> ## Documentation Index
> Fetch the complete documentation index at: https://docs.tako.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Search
export const CodingAgentCTA = ({description, href}) =>
{description} Building with a coding agent?{" "}
Give your agent the full reference →
;
export const PlaygroundButton = ({href = "https://tako.com/playground", label = "Try in Playground"}) => ;
## When to use Search
[Search](/api-reference/search-v3) is for **fast retrieval you render or post-process yourself**, with no written answer on top. One call returns **both** kinds of result — **data results** (interactive Tako knowledge cards backed by structured data) **and web search results**. Reach for it when:
There's no answer-synthesis LLM call in the loop, so results come back fast — quick enough to fan out across many entities in parallel.
Call Search repeatedly — one query per entity — and act on structured results instead of waiting on generated text.
Each result is a knowledge card — a full data series with its sources and methodology, not a lone value — so one query returns the surrounding context too, ready to render or compute on.
No single source has everything, so Search queries Tako's curated index (finance, macro, geopolitics, sports, weather) **and** the live web **by default** — broad coverage you can trust.
Choosing between Tako's surfaces (see the [full comparison](/documentation/integrating-tako/agent/overview#choosing-a-tako-surface)):
| Surface | What it's for |
| ---------------------------------------------------------------- | ------------------------------------------------------------------------------------------ |
| **[Search](/api-reference/search-v3)** | Fast, parallel retrieval of structured data and cards, in one call, no synthesized answer. |
| **[Answer](/documentation/integrating-tako/answer/overview)** | A written, source-attributed answer over the same retrieval, in one call. |
| **[Search Agent](/documentation/integrating-tako/agent/search)** | Multi-step research returning schema-defined structured data and cards. |
| **[Answer Agent](/documentation/integrating-tako/agent/answer)** | Deep research synthesizing a cited answer backed by visualizations. |
## Example
```bash theme={null}
curl -X POST https://tako.com/api/v3/search \
-H "X-API-Key: YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"query": "What is the price of Silver?"
}'
```
```bash theme={null}
pip install tako-sdk
```
```python theme={null}
import os
from tako import Configuration, SearchRequest
from tako.lib import Tako
config = Configuration()
config.api_key["apiKey"] = os.environ["TAKO_API_KEY"]
client = Tako(config)
results = client.search(SearchRequest(query="What is the price of Silver?"))
print(results.request_id)
for card in results.cards or []:
print(card.title, card.webpage_url)
```
Query: "What is the price of Silver?"
## Use cases
Fan out Search calls in an agentic loop to gather fresh, structured data fast.
```python theme={null}
for ticker in ["NVDA", "AMD", "INTC"]:
results = client.search(SearchRequest(query=f"{ticker} quarterly revenue"))
```
Restrict to Tako's authoritative knowledge graph when you only want vetted sources.
```python theme={null}
results = client.search(SearchRequest(query="US inflation rate", sources={"data": {}}))
```
Embed the live visualization from each result straight into your UI.
```python theme={null}
results = client.search(SearchRequest(query="S&P 500 over the last 5 years"))
for card in results.cards or []:
print(card.embed_url) # drop into an