Seeking Feedback & Collaboration: Talordata - A Multi-Engine SERP API for LangChain Agents & RAG Workflows

Talking Shop
1

Hi everyone,

I’ve been working with LangChain (and LangGraph) for building agents and RAG systems. One pain point I often encounter is the cost and single-engine limitation of existing search tools (like Tavily, Serper, or SerpAPI) when doing high-volume monitoring or multi-region searches.

I’ve been exploring Talordata, a multi-engine SERP API (Google + Bing + Yandex + others) that emphasizes:

  • Pay-per-success pricing (often cheaper at scale)
  • Strong structured JSON output
  • Good support for AI Overviews, local results, and shopping data

What I’m Looking For

I’d love to get community feedback on the following:

  1. Would a dedicated langchain-talordata integration (as a Tool / Retriever) be useful for the ecosystem?
  2. What features would you want most? (e.g. async support, retry logic, specific output parsing, MCP compatibility, etc.)
  3. Any existing pain points with current search tools that this could address?

Proposed Contribution

I’m planning to open-source a lightweight integration package following LangChain’s contribution guidelines. If there’s interest, I can:

  • Share a early MVP / GitHub repo for testing
  • Add it as a community integration
  • Provide example usage with LangGraph agents

Has anyone here tried Talordata or similar multi-engine tools in LangChain? Any feedback, suggestions, or interest in collaborating on the integration would be greatly appreciated!

Thanks in advance :folded_hands:
Looking forward to your thoughts.