1. User Asks
"Is EURUSD bullish?"
AI
ChatGPT / OpenAI Integration
Give GPT-4o access to real-time market data. Build Custom GPTs with live indicators, or use function calling in your own applications to combine AI reasoning with fresh financial data.
~20 min setupREST + JSONX-API-Key authentication
~20 minTypical setup
AI AssistantsIntegration type
REST + JSONUniversal interface
X-API-KeyOne auth pattern
ChatGPT / OpenAI
How It Works
2. GPT Calls API
Fetches RSI, summary, screener via tools
3. GPT Analyzes
Combines data with reasoning for a grounded answer
Option 1: Custom GPT (No Code)
Create a Custom GPT in the ChatGPT interface that can query live market data:
- Go to Explore GPTs > Create a GPT
- Set the system prompt: "You are a forex analyst. Use your tools to fetch real-time data before answering."
- Under Actions, click Create new action
- Paste the OpenAPI schema below
- Under Authentication, select API Key with header
X-API-Key
json
{
"openapi": "3.1.0",
"info": {
"title": "TickAtlas Market Data",
"version": "1.0.0"
},
"servers": [
{ "url": "https://tickatlas.com" }
],
"paths": {
"/v1/indicator": {
"get": {
"operationId": "getIndicator",
"summary": "Get a technical indicator value",
"parameters": [
{ "name": "symbol", "in": "query", "required": true, "schema": { "type": "string" } },
{ "name": "indicator", "in": "query", "required": true, "schema": { "type": "string" } },
{ "name": "timeframe", "in": "query", "required": false, "schema": { "type": "string", "default": "H1" } }
]
}
},
"/v1/summary": {
"get": {
"operationId": "getMarketSummary",
"summary": "Get rule-based market analysis with bias and confidence",
"parameters": [
{ "name": "symbol", "in": "query", "required": true, "schema": { "type": "string" } },
{ "name": "timeframe", "in": "query", "required": false, "schema": { "type": "string", "default": "H1" } }
]
}
},
"/v1/screener": {
"get": {
"operationId": "screenMarket",
"summary": "Scan symbols by indicator criteria",
"parameters": [
{ "name": "indicator", "in": "query", "required": true, "schema": { "type": "string" } },
{ "name": "timeframe", "in": "query", "required": false, "schema": { "type": "string", "default": "H1" } },
{ "name": "max_val", "in": "query", "schema": { "type": "number" } },
{ "name": "min_val", "in": "query", "schema": { "type": "number" } }
]
}
}
}
}Option 2: Function Calling (Python)
Define TickAtlas endpoints as OpenAI tools for programmatic use:
json
tools = [
{
"type": "function",
"function": {
"name": "get_indicator",
"description": "Get a technical indicator value for a forex/crypto symbol",
"parameters": {
"type": "object",
"properties": {
"symbol": {"type": "string", "description": "Trading symbol, e.g. EURUSD"},
"indicator": {"type": "string", "description": "e.g. RSI_14, MACD_hist"},
"timeframe": {"type": "string", "enum": ["M1","M5","M15","M30","H1","H4","D1"]}
},
"required": ["symbol", "indicator", "timeframe"]
}
}
},
{
"type": "function",
"function": {
"name": "get_market_summary",
"description": "Rule-based market analysis: bias, confidence, and a plain-text summary for a symbol",
"parameters": {
"type": "object",
"properties": {
"symbol": {"type": "string"},
"timeframe": {"type": "string", "enum": ["M1","M5","M15","M30","H1","H4","D1"]}
},
"required": ["symbol", "timeframe"]
}
}
},
{
"type": "function",
"function": {
"name": "screen_market",
"description": "Scan all symbols to find those matching indicator criteria (e.g. RSI below 30 = oversold)",
"parameters": {
"type": "object",
"properties": {
"indicator": {"type": "string"},
"timeframe": {"type": "string", "enum": ["M1","M5","M15","M30","H1","H4","D1"]},
"max": {"type": "number"},
"min": {"type": "number"}
},
"required": ["indicator", "timeframe"]
}
}
}
]Tool Call Handler
python
import os
import json
import requests
from openai import OpenAI
CLAW_API_KEY = os.environ["CLAW_API_KEY"]
CLAW_BASE = "https://tickatlas.com/v1"
def call_tickatlas(endpoint: str, params: dict) -> dict:
resp = requests.get(
f"{CLAW_BASE}/{endpoint}",
headers={"X-API-Key": CLAW_API_KEY},
params=params,
timeout=10,
)
resp.raise_for_status()
# Every success response is {"success": true, "data": {...}}
return resp.json()["data"]
def handle_tool_call(tool_call) -> str:
name = tool_call.function.name
args = json.loads(tool_call.function.arguments)
if name == "get_indicator":
result = call_tickatlas("indicator", {
"symbol": args["symbol"],
"indicator": args["indicator"],
"timeframe": args["timeframe"],
})
elif name == "get_market_summary":
result = call_tickatlas("summary", {
"symbol": args["symbol"],
"timeframe": args["timeframe"],
})
elif name == "screen_market":
params = {"indicator": args["indicator"], "timeframe": args["timeframe"]}
if "max" in args: params["max_val"] = args["max"]
if "min" in args: params["min_val"] = args["min"]
result = call_tickatlas("screener", params)
else:
result = {"error": f"Unknown tool: {name}"}
return json.dumps(result)
client = OpenAI()
messages = [
{"role": "system", "content": (
"You are a forex market analyst with access to real-time indicator data via the TickAtlas API. "
"When users ask about market conditions, use the tools to fetch current data before answering. "
"Always cite the actual values in your response."
)},
{"role": "user", "content": "Is EURUSD bullish right now? What does the RSI say?"},
]
response = client.chat.completions.create(model="gpt-4o", messages=messages, tools=tools)
while response.choices[0].message.tool_calls:
assistant_msg = response.choices[0].message
messages.append(assistant_msg)
for tool_call in assistant_msg.tool_calls:
result = handle_tool_call(tool_call)
messages.append({
"role": "tool",
"tool_call_id": tool_call.id,
"content": result,
})
response = client.chat.completions.create(model="gpt-4o", messages=messages, tools=tools)
print(response.choices[0].message.content)