Best APIs for Tracking New Token Launches in 2026

The short answer

"New token" is ambiguous, and the ambiguity matters because the events happen at different times:

• Token deployment — the contract or mint exists. Often meaningless on its own; anyone can deploy.
• First liquidity / new pair — the token becomes tradeable. This is the event most products actually want.
• Launchpad creation — a Pump.fun or Four.meme launch, which carries its own lifecycle including graduation.

A launch feed that fires on deployment drowns you in noise. One that fires on first liquidity is a trading signal.

• Bitquery — new pairs, token creation and launchpad lifecycle events across 40+ chains, streamed.
• Birdeye — new listings and discovery across its supported chains.
• DexScreener — widely used for new pair discovery, screener-first.
• Solana-native launch services — venue-specific feeds with execution attached.
• Dune — retrospective launch cohort analysis.

What to look for in a launch API

1. Which event fires. Deployment, first liquidity, or launchpad creation — and can you subscribe to them separately?
2. Latency. For launch strategies, seconds decide outcomes. Polling a REST endpoint is not competitive.
3. Cross-chain and cross-venue coverage. Launches move between chains and venues with fashion; single-venue coverage ages badly.
4. Immediate risk context. At launch you want the deployer's history, initial distribution, liquidity size and whether it is locked — a token address alone tells you nothing.
5. Lifecycle continuity. On launchpads, trading migrates after graduation. A feed that stops at the curve leaves a hole at the most liquid moment.

The best APIs for new token launches

1. Bitquery — best for cross-chain launch detection with context

Bitquery indexes token creation, first liquidity and new pair events across 300+ DEXs on 40+ chains, plus dedicated launchpad coverage for Pump.fun, PumpSwap, Raydium and Four.meme including bonding-curve trades, graduations and migrations.

The context is what makes it actionable. Because launches sit in the same schema as the rest of the chain, one integration also gives you the deployer's other tokens and holdings, initial holder distribution, early trade flow and liquidity events — the inputs to a risk score, available at the moment the token appears rather than hours later.

Streaming runs over WebSocket, Kafka with offset replay at under 500ms p95, and CoreCast gRPC at under 300ms on Solana.

Best for: sniping and discovery products, launch analytics, rug-risk scoring, cross-chain screeners.

Limitations: no execution — pair with an RPC provider. No Solana mempool, so pre-confirmation launch detection is not available there.

Pump.fun API · Four.meme API · DEX API · Docs: Pump.fun API

2. Birdeye — best for discovery UI and new listings

Birdeye surfaces new tokens, trending activity and security signals with a trader-facing discovery model.

Best for: discovery features and token pages.

Limitations: ten chains, and market-data granularity rather than full lifecycle events with deployer context.

3. DexScreener — best-known new pair screener

DexScreener is the reference screener for new pairs across many chains and venues, familiar to essentially every on-chain trader.

Best for: discovery, manual research, quick verification.

Limitations: screener-first; check current API terms and rate limits before designing a product around it.

4. Solana-native launch services

Several Solana services focus on launchpad feeds, often bundling execution.

Best for: single-venue bots wanting data and execution together.

Limitations: narrow scope; verify reliability and history depth.

5. Dune — best for retrospective launch analysis

Dune supports cohort studies — graduation rates, survival curves, deployer patterns.

Best for: research and dashboards.

Limitations: not a live feed.

Comparison

Provider	New pairs	Launchpad lifecycle	Deployer context	Cross-chain	Sub-second stream
Bitquery	Yes, 300+ DEXs	Pump.fun, PumpSwap, Four.meme	Yes, same schema	40+ chains	gRPC <300ms
Birdeye	Yes	Partial	Security signals	10 chains	WebSocket
DexScreener	Yes	Partial	Limited	Many chains	Check API terms
Solana launch services	Venue-specific	Yes, venue-specific	Varies	Solana	Varies
Dune	Yes, via SQL	Yes, via SQL	Yes, via SQL	Many	No

Building a launch risk score

The launch feed is the easy half. What separates a usable product from an alert firehose:

1. Liquidity size and lock status. Tiny or unlocked liquidity is the most common rug precondition.
2. Initial holder distribution. If the deployer and a handful of wallets hold nearly all supply, distribution is not real.
3. Deployer history. Previous tokens by the same address, and what happened to them, is the strongest single signal available at launch.
4. Early trade asymmetry. Buys succeeding while sells fail is the classic honeypot signature.
5. Sell pressure from insiders. Early recipients exiting into the first buyers.

All five are queries against transfers, trades and holder data — which is why launch detection and general chain indexing are best solved by the same provider rather than two.

FAQ

How do I detect new tokens in real time?

Subscribe to new pair creation and token deployment events rather than polling. Bitquery streams both over WebSocket, Kafka and gRPC, with CoreCast at under 300ms on Solana for latency-sensitive consumers.

Should I track token deployment or first liquidity?

First liquidity, for almost every trading use case. Deployment is cheap and constant; liquidity is the moment a token becomes tradeable and the point at which a signal has meaning.

How do I check whether a new token is a rug?

There is no single flag. Combine liquidity size and lock status, initial holder concentration, the deployer's previous tokens, and early buy/sell asymmetry. Treat any single-signal "safe" verdict — from any provider — with suspicion.

Can I track launches across multiple chains at once?

Yes, with a unified schema. Bitquery covers new pairs across 40+ chains with the same query shape, so adding a chain is a parameter change rather than another integration.

What is the fastest way to detect a Pump.fun launch?

A gRPC stream on token creation events. Bitquery's CoreCast delivers under 300ms, and the same subscription can carry the first bonding-curve trades so you see initial buys immediately. Benchmark against alternatives on your own infrastructure before committing.

Related reading

• Bitquery vs Birdeye
• Bitquery vs Helius
• Pump.fun API · Four.meme API · DEX API