NQ Advisor MCP
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@NQ Advisor MCPWhat's the current NQ market state and do you have a trade suggestion?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
NQ Advisor MCP
An MCP (Model Context Protocol) server that gives Claude Desktop and Claude Code a live, tool-shaped view of NinjaTrader 8 market data for the NQ futures contract, plus a deterministic research engine that answers one question: when a similar setup appeared before, what happened next?
Research and advisory only. Nothing in this repository places, modifies, or cancels an order.
What is here
Path | What it does |
| The MCP server (Python, FastMCP). One deterministic feature layer, one structured Claude call per bar, hard vetoes on bad data. |
| Deterministic research engine: export validation, session anchoring, candidate probes, MFE/MAE outcomes, kNN setup bank, expectancy report with an out-of-sample split. No network, no AI. |
| NinjaTrader 8 indicator that publishes bars and indicator values over a local HTTP endpoint. |
| Command-line entry points for the research engine. |
| Export schema, research workflow, NinjaTrader validation checklist, signal schema. |
| Unit tests for the feature engine and the suggestion payload logic. |
Related MCP server: TradingView MCP Jackson
How it works
NTBridge.csruns inside NinjaTrader 8 and serves the latest bars and indicator values onhttp://localhost:8765.The MCP server polls the bridge, computes trend and momentum features deterministically (
features.py), and exposes them as tools.nq_market_stateandnq_recent_barsnever call a model, so they are free and fast.nq_suggest_trademakes exactly one structured Claude call per bar (ai.py): direction, entry, stop, target, confidence, reasoning, and invalidation. The result is cached per bar, a server-side fallback model covers outages, and two hard vetoes cannot be overridden by the model: stale data past a trust threshold, and aHardNoTradecondition from the feature layer.nq_analog_statsfinds the k nearest historical setups in the research bank (analogs.py,research/neighbors.py) and reports their outcomes.nq_healthreports bridge connectivity, data freshness, and AI telemetry so a bad feed is visible before it becomes a bad suggestion.
Tools
Tool | Calls a model? | Returns |
| No | Live snapshot plus trend and momentum composites |
| No | Recent 1-minute bars with indicators |
| No | Outcomes of the nearest historical setups |
| No | Bridge, freshness, and AI telemetry diagnostics |
| Yes, once per bar | Direction, entry, stop, target, confidence, reasoning, invalidation |
Setup
python -m venv .venv
.\.venv\Scripts\pip install -r requirements.txt
copy .env.example .env # then add your ANTHROPIC_API_KEYRegister the server with Claude Desktop or Claude Code (adjust the path):
{
"mcpServers": {
"nq-advisor": {
"command": "C:\\path\\to\\nq-advisor-mcp\\.venv\\Scripts\\python.exe",
"args": ["-m", "nq_advisor_mcp"],
"cwd": "C:\\path\\to\\nq-advisor-mcp"
}
}
}Or run it directly:
.\start_advisor_mcp.ps1 # or: .\.venv\Scripts\python.exe -m nq_advisor_mcpConfiguration lives in .env (see .env.example): ANTHROPIC_API_KEY, ANTHROPIC_MODEL, ANTHROPIC_EFFORT, ANTHROPIC_MAX_TOKENS, NT_BRIDGE_URL, NT_BRIDGE_TIMEOUT_SECONDS, and optional ADVISOR_* overrides for the fallback model, chart timezone, staleness thresholds, and replay glob.
Research workflow
Export 1-minute bars from NinjaTrader in the format described in docs/EXPORT_SCHEMA.md (exports are not included in this repository), then:
.\.venv\Scripts\python.exe validate_export.py replays\*.jsonl # check data and timezone
.\.venv\Scripts\python.exe research_report.py --latest # expectancy reportdocs/RESEARCH_WORKFLOW.md walks through the pipeline. docs/NINJATRADER_VALIDATION.md lists what must be checked manually in NinjaTrader 8, especially the chart timezone assumption, before trusting any output.
Tests
.\.venv\Scripts\python.exe -m pytest -q testsSafety and scope
Advisory only. There is no order-execution code in this repository.
The model can decline or lower confidence, but it cannot override the stale-data or
HardNoTradevetoes.Nothing here is financial advice. Validate the research engine against your own exports before relying on it.
Author
Jordan Rhodes, github.com/ReSparkOS
This server cannot be deployed
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