Exa RAG Integration

Quick Reference

Topic When to Use Reference

LangChain Building RAG chains with LangChain langchain.md

LlamaIndex Using Exa as a LlamaIndex data source llamaindex.md

Vercel AI SDK Adding web search to Next.js AI apps vercel-ai.md

MCP & Tools Claude MCP server, OpenAI tools, function calling mcp-tools.md

Essential Patterns

LangChain Retriever

from langchain_exa import ExaSearchRetriever

retriever = ExaSearchRetriever( exa_api_key="your-key", k=5, highlights=True )

docs = retriever.invoke("latest AI research papers")

LlamaIndex Reader

from llama_index.readers.web import ExaReader

reader = ExaReader(api_key="your-key") documents = reader.load_data( query="machine learning best practices", num_results=10 )

Vercel AI SDK Tool

import { exa } from "@agentic/exa"; import { createOpenAI } from "@ai-sdk/openai"; import { generateText } from "ai";

const result = await generateText({ model: openai("gpt-4"), tools: { search: exa.searchAndContents }, prompt: "Search for the latest TypeScript features", });

OpenAI-Compatible Endpoint

from openai import OpenAI

client = OpenAI( base_url="https://api.exa.ai/v1", api_key="your-exa-key" )

response = client.chat.completions.create( model="exa", messages=[{"role": "user", "content": "What are the latest AI trends?"}] )

Integration Selection

Framework Best For Key Feature

LangChain Complex chains, agents ExaSearchRetriever, tool integration

LlamaIndex Document indexing, Q&A ExaReader, query engines

Vercel AI SDK Next.js apps, streaming Tool definitions, edge-ready

OpenAI Compat Drop-in replacement Minimal code changes

Claude MCP Claude Desktop, Claude Code Native tool calling

Common Mistakes

• Not using highlights for RAG - Full text wastes context; use highlights=True for relevant snippets

• Missing source attribution - Always include result.url in citations for grounded responses

• Ignoring summaries - summary=True provides concise context without full page overhead

• Over-fetching results - Start with 3-5 results; more isn't always better for RAG quality

• Not filtering domains - Use include_domains to limit to authoritative sources

• Skipping date filters - For current events, always add start_published_date to avoid stale info

• Forgetting async patterns - Use async retrievers in production for better throughput