Crypto Options Desk MCP
# Crypto Options Desk MCP
A **Model Context Protocol (MCP)** server that gives an LLM agent one typed, audited, read-only-by-default
tool surface over a quant crypto-options desk's analytics: gamma exposure, vanna, skew, vol surface,
options flow, technicals, portfolio greeks, scenario analysis, vol-selling signals, and live positions.
Point Claude (Desktop or Code) at it and ask *"give me a BTC options market memo"* — the agent calls the
tools itself and reasons over real Bybit data.
**What it actually does, end to end:** the LLM drives the whole desk. It calls the flow tools (GEX, vanna,
skew, vol surface) to read dealer positioning, the sentiment/funding/OI tools to read the crowd, the
technicals for trend, and the IV-RV / vol-selling / strategy tools to find an edge — then it cross-checks
those numbers against each other and writes a trader-grade memo: regime call, the structural shifts that
matter, defined-risk trade ideas with strikes/breakevens, an allocation, and a risk checklist. With a
read-only API key it also pulls your live book and folds current positions into the same analysis. The
math is identical to what the (private) strategy bots run — the agent just narrates and reasons over it.
See the [`examples/`](examples/) folder for real outputs: full market memos from both Claude and Codex
(`*_market_analysis_2026-06-07.md`) and the **delta updates** they produced ~11h later
(`*_market_analysis_2026-06-08.md`) — each diffs the new snapshot against the prior one (spot, IV, GEX,
funding, OI) and tells you what *changed* and why it matters, not just where the market is.
> Extracted from a private multi-strategy trading desk. This is the **analytics surface** only — no
> strategy signals, thresholds, or alpha. The server is a *thin facade*; all math lives in the bundled
> libraries (`options_lib`, `indicators_lib`, `portfolio_lib`, `bybit_api`) — the same code the (private)
> strategy bots import directly. One implementation, surfaced two ways.
---
## Contents
- [Install](#install)
- [Use with Claude](#use-with-claude) (Desktop & Code)
- [Keep the session rolling](#keep-the-session-rolling) ⭐
- [Example outputs](#example-outputs)
- [API key setup](#api-key-setup-optional) (optional)
- [The 22 tools](#the-22-tools)
- [Bonus: the research prompt](#bonus-the-research-prompt)
- [Configuration](#configuration)
- [Safety model](#safety-model)
- [Architecture](#architecture)
---
## Install
Requires Python ≥ 3.11.
```bash
# with uv (recommended)
uv venv && uv pip install -e .
# or plain pip
pip install -e .
```
This installs the `trading-mcp` console command (it speaks MCP over stdio).
Smoke-test it:
```bash
trading-mcp # starts the server (Ctrl-C to stop) — no output is normal; logs go to a file
pytest # after: pip install -e ".[dev]"
```
---
## Use with Claude
The server communicates over **stdio**, so any MCP client launches it as a subprocess.
### Claude Desktop
Edit your MCP config file:
- **macOS:** `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows:** `%APPDATA%\Claude\claude_desktop_config.json`
```jsonc
{
"mcpServers": {
"trading-mcp": {
"command": "trading-mcp"
}
}
}
```
If `trading-mcp` isn't on Claude's PATH, use the venv's absolute path instead:
```jsonc
{
"mcpServers": {
"trading-mcp": {
"command": "/abs/path/to/trading-mcp/.venv/bin/trading-mcp"
}
}
}
```
Or run it as a module (no console script needed):
```jsonc
{
"mcpServers": {
"trading-mcp": {
"command": "/abs/path/to/.venv/bin/python",
"args": ["-m", "mcp_trading"]
}
}
}
```
Restart Claude Desktop — you'll see the 🔌 tools appear. Try: *"Use trading-mcp to analyze BTC gamma
exposure and the vol surface, then summarize the regime."*
### Claude Code (CLI)
```bash
# from anywhere, register the installed command
claude mcp add trading-mcp -- trading-mcp
# or pin to a specific venv / module form
claude mcp add trading-mcp -- /abs/path/to/.venv/bin/python -m mcp_trading
# with an API key for the position tools (see below)
claude mcp add trading-mcp --env BYBIT_API_KEY=xxx --env BYBIT_API_SECRET=yyy -- trading-mcp
claude mcp list # verify it's connected
```
Then in a Claude Code session: *"call get_gex_analysis for ETH and explain the key levels."*
---
## Keep the session rolling
**The single biggest win: don't treat each query as one-shot. Keep one long-lived chat and let market data
accumulate in it over time.** A single snapshot tells the model where the market *is*; a session that has
seen several snapshots tells it where the market is *going* — and that's where the analysis gets sharp.
Why it works:
- **Deltas beat levels.** "IV is 93%" is noise; "ETH IV went +6.6 pts into an up-move while GEX short
gamma halved" is a tradable signal. The model can only compute that second sentence if the earlier
snapshot is still in context. See the `2026-06-08` example memos — they're *entirely* a diff against the
`2026-06-07` snapshot taken ~11h earlier.
- **Positions get tracked in time.** Re-run the position tools (or paste your book) into the same session
and the agent follows each leg across snapshots — PnL drift, greeks decay, whether the original thesis
still holds, when premium has bled enough to exit. It remembers what it recommended and grades it.
- **Theses carry forward.** The trade ideas, strikes, and risk levels from the first memo become the
reference frame for the next one ("the ETH put-spread thesis is *stronger* now — wider premium, less
short gamma, price lifted off support"), instead of starting cold every time.
Practical loop:
1. Start a memo: *"pull BTC + ETH flow, sentiment, technicals, IV-RV and write a market memo."*
2. Hours/days later, **in the same chat**: *"re-pull everything and give me a delta update vs the last
snapshot — what changed, and does it change the trade?"*
3. With an API key add: *"also pull my positions and track them against the thesis."*
A real multi-day position-tracking history (Claude following a book across snapshots) is published here:
**→ https://claude.ai/share/cdb4169c-2656-42b9-99e1-6b6b23469ace**
---
## Example outputs
The [`examples/`](examples/) folder holds real, unedited memos generated through this server:
| File | What it is |
|------|------------|
| [`claude_market_analysis_2026-06-07.md`](examples/claude_market_analysis_2026-06-07.md) | Full BTC/ETH options memo — snapshot, IV-RV edge, GEX structure, ranked trade ideas |
| [`codex_market_analysis_2026-06-07.md`](examples/codex_market_analysis_2026-06-07.md) | Same day via Codex — straddle/strangle picks with strikes, breakevens, allocation |
| [`claude_market_analysis_2026-06-08.md`](examples/claude_market_analysis_2026-06-08.md) | **Delta update** ~11h later — a `Then → Now → Δ` table and what the shifts mean for the thesis |
| [`codex_market_analysis_2026-06-08.md`](examples/codex_market_analysis_2026-06-08.md) | Codex delta update — re-ranked trades, updated allocation, risk controls |
The `06-08` files only exist *because* the `06-07` snapshot was still in the session — that's the rolling
workflow above, captured on disk.
---
## API key setup (optional)
**Most tools need no credentials** — GEX, vanna, skew, flow, vol surface, indicators, klines, funding,
OI, options chain, IV-RV, and all strategy-analysis tools use Bybit **public** market data.
Only the **two user-position tools** (`get_user_options_positions`, `get_user_all_positions`) require a
Bybit API key. A **read-only** key is enough and recommended.
Provide the key by env var (`BYBIT_API_KEY`, `BYBIT_API_SECRET`) any of these ways:
```bash
# 1) .env file (copy the template, fill in)
cp .env.example .env
# 2) inline in the Claude Desktop config
# "trading-mcp": { "command": "trading-mcp",
# "env": { "BYBIT_API_KEY": "xxx", "BYBIT_API_SECRET": "yyy" } }
# 3) Claude Code flags
claude mcp add trading-mcp --env BYBIT_API_KEY=xxx --env BYBIT_API_SECRET=yyy -- trading-mcp
```
Without a key the position tools return a structured error; everything else works.
---
## The 22 tools
Every tool returns a uniform envelope — `{ "success": bool, "data": …, "timestamp": … }` (or a
tool-specific structured object). Defaults shown in `()`.
### Options flow (5)
| Tool | Params | Returns |
|------|--------|---------|
| `get_gex_analysis` | `base_coin`(BTC), `min_oi`(1.0) | Gamma-exposure profile: net GEX, gamma walls, flip level, dealer-positioning market impact |
| `get_vanna_analysis` | `base_coin`(BTC), `price_move`(0.05) | Vanna exposure and the implied-vol impact of a given % price move |
| `get_flow_analysis` | `base_coin`(BTC) | Options flow: volume, put/call ratios, unusual-activity flags |
| `get_skew_analysis` | `base_coin`(BTC) | Volatility skew + term structure across strikes and expiries |
| `get_vol_surface_metrics` | `base_coin`(BTC) | Surface diagnostics: 25Δ risk-reversal, 10Δ skew, vol-of-vol, variance-risk premium |
### Technical analysis (1)
| Tool | Params | Returns |
|------|--------|---------|
| `get_technical_indicators` | `symbol`, `interval`(1h), `hours_back`(720) | EMA stack, RSI, MACD, ATR, Bollinger, ADX, Hurst exponent, Z-score |
### Market data (2)
| Tool | Params | Returns |
|------|--------|---------|
| `get_historical_data` | `symbol`, `interval`(1h), `hours_back`(720) | Kline count, latest price, last 10 OHLCV candles |
| `get_options_chain` | `base_coin`(BTC), `min_oi`(1.0) | Live options chain, OI-filtered, with a sample slice |
### Sentiment & positioning (3)
| Tool | Params | Returns |
|------|--------|---------|
| `get_market_sentiment_analysis` | `symbol`(BTCUSDT) | Long/short ratios, positioning bias, sentiment extremes |
| `get_open_interest_analysis` | `symbol`(BTCUSDT) | Open-interest level + trend |
| `get_funding_rate_analysis` | `symbol`(BTCUSDT) | Funding rate, carry cost, funding extremes |
### Portfolio (2)
| Tool | Params | Returns |
|------|--------|---------|
| `analyze_portfolio_greeks` | `portfolio_data` | Aggregate Δ/Γ/Θ/Vega + risk metrics for a set of option positions |
| `run_scenario_analysis` | `portfolio_data`, `scenarios` | Portfolio PnL across supplied price/vol scenarios |
### Vol selling (2)
| Tool | Params | Returns |
|------|--------|---------|
| `get_iv_rv_spread` | `base_coin`(BTC), `rv_window`(30) | ATM implied vol vs Garman-Klass realized vol spread — the vol-selling edge metric |
| `get_covered_call_signal` | `base_coin`(BTC), `target_delta`(0.10), `iv_rv_threshold`(10.0), `max_dte`(14) | Covered-call go/no-go: IV-RV check, vol regime, term structure, skew, recommended OTM strike |
### Strategy analysis (4)
| Tool | Params | Returns |
|------|--------|---------|
| `analyze_straddles` | `base_coin`(BTC), `min_oi`(10.0) | Straddle candidates ranked by profitability |
| `analyze_strangles` | `base_coin`(BTC), `min_oi`(10.0) | Strangle optimization |
| `analyze_spreads` | `base_coin`(BTC), `min_oi`(10.0), `spread_types`([call_spread,put_spread]) | Vertical call/put spread analysis |
| `analyze_portfolio_strategies` | `portfolio_positions` | Classifies existing multi-leg strategies in a portfolio (legs, confidence, net cost, breakevens) |
### User positions (2) — *API-key gated*
| Tool | Params | Returns |
|------|--------|---------|
| `get_user_options_positions` | `base_coin`(BTC, or `all`), `position_type`(option) | Live option positions + total unrealised PnL |
| `get_user_all_positions` | `base_coin`(BTC), `position_type`(option/linear/inverse/all) | All positions, per-category breakdown + summary |
### Meta (1)
| Tool | Params | Returns |
|------|--------|---------|
| `get_server_info` | — | Server name, version, tool count, categories |
---
## Bonus: the research prompt
The server also ships one MCP **prompt**, `quant_research_prompt(asset)`, that primes Claude with a
senior-quant options-research workflow — it tells the model which tools to call and how to structure a
market memo (snapshot → sentiment/flow → microstructure → strategy proposals → risk checklist). In Claude
Desktop it appears in the prompt picker; just pass an asset like `BTC`.
---
## Configuration
| Env var | Default | Purpose |
|---------|---------|---------|
| `BYBIT_API_KEY` / `BYBIT_API_SECRET` | — | Only for the two user-position tools (read-only key recommended) |
| `MCP_LOG_FILE` | `/tmp/mcp-trading.log` | Where the server logs (never stdout — stdio is the JSON-RPC channel) |
| `DEBUG_MCP` | unset | Set to `1` for DEBUG-level logs |
---
## Safety model
- **Uniform envelope** — every tool returns structured `{success, data, timestamp}`; failures are never free text.
- **Read-first** — the analytics surface has no side effects; nothing places or modifies orders.
- **Key-gated** — only the position tools touch authenticated endpoints; an unconfigured agent physically can't read your book, let alone move money. Use a **read-only** key.
- **Logs off the wire** — MCP uses stdio for JSON-RPC, so all logging is file-only by design.
---
## Architecture
```
mcp_trading/ thin MCP facade — server.py = 22 @mcp.tool wrappers + 1 prompt
├─ orchestrator.py routes tool calls to the libs; holds the Bybit client + vol analyzer
├─ options_lib/ GEX · vanna · skew · flow · vol surface · strategy classification · pricing
├─ indicators_lib/ technicals + sentiment
├─ portfolio_lib/ portfolio engine · greeks · scenario analysis
└─ bybit_api/ exchange client (klines, options chain, funding, OI, positions)
```
The facade holds **no business logic** — it validates inputs (Pydantic models) and delegates. That's why
the agent and the bots compute identical numbers from identical code.
## License
MIT — see [LICENSE](LICENSE).
TDQS
Scored across 22 tools
Most tools have clearly distinct purposes, with slight overlap between vol-related tools like get_iv_rv_spread and get_vol_surface_metrics. However, descriptions are sufficiently detailed to differentiate them, and each tool targets a specific analytical need.
All tool names follow a consistent verb_noun pattern using snake_case. The verbs are uniformly distribute among 'analyze', 'get', and 'run', and nouns clearly describe the resource or action. There is no mixing of conventions.
With 22 tools, the server is slightly above the typical ideal range but still well-scoped for a comprehensive crypto options desk. Each tool serves a distinct purpose, and the count reflects the complexity of the domain without being excessive.
The tool set covers a wide range of analytics including Greeks, strategies, volatility, sentiment, and user positions. However, it lacks execution tools (e.g., place order, modify position), which is a notable gap for a trading desk. Scenario analysis partly compensates but does not replace trading actions.