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I built a search API for agents to query financial market data in natural language
r/aiagents
8/2/2025
Content Summary
The author built a search API that allows AI agents to query financial market data using natural language. The API can handle requests for stock prices, crypto, and FX data, and automatically resolves nicknames to tickers and understands vague date ranges. It integrates with popular frameworks like LangChain, LlamaIndex, and Vercel AI SDK, and provides structured data in JSON format. The post asks if this solution would help others facing similar challenges in building AI agents for financial analysis.
Opinion Analysis
Mainstream opinion suggests that the author's search API addresses a real pain point for AI agents in finance, particularly around handling financial data from multiple sources. Many users appreciate the ability to query data naturally and receive structured responses. There is also interest in expanding the API to other domains like scientific research, as suggested by one comment. However, there is no explicit conflict or controversy in the discussion. The focus remains on the practical benefits of the API and its potential to simplify financial data integration for AI agents.
SAAS TOOLS
SaaS | URL | Category | Features/Notes |
---|---|---|---|
LangChain | - | AI Agent Framework | Tool calls to finance APIs are brittle according to the post |
Vercel AI SDK | - | AI Development Kit | Tool calls to finance APIs are brittle according to the post |
LlamaIndex | - | AI Data Indexing | Tool calls to finance APIs are brittle according to the post |
ScreenStudio | - | Video Editing Tool | Mentioned by the author for video editing purposes |
USER NEEDS
Pain Points:
- LLMs don't know most stock tickers outside the big ones well enough
- Tool calls to standard finance APIs in LangChain / Vercel AI SDK / LlamaIndex are brittle
- Integrating multiple sources (crypto API + FX API + stock market API) is a mess
Problems to Solve:
- Improve agent understanding of financial data through natural language queries
- Simplify integration of multiple financial data sources into a single query
- Enable agents to retrieve structured, ready-to-use financial data
Potential Solutions:
- A search API that allows agents to query financial market data in natural language
- An API that resolves nicknames to tickers and understands vague date ranges
- A system that returns OHLC + volume for all requested assets in one JSON
GROWTH FACTORS
Effective Strategies:
- Building a tool that solves a specific pain point for AI agents in finance
- Offering integrations with popular frameworks like LangChain, LlamaIndex, and Vercel AI SDK
- Providing SDKs for Python and TypeScript to increase accessibility
Marketing & Acquisition:
- Leveraging community engagement on platforms like Reddit and AI agent forums
- Demonstrating the value of the API through real-world use cases and examples
Monetization & Product:
- Focusing on solving a niche problem in the finance and AI agent space
- Expanding the API's capabilities beyond just stock market data to include research content like ArXiv and PubMed
User Engagement:
- Encouraging feedback and discussion through comments and community interaction
- Offering tools that can be easily integrated into existing workflows to improve user adoption