<!-- mcp-name: io.github.SnipMCP/thinchain -->

ThinChain

The catalytic converter between raw broker data and your AI trading agent.

Battle-tested. Sanitization logic extracted from a production options trading app. Handles every bad tick Tradier has thrown at us in production.

ThinChain Demo

☁️ Moving to production?

The open-source server runs locally with your own API keys. For hosted infrastructure with multi-broker failover, SLA guarantees, and webhook alerts — join the managed cloud waitlist.

The Problem

Tradier's MCP dumps 500-row JSON chains. One bad print can corrupt an agent's reasoning. ThinChain sanitizes, compresses, and circuit-breaks that data before it reaches your model.

Installation

git clone https://github.com/snipmcp/thinchain.git
cd thinchain
pip install -e ".[dev]"
cp .env.example .env

Or with Docker:

docker-compose up --build

Configuration

TRADIER_API_KEY=your_key_here
TRADIER_BASE_URL=https://api.tradier.com/v1
POLYGON_API_KEY=your_key_here
POLYGON_BASE_URL=https://api.polygon.io
DEFAULT_BROKER=tradier
CACHE_TTL_SECONDS=30
LOG_LEVEL=INFO

Usage

Three example prompts to send to Claude (or any MCP-compatible agent):

1. Use get_compressed_chain to get an iron condor setup on SPY expiring 2026-06-19
2. Check if SPY options data is trustworthy before I place my trade
3. Get me the ATM straddle strikes for AAPL expiring 2026-06-19

Run it in two terminals

# Tab 1 — start the MCP server
python -m thinchain.server

# Tab 2 — call a tool from a Python shell or your MCP client
# Tool signatures:
#   get_compressed_chain(symbol, expiration, strategy="raw",
#                        delta_range=None, broker="tradier")
#   get_sanitized_quote(symbol, broker="tradier")
#   get_circuit_status(symbol, expiration, broker="tradier")

How it works

Three layers between raw broker output and your model:

Broker API → [Sanitize] → [Compress] → [Circuit Break] → MCP Tool → AI Agent
              hygiene     strategy      anomaly gate
              rules       slicing       + cache

• Sanitize: Drops ghost quotes (0.0/0.0), inverted spreads, NaN/empty/dash values, clamps deltas to [-1, 1], normalizes positive theta on long options, flags illiquid strikes.
• Compress: Slices the chain to only the strikes relevant to your strategy (iron condor, straddle, etc.) — typically 95%+ token reduction.
• Circuit Break: Four-tier data quality (clean / noisy / degraded / circuit_breaker_active). When >65% of rows are anomalous, refuses to serve stale data and falls back to last known-good cache.

Real numbers from a live SPY iron condor (2026-06-19 expiration)

RAW TRADIER PAYLOAD          THINCHAIN OUTPUT
─────────────────────────────────────────────
Rows:        482             Rows:        25
Est tokens:  38,560          Est tokens:  2,000
Token savings:               95%
Anomalous rows removed:      217
Data quality:                noisy → still safely served

ThinChain compresses 482 rows / 38,560 tokens down to 25 rows / 2,000 tokens — and flags 217 anomalous strikes (illiquid, ghost quotes, wide spreads) that would have polluted the agent's context.

Roadmap

• Managed cloud tier (hosted, multi-tenant, webhook alerts)
• Polygon connector hardening (live SIP feed)
• Webhook alerts for circuit breaker trips

Contributing

PRs welcome. Run pytest before submitting.