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A Solana trading bot for pump.fun and letsbonk.fun. Its core feature is sniping new tokens: it watches for token creation, buys, and exits on a strategy you configure. cookbook/ holds one standalone script per action — buy a coin, create one, watch for new ones, decode a transaction — useful on their own even if you never run the bot.

For the full walkthrough, see Solana: Creating a trading and sniping pump.fun bot. It explains the concepts well but lags behind the code, so treat this README as the source of truth for setup and configuration.

Also by Chainstack — if you prefer a terminal interface or want to give an AI agent trading capabilities:

• pumpfun-cli — CLI for trading, launching, and managing tokens on pump.fun; buy, sell, wallet management, and smart routing between the bonding curve and PumpSwap AMM.
• pumpclaw — agent skill that equips AI assistants (OpenClaw, Claude Code, Cursor, Codex) with the ability to operate pumpfun-cli.

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🚨 SCAM ALERT: The Issues section is regularly targeted by scam bots that try to redirect you to an external site and drain your funds. A GitHub Action tags the common patterns, which is not 100% accurate. Deleted comments in issues are scam bots after your private keys — genuine outside devs are welcome and appreciated.

⚠️ NOT FOR PRODUCTION: This code is for learning purposes only. We assume no responsibility for the code or its usage. Modify it for your needs and learn from it — the examples, issues, and PRs contain valuable insights.

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Getting started

1. Prerequisites

Install uv, a fast Python package manager. The project needs Python 3.11+; uv uses an existing install if it's new enough, otherwise it fetches one for you.

2. Clone and install

git clone https://github.com/chainstacklabs/pumpfun-bonkfun-bot.git
cd pumpfun-bonkfun-bot

uv sync                        # create .venv and install dependencies
source .venv/bin/activate      # Unix/macOS — Windows: .venv\Scripts\activate
uv pip install -e .            # install the bot as an editable package

3. Set your credentials

cp .env.example .env

Fill in .env:

Variable	Purpose
SOLANA_NODE_RPC_ENDPOINT	HTTPS RPC endpoint
SOLANA_NODE_WSS_ENDPOINT	WebSocket endpoint (for logs / blocks listeners)
SOLANA_PRIVATE_KEY	Base58 private key of the trading wallet
GEYSER_ENDPOINT, GEYSER_API_TOKEN, GEYSER_AUTH_TYPE	Only for the geyser listener

Public RPC nodes will not work for this workload — see throughput below.

4. Configure a bot

Each YAML file in bots/ is one bot instance. They ship with commented defaults; start from the one matching the listener you want:

File	Listener	Ships with
bot-sniper-1-geyser.yaml	geyser — fastest, needs a Geyser endpoint	pump_fun
bot-sniper-2-logs.yaml	logs — logsSubscribe, supported everywhere	pump_fun
bot-sniper-3-blocks.yaml	blocks — blockSubscribe, not supported by every provider	pump_fun
bot-sniper-4-pp.yaml	pumpportal — third-party aggregator, misses some coins	lets_bonk

Set platform: "pump_fun" or platform: "lets_bonk". pump.fun supports all four listeners; letsbonk.fun supports blocks, geyser, and pumpportal but not logs. The bot validates the pairing at startup and refuses to run an invalid one.

pumpportal is a third-party feed and only reports what it indexes. As of 2026-09-16 it does not push coins whose creation landed in a Solana transaction v1 (a format live since 2026-09-15), so it sees a sample rather than everything. geyser and logs read the chain directly and are unaffected; blocks needs maxSupportedTransactionVersion: 1, which it now sends.

Set enabled: false to keep a config around without running it. Every bot with enabled: true starts when you run the bot.

5. Run

pump_bot                   # as an installed package
uv run src/bot_runner.py   # or directly

Logs land in logs/{bot_name}_{timestamp}.log.

Configuration reference

The YAML files are commented inline. The sections that matter most:

• trade — buy_amount (in SOL), slippage, exit_strategy (time_based, tp_sl, manual), and extreme_fast_mode, which skips the bonding-curve price check and buys a fixed token amount instead. Faster, less precise. See Extreme fast mode for the zero-RPC behavior and its two knobs, trust_create_event and curve_refresh_budget.
• priority_fees — fixed or dynamic. Dynamic costs an extra RPC call, which slows the buy.
• filters — listener_type, max_token_age, name/creator matching, marry_mode (buy only, never sell), yolo_mode (trade continuously).
• retries — attempts and the wait windows around creation, buy, and the next token.
• cleanup — when to close leftover token accounts: disabled, on_fail, after_sell, post_session.
• node.max_rps — cap requests per second to match your provider's plan.

Extreme fast mode: zero-RPC buys

With extreme_fast_mode: true the bot buys a fixed token amount (extreme_fast_token_amount) instead of fetching the curve price first. For tokens detected through the on-chain CreateEvent — the geyser, logs and blocks listeners — the buy is built entirely from the event: the canonical creator, mayhem/cashback flags and quote mint are all in it, so no RPC call happens between detecting the token and submitting the buy. That is the point of the mode; a single account read costs ~40–50 ms even on a good endpoint, a tenth of a slot.

The pumpportal listener can't do this — its payload carries none of those fields — so it performs one batched account read (bonding curve + mint in a single slot-consistent getMultipleAccounts) before buying. If the curve isn't readable within trade.curve_refresh_budget seconds (default 2.0), the token is skipped: a buy built from guessed accounts reverts on-chain with NotAuthorized (6000) or ConstraintSeeds (2006) and still costs the fee. The same skip applies to any token whose event data was incomplete.

trade.trust_create_event: false turns the zero-RPC path off and forces the pre-buy read for every listener — the safe fallback if pump.fun changes what the CreateEvent carries.

Machine checks: tests/regression/verify_extreme_fast_zero_rpc.py (the zero-RPC contract per listener) and tests/regression/verify_pumpportal_buy_path.py (the refresh/skip path). Neither moves funds.

Non-SOL quote assets

pump.fun supports quote assets other than SOL, USDC first. Amounts are in that mint's own whole units, so usdc: 1.0 is one USDC and is not comparable to buy_amount:

trade:
  buy_amount: 0.0001    # SOL-paired coins
  quote_amounts:
    usdc: 1.0           # USDC-paired coins

filters:
  allowed_quote_mints: ["sol", "usdc"]   # omit to allow any configured quote

Keys accept the aliases sol / wsol / usdc or a raw base58 mint. A coin whose quote mint has no configured amount is skipped with a log line rather than bought with a wrongly-scaled amount. SOL always falls back to buy_amount, so existing configs keep working untouched. Buying a USDC-paired coin needs USDC in the wallet plus a little SOL for fees and ATA rent.

Cookbook

cookbook/ is one script per thing you might want to do — buy a coin, create one, watch for new ones, decode a transaction. Each runs on its own with uv run <path>, reads .env directly, and needs no bot config. cookbook/README.md is the index; the shape is:

Directory	What is in it
cookbook/pumpfun/listen/	One script per detection method — logs, blocks, geyser, pumpportal — plus wallet watching
cookbook/pumpfun/read/	Price, curve state, graduation progress, address derivation
cookbook/pumpfun/trade/	Buy, sell, create, and the two sniping variants
cookbook/pumpfun/graduation/	Coins approaching graduation, and migrations to PumpSwap
cookbook/pumpfun/decode/	Account data and transactions, against committed fixtures
cookbook/solana/	Chain-level basics: balances, transaction status, Anchor discriminators
cookbook/pumpswap/	Pool discovery and manual buy/sell on the AMM
cookbook/letsbonk/	Exact-in / exact-out buys and sells on letsbonk.fun
cookbook/legacy/	Instructions pump.fun has moved on from

The quickest way in:

uv run cookbook/solana/solana_read_balances.py               # what you hold
uv run cookbook/pumpfun/read/pumpfun_read_price.py <CURVE>   # what it costs
uv run cookbook/pumpfun/trade/pumpfun_buy_token_v2.py <MINT> --dry-run

Filenames follow <protocol>_<verb>_<noun>[_<variant>].py, so a name tells you which chain, what it does and which instruction version before you open it. Scripts that spend real funds say so on the first line of their docstring. The decode scripts fall back to the fixtures beside them (raw_*.json), which are recaptured from mainnet rather than hand-edited — a stale fixture makes a working decoder look broken and a broken one look fine.

Related docs: Listening to pump.fun migrations · Sniping with only logsSubscribe

Regression checks

tests/regression/ holds one offline script per bug that has been fixed here. They import the bot's own code, move no funds, and each one's docstring names the bug it guards. Run them after any pump.fun program upgrade or change to src/:

uv run tests/regression/run_all.py                      # the whole set
uv run tests/regression/verify_v2_account_layout.py     # account layouts, PDAs, encoding
uv run tests/regression/verify_curve_account_sizes.py   # 125/151/256-byte curves all decode
uv run tests/regression/verify_tx_status_checks.py      # every path reads meta.err

Development tools

tools/ holds the scripts used to exercise the bot rather than teach it. They import src/ and several of them spend real funds — read the module docstring first.

uv run tools/simulate_v2_trades.py <MINT>    # mainnet simulation, no funds moved
uv run tools/simulate_bot_buy_path.py        # the bot's buy path against a fresh coin, no funds moved
uv run tools/compare_listeners.py            # race all four listeners against each other
uv run tools/compare_migration_listeners.py  # race the two migration detection methods
uv run tools/cleanup_accounts.py [MINT]      # close leftover token accounts — submits transactions
uv run tools/live_v2_round_trip.py --yes     # real buy_v2 + sell_v2 — SPENDS REAL FUNDS
uv run tools/live_listener_matrix.py --yes   # real round trip per listener — SPENDS REAL FUNDS

Throughput and rate limits

Every node provider has its own limits — method availability, requests per second, plan-specific caps. Consult your provider's docs before running the bot, and don't expect public RPC nodes to hold up.

One case worth knowing about: getProgramAccounts over the whole pump.fun program is no longer served by anyone. That program owns more than 10 million accounts, so providers reject the request or time out no matter which filters you pass. Use a filtered subscription instead — cookbook/pumpfun/graduation/pumpfun_watch_graduating_programsubscribe.py shows the pattern.

For Chainstack, the numbers you need are in the throughput guidelines, kept up to date.

The bot rate-limits itself with a token bucket: node.max_rps in the YAML (25 by default) smooths the request rate while allowing short bursts, and 429s are retried with exponential backoff.

For faster execution, Chainstack offers Solana Trader nodes for transaction propagation and the Yellowstone gRPC Geyser plugin for streaming updates.

IDLs

The IDLs under idl/ are vendored from pump-fun/pump-public-docs — currently upstream commit 8109141. To refresh, copy pump.json, pump_amm.json, and pump_fees.json into pump_fun_idl.json, pump_swap_idl.json, and pump_fees.json, and note the upstream commit in your commit message. Don't hand-edit them.

The buy_v2 / sell_v2 account lists are complete in the IDL — that's the point of the v2 interface. The legacy buy / sell lists are not: the IDL omits PDAs the on-chain program requires. For anything outside v2, cross-check against a recent successful on-chain transaction before trusting the IDL.

CLAUDE.md documents the protocol gotchas in detail — account layouts, quote-mint handling, fee recipients, and what the IDL gets wrong.

Contributing

Maintainers are listed in MAINTAINERS.md. Open an Issue for feedback or bugs.

Lint and format the files you changed (uv sync installs ruff for you):

uv run ruff check --fix path/to/changed.py
uv run ruff format path/to/changed.py

Running ruff check over the whole repo reports a large backlog of pre-existing errors — that's a known baseline, so scope it to your own files.

Then test your change with a learning example rather than by running a bot with real funds.