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Solanatracker Api

Community
agiprolabs
solanatracker-api

Solana token data, PnL, risk scores, 1-second OHLCV, wallet analytics, and self-hosted swap execution via Raptor

Overview

Publisheragiprolabs
Repositoryclaude-trading-skills
Skill namesolanatracker-api
Stars
434
Forks
85
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by agiprolabs on GitHub. Read the source before you install it.

Installation

Install the Solanatracker Api AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/agiprolabs/claude-trading-skills/tree/main/skills/solanatracker-api
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/agiprolabs/claude-trading-skills.git /tmp/claude-trading-skills
mkdir -p .claude/skills
cp -r /tmp/claude-trading-skills/skills/solanatracker-api .claude/skills/solanatracker-api
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Solanatracker Api in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Solanatracker Api on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Solanatracker Api is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

SolanaTracker API — Token Data, Analytics & Raptor DEX Aggregator

SolanaTracker provides comprehensive Solana token data with unique features: 1-second OHLCV resolution, wallet PnL tracking, risk scoring, bundler/sniper detection, and a self-hosted DEX aggregator (Raptor) supporting 25+ DEXes with no rate limits.

Quick Start

python
import httpx

API_KEY = os.getenv("SOLANATRACKER_API_KEY", "")
BASE = "https://data.solanatracker.io"
HEADERS = {"x-api-key": API_KEY}

# Token info with risk score, pools, holders
resp = httpx.get(f"{BASE}/tokens/{mint}", headers=HEADERS)
token = resp.json()
print(f"Risk: {token['risk']['score']}/10, Pools: {len(token['pools'])}")

# Wallet PnL
resp = httpx.get(f"{BASE}/pnl/{wallet}", headers=HEADERS)
pnl = resp.json()
print(f"Win rate: {pnl['summary']['winPercentage']}%")

Authentication & Pricing

  • API Key: From your SolanaTracker dashboard, passed as x-api-key header
  • Plans: Starting ~€50/mo (200K requests), €200/mo (higher volume), Enterprise custom
  • Raptor: Free during public beta (self-hosted, no rate limits)

Core Data Endpoints

Token Data

python
# Full token info (metadata, pools, risk, events, holders summary)
GET /tokens/{tokenAddress}

# New tokens (paginated, pages 1-10)
GET /tokens/latest?page=1

# Trending by volume (default: past hour)
GET /tokens/trending
GET /tokens/trending/{timeframe}  # 5m, 15m, 30m, 1h, 4h, 12h, 24h

# Top performers
GET /tokens/top

# Graduated from bonding curves (pump.fun → Raydium)
GET /tokens/graduated
GET /tokens/graduating

# Multiple tokens in one request
GET /tokens/multi?tokens=ADDR1,ADDR2

# Deployer's tokens
GET /tokens/deployer/{deployerAddress}

# Token by pool address
GET /tokens/pool/{poolAddress}

# All-time high
GET /tokens/{token}/ath

Price Data

python
# Current price with liquidity and market cap
GET /price?token={address}

# Price with change percentages
GET /price?token={address}&priceChanges=true

# Historic prices (3d, 5d, 7d, 14d, 30d snapshots)
GET /price/history?token={address}

# Multiple token prices
GET /price/multi?tokens=ADDR1,ADDR2

OHLCV Charts (1-second resolution)

python
# Candle data — supports 1s resolution (unique to SolanaTracker)
GET /chart/{token}?type=1s&time_from=UNIX&time_to=UNIX

# Timeframes: 1s, 5s, 15s, 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1mn
# Optional: currency=usd|sol|eur, removeOutliers=true, marketCap=true

# Specialized charts
GET /chart/{token}/bundlers   # Bundler activity overlay
GET /chart/{token}/holders    # Holder count overlay
GET /chart/{token}/insiders   # Insider activity overlay
GET /chart/{token}/snipers    # Sniper activity overlay

Wallet PnL

python
# Full wallet PnL across all tokens
GET /pnl/{wallet}

# Token-specific PnL
GET /pnl/{wallet}/{token}

# First buyers with PnL
GET /first-buyers/{token}

# Optional params: showHistoricPnL=true (1d/7d/30d), holdingCheck=true

PnL response summary fields: realized, unrealized, total, totalInvested, averageBuyAmount, totalWins, totalLosses, winPercentage, lossPercentage

Wallet Data

python
# All tokens held by wallet
GET /wallet/{owner}

# Paginated wallet tokens
GET /wallet/{owner}/paginated

# Trade history
GET /wallet/{owner}/trades

# Portfolio chart over time
GET /wallet/{owner}/chart

Holder Analysis

python
# Paginated holder list
GET /tokens/{token}/holders?page=1

# Top 100 holders
GET /tokens/{token}/holders/top

# Top 20 holders (lighter)
GET /tokens/{token}/holders/top20

# Bundler detection
GET /tokens/{token}/bundlers

Top Traders

python
# Global top traders
GET /top-traders/all
GET /top-traders/all/paginated?page=1

# Token-specific top traders
GET /top-traders/{token}

# Optional: expandPnl=true, sortBy=total|winPercentage

Risk Assessment

Risk is included in the /tokens/{token} response:

json
{
  "risk": {
    "score": 7,        // 1-10 (10 = safest)
    "rugged": false,
    "jupiterVerified": true,
    "risks": [
      { "name": "Top 10 holders own 45%", "level": "warn" },
      { "name": "Freeze authority enabled", "level": "danger" }
    ]
  }
}

Risk factors: sniper/insider concentration, developer holdings, bundler activity, top 10 holder %, mint/freeze authority, social presence, metadata completeness, liquidity.

Search (30+ filters)

python
GET /search?query=BONK&minLiquidity=10000&minRiskScore=5&market=raydium&sortBy=volume&limit=50

# Key filters: query, symbol, minLiquidity, maxLiquidity, minMarketCap, maxMarketCap,
# minVolume, maxVolume, hasImage, hasSocials, minHolders, maxHolders, minRiskScore,
# freezeAuthority, mintAuthority, deployer, market, sortBy, sortOrder, limit (max 500), page

Raptor — Self-Hosted DEX Aggregator

See the dedicated raptor-dex skill for complete Raptor documentation including setup, API reference, deployment guides, WebSocket streaming, and execution scripts.

Raptor is SolanaTracker's self-hosted DEX aggregator: 25+ DEXes, no rate limits, no API key, Yellowstone Jet TPU submission. GitHub | Docs

DataStream WebSocket

Real-time streaming via WebSocket for 30+ event types:

python
import websockets, json

async def stream():
    uri = f"wss://datastream.solanatracker.io/{DATASTREAM_KEY}"
    async with websockets.connect(uri) as ws:
        # Subscribe to token trades
        await ws.send(json.dumps({"type": "join", "room": f"transaction:{token_addr}"}))
        # Also: price:{token}, holders:{token}, latest_tokens, graduated, etc.
        async for msg in ws:
            data = json.loads(msg)
            if data.get("type") != "joined":
                print(data)

Key channels: transaction:{token}, price:{token}, holders:{token}, latest_tokens, graduated, graduating, bundlers:{token}, insiders:{token}, snipers:{token}, wallet_transaction:{wallet}

When to Use SolanaTracker vs Alternatives

NeedUse
1-second OHLCV candlesSolanaTracker
Wallet PnL trackingSolanaTracker
Token risk scoringSolanaTracker
Bundler/sniper detectionSolanaTracker
Self-hosted swap executionRaptor
Free no-auth quick lookupDexScreener
Real-time gRPC streamingYellowstone
Parsed transaction historyHelius
Cross-chain dataDexScreener or CoinGecko

Files

References

  • references/data_api_endpoints.md — Complete Data API endpoint reference with parameters and response schemas
  • references/raptor_setup.md — Raptor quick-start reference (full docs in the raptor-dex skill)
  • references/risk_and_pnl.md — Risk scoring methodology and PnL calculation details
  • docs.solanatracker.io/llms-full.txt — Complete SolanaTracker documentation (13K+ lines, LLM-optimized) covering Data API, Swap API, Datastream WebSocket, Solana RPC, Yellowstone gRPC, SDK libraries, and all endpoint schemas. Fetch on demand rather than embedding.

Scripts

  • scripts/token_analysis.py — Fetch token data, risk score, holders, and trades
  • scripts/wallet_pnl.py — Wallet PnL analysis with win rate and trade breakdown

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Solanatracker Api AI skill do?

Solana token data, PnL, risk scores, 1-second OHLCV, wallet analytics, and self-hosted swap execution via Raptor

Why use Solanatracker Api on TypingMind?

Because you install it once and use it with any model. Solanatracker Api is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Solanatracker Api in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/agiprolabs/claude-trading-skills/tree/main/skills/solanatracker-api. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Solanatracker Api?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Solanatracker Api?

As many as you like. As long as a model supports skills, you can use Solanatracker Api with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Solanatracker Api AI skill free?

Yes. It is published on GitHub by agiprolabs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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