます
Available Tools
2 toolsget_candlesticksC
Get candlestick data for an OKX instrument
| Name | Required | Description | Default |
|---|---|---|---|
| instrument | Yes | Instrument ID (e.g. BTC-USDT) | |
| bar | No | Time interval (e.g. 1m, 5m, 1H, 1D) | 1m |
| limit | No | Number of candlesticks (max 100) |
TDQS
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 but only states what the tool does without mentioning rate limits, authentication needs, response format, or pagination behavior. It doesn't explain what 'candlestick data' includes (e.g., OHLC values) or any constraints beyond the implied data retrieval.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded and appropriately sized for a simple data retrieval tool, with every word contributing to clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 for a tool with three parameters. It doesn't cover behavioral aspects like response format, error handling, or usage context, leaving significant gaps for an AI agent to understand how to effectively invoke and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all three parameters. The description adds no additional meaning beyond the schema, such as explaining the significance of candlestick intervals or instrument IDs in context. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('candlestick data for an OKX instrument'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling tool 'get_price', which likely provides different market data, leaving room for improvement in distinguishing between similar data retrieval functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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 the sibling 'get_price' or any alternatives. It lacks context about when candlestick data is appropriate (e.g., for charting, technical analysis) versus price data, offering no usage boundaries or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_priceC
Get latest price for an OKX instrument
| Name | Required | Description | Default |
|---|---|---|---|
| instrument | Yes | Instrument ID (e.g. BTC-USDT) |
TDQS
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 what the tool does but lacks details on traits like rate limits, authentication needs, error handling, or response format. 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It is appropriately sized and front-loaded, clearly stating the tool's purpose without unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
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 behavioral traits, return values, or usage context, which are essential for a tool that fetches financial data. This leaves clear gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the 'instrument' parameter. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'latest price for an OKX instrument', making the purpose specific and understandable. It doesn't explicitly distinguish from the sibling 'get_candlesticks', which provides historical price data, so it misses full differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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_candlesticks'. There is no mention of prerequisites, context, or exclusions, leaving usage unclear.
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.
2 tool updates
v1.0.0- Added
get_candlesticks - Added
get_price
TDQS
Scored across 2 tools
The two tools have distinct purposes: get_candlesticks retrieves historical price data in candlestick format, while get_price fetches the latest price. There is minimal overlap as they target different data types (historical vs. current), though both relate to instrument pricing which could cause slight confusion in some contexts.
Both tools follow a consistent verb_noun naming pattern (get_candlesticks, get_price) with clear, descriptive names. The snake_case style is uniform throughout, making the tools easy to identify and predict.
With only 2 tools, the server feels severely under-scoped for a financial trading platform like OKX. This minimal set lacks essential operations such as placing orders, managing accounts, or accessing market depth, which are core to trading workflows.
The tool surface is highly incomplete for an OKX server, covering only price data retrieval. There are significant gaps in trading functionality (e.g., no create_order, cancel_order), account management, or market data beyond basic prices, which will likely cause agent failures in typical trading scenarios.
Maintenance
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