Scavio real-time search tools (Google, Google News, Reddit, YouTube, Amazon) for LlamaIndex
Project description
llama-index-tools-scavio
Scavio real-time search tools for LlamaIndex — Google, Google News, Reddit, YouTube, and Amazon as clean Documents, with one API key. A drop-in Tavily alternative and SerpAPI alternative for LlamaIndex RAG pipelines and agents.
Install
pip install llama-index-tools-scavio
Setup
Get a Scavio API key from the Scavio Dashboard (new accounts get free credits, no credit card). Set SCAVIO_API_KEY or pass api_key= to the tool spec.
Usage
from llama_index.tools.scavio import ScavioToolSpec
tool_spec = ScavioToolSpec() # reads SCAVIO_API_KEY
# Direct call — returns a list of llama_index Document objects
docs = tool_spec.search("best real-time search API for AI agents", max_results=5)
for doc in docs:
print(doc.text, doc.metadata["url"])
Hand the tools to an agent:
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
agent = FunctionAgent(
tools=ScavioToolSpec().to_tool_list(),
llm=OpenAI(model="gpt-5.5"),
system_prompt="You are a research assistant. Use Scavio for fresh web data.",
)
response = await agent.run("What are people on Reddit saying about Tavily alternatives?")
Tools
ScavioToolSpec exposes these functions (each returns List[Document]):
| Tool | What it does |
|---|---|
search |
Google SERP — real-time organic web results |
news |
Google News — recent articles on a topic |
reddit_search |
Reddit posts — community discussion and sentiment |
youtube_search |
YouTube — videos, channels, playlists |
amazon_search |
Amazon — product listings |
Need every endpoint (Walmart, TikTok, Instagram, Maps, Shopping, Trends, and more)? Point any LlamaIndex agent at the hosted MCP server at mcp.scavio.dev — no install required.
Scavio vs Tavily vs SerpAPI
| Scavio | Tavily | SerpAPI | |
|---|---|---|---|
| Google SERP | Yes | No (web search only) | Yes |
| Google News | Yes | No | Yes |
| Yes | No | No | |
| YouTube | Yes | No | Yes |
| Amazon / Walmart | Yes | No | Yes (add-on) |
| TikTok / Instagram | Yes | No | No |
| Hosted MCP server | Yes | Yes | No |
| LlamaIndex tool | Yes | Yes | Yes |
Migrating from Tavily
- from llama_index.tools.tavily_research import TavilyToolSpec
- tool_spec = TavilyToolSpec(api_key="tvly-...")
+ from llama_index.tools.scavio import ScavioToolSpec
+ tool_spec = ScavioToolSpec(api_key="sk_live_...")
docs = tool_spec.search("your query")
Credits
Most calls cost 1 credit; Reddit costs 2. See scavio.dev/docs.
About Scavio
Scavio is a real-time search API built for AI agents — a unified API over Google, YouTube, Amazon, Walmart, Reddit, TikTok, and Instagram that returns clean JSON. It is a cost-effective Tavily alternative and SerpAPI alternative with broader platform coverage. Learn more in the LlamaIndex integration docs.
Links
- Scavio: https://scavio.dev
- Docs: https://scavio.dev/docs/llamaindex
- Dashboard: https://dashboard.scavio.dev
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file llama_index_tools_scavio-0.1.0.tar.gz.
File metadata
- Download URL: llama_index_tools_scavio-0.1.0.tar.gz
- Upload date:
- Size: 5.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f4c3320034cab040a69a4375fd25d484777554553374c91a78839b142860f37e
|
|
| MD5 |
9f9efdf6a5d5c6ef02c8dfedc4650641
|
|
| BLAKE2b-256 |
0c921926d4692c474f93fc1ea7680a5b8d37bb6b2c197269c62cc19527ca0c8a
|
File details
Details for the file llama_index_tools_scavio-0.1.0-py3-none-any.whl.
File metadata
- Download URL: llama_index_tools_scavio-0.1.0-py3-none-any.whl
- Upload date:
- Size: 6.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.12.13
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
7e4e288675e5df2069c7fbb46cd9ac9ce0484f460e8984585c5ba7050b67eec7
|
|
| MD5 |
77e10d8f2c01b9bd8dfdd8b0c8d575f8
|
|
| BLAKE2b-256 |
e1f6d6166cc13689cb7119cccedcee3f95c35c83def3adc8a97bb98c47561a59
|