AlgoChains MCP Server

---

The only MCP server with live futures bots, real fill data, real-time ML inference, and 503 tools across 20 domains — all backed by real APIs, zero synthetic data.

Connect your AI assistant (Claude, Cursor, ChatGPT) to your trading infrastructure in 3 commands. Ask Claude "What's my paper P&L today?" — it reads your AlgoChains virtual paper account and tells you. No broker required.

You ask Claude:                       Claude calls:                    Server calls:
"What's my paper P&L?"        →  get_my_portfolio()        →  AlgoChains paper account → real signals
"What signals did MNQ fire?"  →  get_signal_stream()       →  copy-trade signal feed → live bot output
"Run a backtest on MNQ"       →  run_backtest()             →  Databento tick archive
"Is the market trending?"     →  detect_market_regime()    →  Polygon + FRED → analysis
"What's my live NQ position?" →  get_positions()           →  Tradovate API → real data  (live users)

---

Quick Install

# 1. Install
pip install algochains-mcp-server

# 2. Connect to your IDE (no credentials needed to start)
python scripts/quickstart.py --generate-config cursor

# 3. Verify
python scripts/quickstart.py --mode demo

That's it. Your AI now has 168 tools (smart mode) available immediately.

Recommended next step — no broker needed: Sign up at algochains.ai for a free hosted virtual paper account, set ALGOCHAINS_SUBSCRIBER_KEY=sub_live_…, and start copy-trading MNQ signals instantly. See Option B below.

For live broker connectivity (Tradovate, Alpaca, etc.), see Option C.

---

Subscriber Onramp — Try It Free (No Broker Required)

The fastest way to get value from this server is as a subscriber: sign up at algochains.ai, get a free hosted virtual paper account, and start copy-trading the live MNQ bot's signals in seconds. No Tradovate credentials. No Alpaca account. No real money.

How it works

1. Sign up at algochains.ai — free paper account provisioned automatically
2. Dashboard shows your sub_live_… subscriber key — copy it
3. Set ALGOCHAINS_SUBSCRIBER_KEY=sub_live_… in your shell or .env
4. Claude now has 9 subscriber-scoped tools available:

Tool	What it does
get_my_portfolio	Paper balance + active bot assignments + open signals + 7-day P&L in one call
get_signal_stream	Unread copy-trade signals for the bots you follow (MNQ by default)
get_my_pnl	Today's P&L and 7-day P&L from your paper fills
get_my_fills	Paginated fill history — symbol, side, qty, fill price, P&L per trade
get_my_assignments	Which bots you're subscribed to and their risk caps
get_marketplace_listings	Browse all approved bots available to subscribe to
place_paper_order	Place a self-directed paper order (filled at real quotes)
cancel_paper_order	Cancel a pending paper order
get_my_paper_positions	Open and recently filled self-directed paper orders

All 9 tools require only the sub_live_… key — no OWNER_API_TOKEN, no broker credentials.

Subscriber key format

Keys always start with sub_live_ (production) or sub_test_ (sandbox). Set the key as ALGOCHAINS_SUBSCRIBER_KEY in your .env — the server resolves your subscriber_id server-side via Supabase. Your key never touches this repo.

Subscriber quick-start prompts

Portfolio snapshot:
"Run get_my_portfolio. What's my paper balance and how did the MNQ bot do today?"

Signal stream:
"Call get_signal_stream. What signals has the MNQ bot fired in the last hour?"

Fill history:
"Run get_my_fills with limit=20. List the last 20 fills with P&L per trade."

Marketplace browse:
"Run get_marketplace_listings. Which bots are available to subscribe to?"

Paper trade:
"I want to paper-trade 1 MES long at market. Use place_paper_order."

Bot owners: See MARKETPLACE_CREATOR_GUIDE.md and check_propagation_health / test_signal_propagation for the copy-trade pipeline health tools (requires OWNER_API_TOKEN).

---

Smart Mode vs Full Mode

AlgoChains exposes tools in two tiers, controlled by ALGOCHAINS_TOOL_MODE:

Mode	Tools Exposed	Token Cost	When to Use
Smart (default)	168 curated	~4K tokens	Cursor, Windsurf (80-tool limit), everyday use
Full (ALGOCHAINS_TOOL_MODE=full)	503 tools	~40K tokens	Claude Code, full agentic sessions

Smart mode includes: all live bot tools, market data, signals, research/backtest, Onyx RAG, prop fund pipeline, position sizing, broker management, and order execution. Everything you need 95% of the time.

Full mode unlocks the remaining 330 tools: advanced DeFi, Kalshi order placement, multi-tenant SaaS, QuantConnect integration, alt-data pipelines, and more.

discover_tools — Find Any Tool Without Full Mode

Even in smart mode, you can find and use any of the 503 tools:

# Ask the server to find the right tool for your task
discover_tools("walk-forward validation with leakage check")
# → Returns: walk_forward_test, run_mcpt_validation, analyze_overfitting

# Then call it
execute_dynamic_tool("walk_forward_test", {"symbol": "MNQ", "lookback_days": 252})

This provides 99.6% token reduction vs exposing all 503 tools (arXiv:2603.20313).

---

Tool Domains

All 503 tools organized across 21 domains:

#	Domain	Smart	Full	Key Tools
1	Market Data	14	22	get_quote, get_ohlcv, get_tick_data, get_options_chain, get_footprint_chart, get_dark_pool_volume
2	Signals & Analysis	12	18	generate_signal, detect_market_regime, get_ensemble_vote, compute_gex, read_tape, pair_trade_signal
3	Research & Backtesting	10	16	run_backtest, walk_forward_test, run_mcpt_validation, validate_strategy_metrics, analyze_overfitting
4	Position Sizing	6	8	compute_r_multiple_size, compute_volatility_targeted_size, compute_idm, dual_size_conservative
5	Options Analytics	4	6	compute_option_greeks, find_optimal_strike, get_options_chain, unusual_options_activity
6	Prop Fund Pipeline	8	10	evaluate_strategy_for_prop_fund, simulate_prop_fund_evaluation, list_prop_funds, check_rithmic_status
7	Broker Management	6	15	check_all_broker_credentials, connect_broker, get_broker_onboarding_guide, store_api_key
8	Subscriber / Copy-Trade	3 stdio	16 bridge	get_subscriber_status, accept_subscriber_terms, join_bot, get_my_portfolio, get_signal_stream, place_paper_order
9	Account Protection	6	8	check_protection_status, record_stop_event, lock_instrument, check_rate_limit_status
10	Order Execution	8	12	place_order, place_bracket_order, cancel_order, smart_route_order, execute_twap
11	Emergency / Destructive	3	5	flatten_all_positions, cancel_all_orders, emergency_stop, trip_circuit_breaker
12	Intelligence (Onyx + Macro)	10	14	onyx_ask, onyx_search, get_macro_signals, get_us_economic_indicators, get_fed_policy_signals
13	Prediction Markets	8	12	get_prediction_markets, search_prediction_markets, get_kalshi_settlements, place_kalshi_order
14	Skills Bridge	5	5	list_skills, get_skill_detail, search_skills, get_skills_for_task, invoke_moltbook_debate
15	Agent Memory	6	8	get_openclaw_memory, store_trade_lesson, get_current_regime, get_openclaw_state_summary
16	Live Bot Intelligence	12	18	get_bot_health, get_live_bot_metrics, get_bot_position_state, get_ai_pipeline_health, restart_trading_bot
17	Desktop Tower / Dispatch	4	8	dispatch_tower_job, get_tower_job_status, run_tower_backtest, sync_to_tower
18	Performance Reporting	4	6	generate_bot_tearsheet, get_bot_metrics_full, run_mcpt_pipeline, capture_learning_signal
19	Billing & Subscription	12	12	get_started, get_pricing, get_checkout_url, accept_subscriber_terms, get_my_usage, create_referral_code, get_referral_earnings, create_creator_onboarding_link, get_my_creator_earnings, run_creator_payouts, get_my_realized_pnl, get_system_status
20	Platform / SaaS	8	20	join_waitlist, create_support_ticket, track_platform_event, get_analytics_summary
21	AlphaLoop / Evolution	12	22	run_alphaloop_cycle, get_alphaloop_results, get_algochains_telos, send_ntfy_notification

Subscriber tools are split by transport: local stdio exposes the consent/status funnel, while the HTTP bridge exposes the full subscriber data and paper-order surface.

---

Live Bot Showcase

AlgoChains runs 4 live futures bots on Tradovate. Their state, fills, ML pipeline health, and brackets stream through this MCP server in real time.

Bot	Symbol	Strategy	Live Since	Key MCP Tool
MNQ_Upgraded_Scalper	MNQ	7-AI ensemble, 5-min bars	Dec 2024	get_bot_health(bot="MNQ")
CL_Swing_Scalper	CL	FinBERT sentiment + momentum	Jan 2025	get_bot_health(bot="CL")
MES_EMA_Swing	MES	EMA pullback + regime detection	Feb 2025	get_bot_health(bot="MES")
NQ_EMA_Swing	NQ	Trend following + foundation model	Feb 2025	get_bot_health(bot="NQ")

get_bot_health — Full e2e Signal→Order→Fill Trace

# Returns: process state, position, bracket status, AI pipeline health,
#          ml_env_flags (MASSIVE_NEWS_FEATURES, MASSIVE_PCR_FEATURES, MASSIVE_HALT_GUARD),
#          cc_health (Command Center last-seen, WS status, Databento live feed age),
#          signal_health (params, risk_bootstrap, bot_version, trading_mode),
#          e2e_sentinel (signal→order→bracket→fill lifecycle state)
health = get_bot_health(bot="MNQ")

# All 4 bots in one call
status = get_all_bot_ops_status()
# Returns: process + position + bracket + pipeline snapshot for MNQ/CL/MES/NQ

No credentials needed if you have ALGOCHAINS_BRIDGE_API_KEY. Read-only.

---

Billing & Subscription Funnel (Fully Programmatic)

Every billing action is available as an MCP tool — no browser required after the initial Stripe checkout. An agent or a user can go from zero to copy-trading MNQ signals in one conversation thread.

New-user discovery (no auth, always available)

get_started(goal="subscriber")   # guided next-step map for new users
get_pricing()                    # transparent tiers, referral %, creator share
get_system_status()              # platform health, bot roster, live tool count

Subscribe programmatically

# 1. Get a Stripe-hosted checkout URL (one call — no browser needed after this)
get_checkout_url(email="you@example.com", tier="paper")
# → returns a checkout_url the user visits once to enter payment details
# → subscriber API key is emailed automatically after payment

# 2. Set ALGOCHAINS_SUBSCRIBER_KEY, then accept the CFTC risk disclosure
#    (required before signals; subscriber_id is resolved from the key)
accept_subscriber_terms(
    acknowledgment="I have read and understand the risk disclosure above. I accept full responsibility for my trading decisions."
)

# 3. Subscribe to MNQ copy-trade signals (published for you to review and act on)
join_bot(bot="MNQ", size_multiplier=1.0)

# 4. Check stdio status; use the HTTP bridge for portfolio/signal tools
get_subscriber_status()

Usage metering

get_my_usage()
# → calls_this_month, included_quota, overage_calls, projected_overage_usd

Referral program

create_referral_code()   # → code: "AC-X7K2NP"
get_my_referrals()       # attributed sign-ups + commission
get_referral_earnings()  # total earned, pending payout

Creator revenue (strategy publishers)

create_creator_onboarding_link(creator_id="cr_...", creator_email="you@example.com")
# → Stripe Connect Express onboarding URL (KYC, bank account)

get_my_creator_earnings(creator_id="cr_...")
# → accrued_usd, paid_usd, pending_payout_usd, next_payout_date

# Owner-gated payout run (requires OWNER_API_TOKEN)
run_creator_payouts(dry_run=True)   # preview
run_creator_payouts(dry_run=False, owner_token="tok_...")  # execute transfers

Realized P&L (live-tier subscribers)

get_my_realized_pnl()
# → realized_pnl_usd, trade_count, period, disclaimer (CFTC 4.41(b))

Tool	Auth	Tier gate
get_started	None	Public
get_pricing	None	Public
get_system_status	None	Public
get_checkout_url	None	Public (Stripe handles billing)
accept_subscriber_terms	Subscriber API key	Paper / Live
get_my_usage	Subscriber API key	Paper / Live
create_referral_code	Subscriber API key	Paper / Live
get_my_referrals	Subscriber API key	Paper / Live
get_referral_earnings	Subscriber API key	Paper / Live
get_my_realized_pnl	Subscriber API key	Live
create_creator_onboarding_link	OWNER_API_TOKEN	Owner
get_my_creator_earnings	OWNER_API_TOKEN	Owner
run_creator_payouts	OWNER_API_TOKEN	Owner

Signals are published for the subscriber to review and act on — no automated execution. Past performance is not indicative of future results. See accept_subscriber_terms for the full CFTC risk disclosure.

---

Desktop Tower Dispatch

Heavy ML workloads (hyperparameter sweeps, walk-forward validation, feature importance) run on the desktop tower (configured via ALGOCHAINS_TOWER_HOST) via dispatch_tower_job. The Mac stays clean.

# Dispatch a backtest or ML job to the GPU tower
dispatch_tower_job(
    job_type="backtest",
    params={"strategy": "mnq_scalper", "lookback_days": 252, "wfv_windows": 12}
)

# Check job status
get_tower_job_status(job_id="job_abc123")

From the CLI (ac command):

# Not yet in ac — see CLI_GAP_ANALYSIS.md for ac tower subcommand roadmap
python3 -c "
from algochains_mcp.algoclaw.desktop_tower import dispatch_tower_job
dispatch_tower_job('backtest', {'strategy': 'mnq_scalper', 'lookback_days': 90})
"

What runs where:

Component	MacBook (execution)	Desktop Tower (ML/GPU)
Live bots (MNQ/CL/MES/NQ)	✅ launchd	—
Token Guardian, Kalshi daemon	✅ launchd	—
Command Center (:3333)	✅ cloudflared tunnel	—
Onyx RAG ($ALGOCHAINS_TOWER_HOST:8085)	—	✅
GPU/ML: FinBERT, Kronos, vLLM	—	✅
Heavy backtests via dispatch_tower_job	sends job →	✅ executes

---

Security

Authentication Tiers

Scope	How to Authenticate	What's Allowed
Public / demo	No credentials	Market data, Onyx search, regime detection
Team	ALGOCHAINS_BRIDGE_API_KEY	Bot metrics, positions (read-only)
Owner	OWNER_API_TOKEN	Order execution, bot restart, emergency stop

Localhost-Only Services

The following services bind to 127.0.0.1 only and are never exposed publicly:

• MCP server HTTP bridge (port 8765 / stdio)
• Command Center dev server (port 3333) — external access via Cloudflare Access tunnel only
• Onyx RAG stack (tower port 8085) — accessible via Tailscale VPN only

Hard-Coded Safety Limits

These cannot be overridden by any AI agent:

Daily loss limit:      $500   (hard stop, all orders blocked until midnight)
Max drawdown:          15%    (circuit breaker trips at 15% peak-to-trough)
Human confirmation:    required for all orders above $10K notional
AI loop detection:     5 identical calls in 60s → 30-minute order block
VIX gate:             all trades blocked when VIX > 35

Full safety documentation: SAFETY_MODEL.md

OWNER_API_TOKEN — Mutation Gating

Tools in danger tier 2 (order execution) and tier 3 (destructive) require OWNER_API_TOKEN in the request header. The HTTP bridge verifies this before dispatching. AI agents that do not supply it get a policy_denied error — not a soft warning.

# Set in .env (never commit)
OWNER_API_TOKEN=your-owner-token-here

---

What's New in v22.x

v22.4 (2026-04-06) — UX & Team Onboarding

• Complete README rewrite (plain English, team access)
• scripts/quickstart.py — interactive setup wizard with health checks
• SAFETY_MODEL.md — answers "is this safe?" for every failure mode
• tool_danger_tiers.py — machine-readable danger classification (0–3) for the documented 503-tool surface
• HTTP bridge /tools endpoint now returns danger_tier, safe_in_demo_mode, etc.
• get_bot_health includes e2e_sentinel, desktop inference SLO, and decision latency SLO slices for signal-to-fill traceability

v22.3 (2026-04-06) — Proprietary Data Ingestion

• ingest_csv_data — validate and ingest real OHLCV CSV files into state/custom_data/
• ingest_json_signals — import pre-computed signals, ML features, labels, and regime tags
• connect_onyx_docs — index local research docs into Onyx for onyx_ask() / onyx_search()
• register_strategy and list_ingested_data — register custom strategy specs and audit imported data

v22.2 (2026-04-21) — Kalshi Pipeline + Model Integrity

• Kalshi prediction markets — AI ensemble → Kelly sizing → order execution
• Subscriber tools — JWT tier auth, get_subscriber_portfolio, get_marketplace_listings
• Unified path resolver (paths.py) — default_control_tower() works on Mac + WSL tower
• Data backend chain — Databento → Massive S3 (back to 2003) → Polygon → yfinance
• SHA-256 model integrity — startup check raises on tampered .pkl, XGBoost JSON companion, model_manifest.json
• Drawdown Triple Penance — drawdown_start_ts auto-logged on first daily loss hit (Bailey & LdP 2015)

v22.0 (2026-04-05) — MCP 2025-11-25 Full Compliance

• Elicitation (human confirmation for high-value trades)
• Durable Tasks (background backtest/optimization jobs)
• SSE streaming transport
• OIDC discovery endpoint
• Trading guardrails with circuit breakers
• AlphaLoop evolution daemon

See the full CHANGELOG.md for v21.x, v22.x, and legacy v26 audit entries.

---

Quick Setup Options (Pick Your Path)

	Path	Credential needed	Best for
A	Demo mode	None	Market data, regime detection, tools exploration
B	AlgoChains hosted paper	Subscriber API key (free signup)	Copy-trade MNQ bot, zero broker setup
B-2	Alpaca paper	Alpaca paper API key	Your own paper equity account
C	Full live	Tradovate + others	Real futures/equities trading

Option A — Demo Mode (No Credentials, 1 Minute)

pip install algochains-mcp-server
python scripts/quickstart.py --mode demo

Available immediately (no credentials):

• get_quote("AAPL") — live price for any symbol
• detect_market_regime() — trending / ranging / choppy
• get_macro_signals() — macro environment analysis
• discover_tools() — find any of the 503 tools
• onyx_ask("any question") — knowledge base search

Option B — AlgoChains Hosted Paper (Free, No Broker Needed)

No Tradovate account. No Alpaca account. No broker credentials at all.

1. Sign up at algochains.ai — free hosted virtual paper account
2. Copy your subscriber key from the dashboard
3. Set it and run:

export ALGOCHAINS_SUBSCRIBER_KEY="<SUBSCRIBER_API_KEY>"
python scripts/quickstart.py --mode paper

What unlocks immediately: local subscriber onboarding/status tools plus the hosted bridge subscriber surface for copy-trade signals from the live MNQ bot, paper P&L tracking, fill history, and self-directed paper orders filled at real quotes. See the Subscriber Onramp section above.

Option B-2 — Alpaca Paper (Your Own Broker)

export ALPACA_API_KEY=your-paper-key
export ALPACA_SECRET_KEY=your-paper-secret
export ALPACA_PAPER=true
python scripts/quickstart.py --mode paper

Option C — Full Live Setup

cp .env.example .env
# Edit .env with Tradovate, Polygon, Databento, Slack credentials
python scripts/quickstart.py --health-check --mode live

Generate IDE Config

python scripts/quickstart.py --generate-config cursor         # Cursor
python scripts/quickstart.py --generate-config claude-desktop # Claude Desktop
python scripts/quickstart.py --generate-config windsurf       # Windsurf

Which URL Do I Use?

Local installs and remote connectors use different transports:

Client	Use this	Why
Cursor, Claude Desktop, Windsurf	Generated stdio config from algochains-mcp --generate-config ...	These apps can spawn the local PyPI package on your machine.
Claude.ai web/mobile custom connector	Public HTTPS URL such as https://<your-domain>/mcp	Claude.ai calls the server from Anthropic's infrastructure, so it cannot reach your localhost, phone, LAN, or Tailscale-only URL.
Local remote-connector test	algochains-mcp-http --host 127.0.0.1 --port 8080 plus a secure HTTPS tunnel	The tunnel provides the public https://.../mcp URL that Claude.ai requires.

For a mobile Claude test, the PyPI package alone is not enough because it runs locally. Start the HTTP transport, expose it through a secure tunnel, then paste the tunnel's https://.../mcp URL into Claude.ai:

pipx install "algochains-mcp-server[http]"
export ALGOCHAINS_HTTP_TRANSPORT_SECRET="<random-token>"
algochains-mcp-http --host 127.0.0.1 --port 8080
cloudflared tunnel --url http://127.0.0.1:8080

Use the tunnel URL as the custom connector URL:

https://<cloudflared-subdomain>.trycloudflare.com/mcp

If the connector UI asks for authentication, use the value of ALGOCHAINS_HTTP_TRANSPORT_SECRET as the bearer token. For production, replace the temporary tunnel with a stable hosted endpoint such as https://mcp.algochains.ai/mcp or your own domain behind Cloudflare.

Never expose owner/live trading tools publicly without bearer auth, WAF/IP restrictions, and strict tool policy checks. See Remote Connectors for the full transport matrix and security checklist.

---

Data Backends

AlgoChains uses a priority chain — best available source wins automatically:

Priority	Backend	Coverage	Use Case
1	Databento	XNAS.ITCH + XNYS.PILLAR; OHLCV-1d + OHLCV-1m	Futures tick data, live streaming
2	Massive S3	us_stocks_sip/day_aggs_v1/ back to 2003	Historical equity backtests, survival-bias-free universe
3	Polygon	REST bars + news snapshots	News features, intraday bars
4	yfinance	Free, ~5yr history	Dev fallback, swing bots

Force a specific backend: DATA_BACKEND=databento|massive|polygon|yfinance in .env.

---

Command Center

URL	Status	Notes
https://cc.algochains.io	Live	Cloudflare Access — authenticate with your @algochains.io account
http://localhost:3333	Local dev	Always accessible without auth

Run locally:

cd algochains-command-center
npm run dev   # starts on :3333

Start Cloudflare tunnel:

cloudflared tunnel run <your-tunnel-id> >> logs/cloudflared_cc.log 2>&1 &

Dashboard panels (V22):

• Bot Status Cards — process state, uptime, last signal, AI confidence
• P&L Chart + Positions Table + Risk Dashboard
• Bracket Status Panel + AI Ensemble Health + Live Trade Validation Feed (SSE)
• Subscriber Protection Panel + System Health

---

Agentic Quick-Start Prompts

Copy these directly into Claude or Cursor:

Subscriber prompts (free, no broker needed)

Portfolio snapshot over the HTTP bridge:
"Run get_my_portfolio with my subscriber bridge key. What's my paper balance and P&L today?"

Signal stream check over the HTTP bridge:
"Call get_signal_stream for the MNQ bot with my subscriber bridge key. What signals fired in the last 2 hours?"

Weekly fill review:
"Run get_my_fills with limit=50. Break down P&L by day."

Marketplace discovery:
"Run get_marketplace_listings. What bots are available and what's each bot's asset class?"

Live bot / operator prompts

Morning brief:
"Run get_macro_signals and get_live_bot_metrics. Summarize market conditions and P&L."

Bot health check:
"Run get_bot_health for all 4 bots. Flag anything that needs attention."

Pre-trade regime check:
"Before I place any orders, run detect_market_regime and check VIX. Should I trade today?"

Validate a backtest:
"Run validate_strategy_metrics: Sharpe 2.4, MaxDD 9%, WinRate 58%, 180 trades.
 Does it pass the MCPT gate? What's the DSR?"

Prop fund compatibility:
"Use evaluate_strategy_for_prop_fund: MNQ scalper, $600 max daily loss, $2500 max DD,
 $120 avg daily profit, holds overnight. Which fund should I target?"

Emergency system check:
"Run check_all_broker_credentials and check_rithmic_status. What's ready, what's missing?"

Tower dispatch:
"Dispatch an overnight Optuna sweep for MNQ to the desktop tower. 200 trials, Sharpe objective."

---

Supported Brokers

Broker	Asset Classes	Status
Tradovate	Futures (MNQ, CL, MES, NQ, ES, GC)	✅ Live
Alpaca	Equities, ETFs, Options, Crypto	✅ Live + Paper
OANDA	Forex (50+ pairs)	✅ Live
Interactive Brokers	Stocks, Futures, Options, Forex	✅ Live (ib_async)
Kalshi	Prediction markets (US events)	✅ Live
E*TRADE	Equities, Options, ETFs	✅ OAuth 1.0a
Rithmic	Futures via prop fund platforms	⏳ DRY_RUN (vendor NDA pending)
Charles Schwab	Equities, Options, Futures	⚠️ Stubs (OAuth 2.0 PKCE)

# Check all broker credential status at once
check_all_broker_credentials()   # masked — never exposes values

---

Architecture

Your AI (Claude / Cursor / ChatGPT)
         │
         │ MCP 2025-11-25 (stdio or HTTP + SSE)
         ▼
AlgoChains MCP Server
  ├── 503 tools / 168 smart-mode (20 domains)
  ├── Trading Guardrails (hard-coded limits, AI loop detection)
  ├── Account Protection (12 pre-trade guards)
  ├── Onyx RAG (semantic search — 400+ docs + 472 skills)
  └── Circuit Breakers (per-tool rate limits, daily loss stops)
         │
         ├── Tradovate     (MNQ, CL, MES, NQ futures — live fills)
         ├── Alpaca        (equities, crypto, options)
         ├── OANDA         (forex)
         ├── Databento     (tick-level data — XNAS.ITCH)
         ├── Massive S3    (day bars back to 2003)
         ├── Polygon       (real-time bars, news)
         └── FRED, CBOE, Kalshi, Polymarket  (macro / alt data)

Data policy: No synthetic data. No mock fills. No placeholder values. Every tool connects to a real API or fails closed with an explicit error.

---

Docs

File	Purpose
SAFETY_MODEL.md	Is this safe? Failure modes, guardrails, team access
CHANGELOG.md	Full version history
docs/GOTCHAS_AND_BUGS.md	Confirmed bugs, gotchas, operational surprises
docs/DEVELOPER_TIER_ONBOARDING.md	Developer key setup, scopes, and bridge auth constraints
docs/SUBSCRIBER_TOOLS.md	Subscriber onboarding, stdio-vs-bridge tools, scopes, and copy-trade constraints
docs/NUMERAI_TOURNAMENT.md	Numerai tournament tool sequence, upload gates, and troubleshooting
docs/TRADOVATE_PARITY.md	Tradovate endpoint mapping vs community server
docs/CLI_GAP_ANALYSIS.md	ac CLI current commands + 10 missing subcommands roadmap
LATENCY_GUIDE.md	Measured tool call latencies (Mac M3 Max, real calls)
MARKETPLACE_CREATOR_GUIDE.md	Publish a validated bot; subscriber copy-trade pipeline setup
algoclaw/README.md	AlgoClaw agent skill system

---

<div align="center">

Built by Tyler Reynolds — experimental AI trading infrastructure.

Safety · Changelog · Command Center · Marketplace

Experimental software connected to live trading accounts. Use at your own risk.

</div>