Quickstart

For AI agents: Use llms.txt for a full index of all documentation.

Add Tako to your agent

The fastest way to build with Tako. Paste one prompt into your coding agent to wire Tako into an existing project, or create a new Tako agent from the console.

Build a Tako agent from scratch
Add to your agent

Create a Tako-powered agent

Follow the agent quickstart in the console. It generates a prompt for your coding agent in seconds to build with the Tako APIs.

Installation

Tako ships official SDKs for Python and TypeScript / JavaScript. Every endpoint is also a single POST, so any other language works over the REST API directly.

pip install tako-sdk

npm install tako-sdk

npm install @takoviz/ai-sdk ai @ai-sdk/openai

https://mcp.tako.com/mcp

For one-click MCP setup in Claude, ChatGPT, Cursor, and VS Code, see the MCP server page.

Get your API key

New to Tako? Sign up and get free credits to start building.

Create an API key

Create an API key from your Tako console.

Store it as an environment variable

Store it as an environment variable — for example TAKO_API_KEY — rather than hardcoding it.

Pick the right tool

Each API is a single call over the same curated, real-time data. Here’s what each one is for.

Answer

You want the question answered, not the data."Should I wear a jacket in New York this week?"Returns — a written answer, with the sources behind it.

Search

You want the data itself, and you’ll do the rest."Nvidia quarterly revenue"Returns — knowledge cards and web results, no LLM in the loop.

You have a result already, and you need what’s under it."https://tako.com/card/…"Returns — that card’s rows as CSV, or a web page as clean text.

Agent

The question needs real work before anything can answer it."Which of the 20 largest US semiconductor companies grew revenue fastest since 2015?"Returns — a cited brief from an asynchronous research job.

Already have your own data? Thin-Viz turns it into interactive, embeddable Tako cards. Want to see what data is available? The Data Graph lets you explore the entities and metrics Tako covers, then pin exactly what you find into Search. It consumes no credits, so it’s the cheapest way to find out what Tako has before you query it.

Make your first request

Pick the use case closest to what you’re building. Each is a single call over the same real-time data — the code and the live result below both change to match.

Stock prices
Sports
Research
Build an agent

Search returns fast, structured knowledge cards for a query — no LLM in the loop. Ideal for pulling live prices you render or compute on yourself.

Code

curl -X POST https://tako.com/api/v3/search \
  -H "X-API-Key: $TAKO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "What are today'\''s top performing stocks?"
  }'

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 are today's top performing stocks?"))
for card in results.cards or []:
    print(card.title, card.webpage_url)

import { Tako } from "tako-sdk";

const tako = new Tako({ apiKey: process.env.TAKO_API_KEY! });

const results = await tako.search({ query: "What are today's top performing stocks?" });
for (const card of results.cards ?? []) {
  console.log(card.title, card.webpage_url);
}

Result

A knowledge card — a full data series with its sources, ready to render or compute on.

Answer returns one written, source-attributed answer plus the Tako cards that back it — in a single call, no retrieval to wire up.

Code

curl -X POST https://tako.com/api/v1/answer \
  -H "X-API-Key: $TAKO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How has Luka Dončić'\''s points per game trended this season?"
  }'

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)

response = client.answer(SearchRequest(query="How has Luka Dončić's points per game trended this season?"))
print(response.answer)
for card in response.cards or []:
    print(card.title, card.webpage_url)

import { Tako } from "tako-sdk";

const tako = new Tako({ apiKey: process.env.TAKO_API_KEY! });

const response = await tako.answer({ query: "How has Luka Dončić's points per game trended this season?" });
console.log(response.answer);
for (const card of response.cards ?? []) {
  console.log(card.title, card.webpage_url);
}

Result

Answer: Luka Dončić is averaging 33.5 points per game this season. His monthly PPG has fluctuated — 38.2 in October, 32.5 in November, 31.0 in December, 34.0 in January, 27.0 in February, and back up to 37.5 in March.

The Answer Agent is an asynchronous deep-research agent for multi-step questions — resolving a cohort, then ranking it across many entities — returning cited prose. Dispatch a run, then poll until it’s done. Want the cards rather than the write-up? Use the Retrieval Agent (/v1/agent/retrieval/runs) instead.

Code

# 1. Dispatch — returns 202 with {"run_id": "...", "status": "queued"}.
curl -X POST https://tako.com/api/v1/agent/answer/runs \
  -H "X-API-Key: $TAKO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Which of the Magnificent Seven tech companies has grown revenue the fastest over the past five years?"
  }'

# 2. Poll with the run_id until status is "completed" or "failed".
curl https://tako.com/api/v1/agent/answer/runs/RUN_ID \
  -H "X-API-Key: $TAKO_API_KEY"

import os
import time
from tako import Configuration, AnswerAgentRunRequest
from tako.lib import Tako

config = Configuration()
config.api_key["apiKey"] = os.environ["TAKO_API_KEY"]
client = Tako(config)

run = client.agent.answer.run(
    AnswerAgentRunRequest(query="Which of the Magnificent Seven tech companies has grown revenue the fastest over the past five years?")
)

# Runs can take minutes — poll on a short interval until terminal.
while run.status not in ("completed", "failed"):
    time.sleep(3)
    run = client.agent.answer.get(run.run_id)

print(run.result.answer)

import { Tako } from "tako-sdk";

const tako = new Tako({ apiKey: process.env.TAKO_API_KEY! });

let run = await tako.agent.answer.run({
  query: "Which of the Magnificent Seven tech companies has grown revenue the fastest over the past five years?",
});

// Runs can take minutes — poll on a short interval until terminal.
while (run.status !== "completed" && run.status !== "failed") {
  await new Promise((r) => setTimeout(r, 3000));
  run = await tako.agent.answer.get(run.run_id);
}

console.log(run.result?.answer);

Result

Answer: NVIDIA grew revenue the fastest over the past five years — from $16.7B in 2020 to $215.9B in 2025, a five-year CAGR of 66.9%. The rest of the Magnificent Seven trailed well behind: Tesla at 24.6%, Meta at 18.5%, Alphabet at 17.2%, Microsoft at 14.5%, Amazon at 13.2%, and Apple at 8.7%.

Prime an agent with exact, source-grounded numbers: Search finds the card, then Contents downloads the exact series behind it as CSV — so your agent computes on real values instead of prose. Those two calls are the whole loop.Resolving through the Data Graph first is an optional upgrade, shown as step 1 below. It trades one extra call for deterministic retrieval: instead of hoping a text query lands on the right card, you resolve the entity and metric to node ids and pin them, so Search can only return cards built from exactly those nodes. Graph calls consume no credits.

Want to skip it? Start at step 2 and send just the query — {"query": "Palantir federal contract obligations"} finds this same card without any graph calls. Drop the whole sources block when you do: strict: true requires a non-empty node_ids list and returns a 400 on its own.

Code

# 1. OPTIONAL: resolve the entity and the metric to graph node ids (no credits).
ENTITY_ID=$(curl -s -G https://tako.com/api/v1/graph/search \
  -H "X-API-Key: $TAKO_API_KEY" \
  --data-urlencode "q=Palantir Technologies" \
  --data-urlencode "types=entity" | jq -r '.results[0].id')

METRIC_ID=$(curl -s -G https://tako.com/api/v1/graph/search \
  -H "X-API-Key: $TAKO_API_KEY" \
  --data-urlencode "q=federal contract obligations" \
  --data-urlencode "types=metric" | jq -r '.results[0].id')

# 2. Pin both ids into Search. strict returns only cards matching a pinned node.
CARD_URL=$(curl -s -X POST https://tako.com/api/v3/search \
  -H "X-API-Key: $TAKO_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{
    \"query\": \"Palantir federal contract obligations\",
    \"sources\": {\"data\": {\"node_ids\": [\"$ENTITY_ID\", \"$METRIC_ID\"], \"strict\": true}}
  }" | jq -r '.cards[0].webpage_url')

# 3. Contents downloads the exact numbers behind the card.
curl -X POST https://tako.com/api/v1/contents \
  -H "X-API-Key: $TAKO_API_KEY" \
  -H "Content-Type: application/json" \
  -d "{\"url\": \"$CARD_URL\", \"mode\": \"inline\"}"

import os
from tako import Configuration, SearchRequest, Sources, DataSourceSettings, ContentsRequest
from tako.lib import Tako

config = Configuration()
config.api_key["apiKey"] = os.environ["TAKO_API_KEY"]
client = Tako(config)

# 1. OPTIONAL: resolve the entity and the metric to graph node ids (no credits).
entity = client.graph_search("Palantir Technologies", types="entity").results[0]
metric = client.graph_search("federal contract obligations", types="metric").results[0]

# 2. Pin both ids into Search. strict returns only cards matching a pinned node.
results = client.search(
    SearchRequest(
        query="Palantir federal contract obligations",
        sources=Sources(
            data=DataSourceSettings(node_ids=[entity.id, metric.id], strict=True)
        ),
    )
)
card = results.cards[0]

# 3. Contents downloads the exact numbers behind it — feed the CSV to your agent.
contents = client.contents(ContentsRequest(url=card.webpage_url, mode="inline"))
print(contents.contents[0].data)

import { Tako } from "tako-sdk";

const tako = new Tako({ apiKey: process.env.TAKO_API_KEY! });

// 1. OPTIONAL: resolve the entity and the metric to graph node ids (no credits).
const entity = (await tako.graphSearch({ q: "Palantir Technologies", types: "entity" })).results[0];
const metric = (await tako.graphSearch({ q: "federal contract obligations", types: "metric" })).results[0];

// 2. Pin both ids into Search. strict returns only cards matching a pinned node.
const results = await tako.search({
  query: "Palantir federal contract obligations",
  sources: { data: { node_ids: [entity.id, metric.id], strict: true } },
});
const card = results.cards![0];

// 3. Contents downloads the exact numbers behind it — feed the CSV to your agent.
const contents = await tako.contents({ url: card.webpage_url!, mode: "inline" });
console.log(contents.contents![0].data);

If you do pin, resolve the ids at request time as above — never hardcode them. Ids are not durable across knowledge-graph rebuilds; Search silently skips one that no longer resolves, and with strict: true that leaves you with no cards.

Result

Step 1, optional — Graph Search resolves each name to a node: an ent:: id for the company, an mt:: id for the metric. Two calls, one results[0] each:

// q=Palantir Technologies&types=entity
{"id": "ent::palantir_technologie::1d41d233", "type": "entity", "name": "Palantir Technologies Inc.", "subtype": "Companies", "label": "ORG"}

// q=federal contract obligations&types=metric
{"id": "mt::federal_contract_obl::1e937180", "type": "metric", "name": "Federal Contract Obligations", "label": "METRIC"}

Search, pinned to those two nodes, returns the card they describe — Palantir’s federal contract obligations by fiscal year. The plain query returns this same card; pinning is what guarantees it:

Contents hands your agent the exact series behind it, as CSV — ready to compute on:

Timestamp,Federal Contract Obligations (USD)
2008-10-01 00:00:00+00:00,135211.06
2009-10-01 00:00:00+00:00,4378216.96
2010-10-01 00:00:00+00:00,5801023.5
...
2024-10-01 00:00:00+00:00,541197885.14
2025-10-01 00:00:00+00:00,1020566208.97
2026-10-01 00:00:00+00:00,896657523.63

Next steps

Developer Playground

No setup required. Try a simple query like “Nvidia earnings” or a long-form prompt to see what Tako returns.

What is Tako?

Learn more about Tako’s key concepts and functionality.

Getting Started

Build with Tako

API Reference

Integrations

Additional Resources

Add Tako to your agent

Create a Tako-powered agent

Installation

Get your API key

Pick the right tool

Answer

Search

Contents

Agent

Make your first request

Next steps

Developer Playground

What is Tako?

​Add Tako to your agent

Create a Tako-powered agent

​Installation

​Get your API key

​Pick the right tool

Answer

Search

Contents

Agent

​Make your first request

​Next steps

Developer Playground

What is Tako?

Add Tako to your agent

Installation

Get your API key

Pick the right tool

Make your first request

Next steps