Building AI agents that can answer real-time financial questions is tough. You need reliable data sources, API integrations, and the right abstractions to make it seamless. That's why the Hermes community just shipped something powerful: the Financial Modeling Prep (FMP) skill.
Whether you're building a financial chatbot, an investment research assistant, or an autonomous trading dashboard, you now have a plug-and-play skill that gives your Hermes AI agent instant access to professional-grade financial data.
The FMP skill connects Hermes to real-time market data across multiple asset classes:
The skill is built on a clean abstraction over Financial Modeling Prep's stable API (v2025+):
def fmp(path, **params):
params["apikey"] = os.environ["FMP_API_KEY"]
qs = "&".join(f"{k}={v}" for k, v in params.items())
url = f"https://financialmodelingprep.com/stable/{path}?{qs}"
return json.loads(urllib.request.urlopen(url).read())
With this helper, querying data is one line:
price = fmp("quote", symbol="AAPL")
print(f"AAPL: ${price[0]['price']} ({price[0]['changesPercentage']:+.2f}%)")
Setup is straightforward:
~/.hermes/.env
):
FMP_API_KEY=your_key_here
Hermes will automatically route these queries to the FMP skill and deliver formatted, contextual answers.
Financial data is increasingly important for AI agents. This skill removes the friction of integrating FMP—you get:
The FMP skill is live in the ** hermes-skills** repository. If you're building financial AI agents, check it out and give the repo a ⭐ to support the project.
Have ideas for other financial endpoints? PRs welcome—let's build the financial data layer for AI agents together.