Data is Power.

The AI-native data layer for crypto. One API. One schema. No fragmentation. Watch an agent route, normalize, aggregate, and return confidence-scored data — live →

API Reference →

dataline-agent · live demolive

select a query below

⊘↵

[01] — pipeline

Intent in.
Confidence-scored data out.

Five stages, one API call. Each stage is testable, observable, replaceable independently.

Intent

intent.parse() — natural language to query

Describe what you need.

"BTC price" "ETH funding" "election odds"

Route

route.select() — best sources by latency

We pick the best sources.

smart routing multi provider fallback latency optimized

Normalize

schema.normalize() — same shape every venue

All data, one schema.

no vendor formats same shape across every venue

Aggregate

data_agreement() — cross source variance, outlier filtered

Reliable production output.

outlier filtering median / blended derived metrics

Output

output.emit() — JSON with confidence

Clean JSON with confidence.

{ symbol, price, confidence, source, ts }

[02] — coverage

Every market your agent might need.

Tier-A native integrations + Tier-B browser fallback (via GhostDriver) for the long tail.

◆

crypto markets

Spot · perps · orderbooks

→ Hyperliquid [live]
→ Coinbase
→ Binance
→ ...

pricevolumeorderbook

▲

prediction markets

Odds · events · resolution

→ Polymarket [live]
→ Kalshi
→ ...

oddseventsmarkets

✦

onchain data

Tx · balance · governance

→ Ethereum, Base
→ Solana
→ BNB · Sui · TON
→ ...

txbalancenft

★

web2 / social

News · sentiment · trends

→ Twitter / X
→ News APIs
→ Farcaster [soon]

newssentimenttrends

[03] — confidence

Your agent should know when to trust the data.

Every Dataline response ships with a confidence score so your agent can refuse or flag unreliable data BEFORE acting on it.

/ scoring model

confidence = score(agreement, freshness, coverage, source reliability)

data_agreement

Cross source variance, with outlier filtering.

source_reliability

Rolling uptime and latency per provider.

freshness

Time decay since each underlying source last ticked.

coverage

How much of the requested market, interval, and source set is represented.

Illustrative example · / source breakdown · BTC price

Source	Latency	Reliability	Used
Binance	84ms	0.99	✓
Hyperliquid	92ms	0.97	✓
Coinbase	204ms	0.99	✓
CoinGecko	512ms	0.88	✗

Aggregated confidence0.98

[04] — act layer

Read AND act on the same surface.

Same intent surface, write side. Non-custodial — your agent signs, your wallet broadcasts. Funds never leave the user.

trade

Hyperliquid trade-only

Open and close perp positions. Trade-only API permissions keep custody with your wallet.

swap

Uni v4 / Aerodrome

Token swaps with route quoting. We return signed tx; your wallet broadcasts.

bet

Polymarket bet

Place orders on prediction markets via the standard CLOB pattern.

browser

GhostDriver fallback

Long-tail dApps without an SDK — GhostDriver clicks through the UI for you.

[05] — playground

Try real data with natural language.

No signup. No credit card. Inspect the routing, the aggregation, and every raw source.

Sample responses are illustrative, not live market data. Live calls are used only when this deployment has configured API credentials.

/ examples

/ settings

Show raw sources

Stream mode

dataline-playground · query● ready

> get btc price

Connecting to Dataline Hub... Authorizing... Routing query: 2 sources picked Paying $0.0001 USDC on Basechain... Aggregating responses...

{

"status": "success",

"data": {

"symbol": "BTC",

"price": 67123.45,

"currency": "USD",

"confidence": 0.98,

"source": "aggregated"

"timestamp": 1716283345

}

$0.0001 USDC · 87ms · 2 sources✓ cached for 30s

/ Data interpretation

Read every value with context.

These rules apply to API responses, MCP tools, examples, and editorial data throughout Dataline.

Time

Timestamps are ISO 8601 in UTC unless an endpoint says otherwise. Freshness and latency are measured in seconds or milliseconds and are returned separately.

Units

Currency, quote asset, decimal precision, percentage basis, interval, and chain decimals belong in the response metadata. Never infer a unit from the field name alone.

Sources

Aggregated responses retain source identifiers and per-source freshness so callers can trace a value, inspect disagreement, or apply their own policy.

Missing values

Missing, stale, unsupported, and filtered values are distinct states. Null is never silently converted to zero, and partial coverage is surfaced instead of hidden.

Quality

Confidence is a versioned score based on agreement, freshness, coverage, and source reliability. It is evidence for a decision, not a guarantee of correctness.

Playground and code-block values are illustrative unless explicitly marked live. See the API reference for each endpoint’s field contract.

npm install·pip install·curl·MCP add-server

npm

pip

curl

MCP

# Install the SDK npm install @dataline/sdk # Make your first call import { Dataline } from '@dataline/sdk'; const tl = new Dataline({ apiKey: process.env.DATALINE_KEY }); const data = await tl.price('BTC'); console.log(data.price); // 67123.45 console.log(data.confidence); // 0.98

# Install the SDK pip install dataline # Make your first call from dataline import Dataline tl = Dataline(api_key=os.environ["DATALINE_KEY"]) data = tl.price("BTC") print(data.price) # 67123.45 print(data.confidence) # 0.98

# Hit the REST endpoint directly curl https://api.dataline.xyz/v1/price/BTC \ -H "Authorization: Bearer $DATALINE_KEY" # Response { "symbol": "BTC", "price": 67123.45, "confidence": 0.98, "source": "aggregated" }

# Remote MCP configuration { "mcpServers": { "dataline": { "url": "https://mcp.dataline.xyz", "transport": "streamable_http" } } } # Verified client-specific setup: https://www.dataline.xyz/mcp

Free tier, no card.

Per-call USDC. No signup.

→

MPP (Tempo)

Streaming micropayments per event.

→

Product contract

Dataline Data: role, use cases, and boundaries

A concise operating contract based on the Dataline Protocol whitepaper.

01 / Responsibility

The shared data foundation. It routes structured or natural-language intent to multiple sources, normalizes the result, and returns evidence with confidence metadata.

02 / Typical use cases

Market, prediction-market, DeFi, wallet, and news research
Grounding for ChatPilot, FlowAgent, trading agents, bots, and partner apps
Read-only wallet queries and preparation of unsigned transaction data

03 / Operating boundary

Data access is non-custodial. It does not hold private keys or sign transactions; wallet actions remain with the user or the calling application.

Data is Power.

500 free calls. No credit card. See the response shape in 30 seconds.

API Reference →

Data is Power.

Intent in.Confidence-scored data out.

Intent

Route

Normalize

Aggregate

Output

Every market your agent might need.

Spot · perps · orderbooks

Odds · events · resolution

Tx · balance · governance

News · sentiment · trends

Your agent should know when to trust the data.

Read AND act on the same surface.

Hyperliquid trade-only

Uni v4 / Aerodrome

Polymarket bet

GhostDriver fallback

Try real data with natural language.

Read every value with context.

Time

Units

Sources

Missing values

Quality

npm install·pip install·curl·MCP add-server

Free tier, no card.

Data is Power.

Intent in.
Confidence-scored data out.