Which integrations are available for this server?

Provides containerized deployment and management of the FIX protocol simulation platform, enabling isolated execution of trading infrastructure components through Docker Compose. Enables source code retrieval and version control integration for the FIX-MCP server through Git cloning operations from the project repository. Provides iconography and visual elements for the Mission Control interface, enhancing user experience with consistent visual cues across trading operations panels. Powers the Mission Control dashboard frontend with React-based UI components for real-time trading operations visualization, scenario management, and interactive terminal interfaces. Facilitates frontend dependency management and development workflow for the Next.js-based Mission Control interface through package installation and script execution. Provides persistent order storage and data management for the FIX trading simulation platform, serving as the primary database for order management system operations. Enables backend FIX protocol engine implementation with MCP SDK integration, supporting real-time trading diagnostics, session management, and algorithmic order processing. Forms the foundation of the Mission Control user interface components, enabling interactive visualization of trading topology, telemetry data, and scenario runbooks. Provides pub/sub messaging infrastructure for real-time event propagation and communication between FIX engine components and the Mission Control dashboard. Enables responsive styling and UI component design for the Mission Control trading operations dashboard through utility-first CSS framework integration.

How do I use FIX MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@FIX MCP Server check all FIX sessions for sequence gaps or latency issues" 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.

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FIX MCP Server

by henryurlo

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

FIX-MCP

FIX protocol simulation platform for capital markets operations. AI-powered SRE copilot with real-time diagnostics, incident runbooks, and MCP tool integration for trading infrastructure management.

Quick Start

git clone https://github.com/henryurlo/fix-mcp-server.git
cd fix-mcp-server
docker compose up -d

Open http://localhost:3000.

Login: henry / henry (admin) · admin / admin · or click Demo Mode.

Service	URL	What it serves
Mission Control	http://localhost:3000	Sleek trading ops dashboard with scenario lifecycle
REST API	http://localhost:8000	MCP tool dispatch, system status
MCP stdio	docker compose run	For AI agents via MCP protocol

No Node or Python on your host — everything runs in containers.

Mission Control

Three tabs:

Tab	Purpose
Mission Control	Live topology, FIX heartbeat panel, scenario picker + interactive terminal
Telemetry	Real-time metrics — sparklines, order book, FX rates
Scenario Library	Browse all scenarios by severity/difficulty, inspect runbooks, success criteria

Core Layout

┌──────────────────┬─────────────────────────────────────┐
│ Topology Graph   │ FIX Terminal                        │
│ (ecosystem)      │ fix-cli> show sessions              │
│                  │ fix-cli> query orders               │
├──────────────────┼─────────────────────────────────────┤
│ Runbook Panel    │ MCP Audit Log                       │
│ (live steps)     │ [+ SRE Copilot slides in →]         │
└──────────────────┴─────────────────────────────────────┘

Scenarios

13 training scenarios covering a full trading day (02:00–16:32 ET). Each includes:

Runbook — 4-6 diagnostic/fix steps with exact MCP tool calls
Success criteria — explicit conditions that define "resolved"
Hints — key problems, flag meanings, common mistakes
Severity & difficulty — from beginner to advanced

Scenario	Severity	Time	Est
`morning_triage`	Critical	06:15	25m
`bats_startup_0200`	Medium	02:05	15m
`predawn_adrs_0430`	Medium	04:35	15m
`preopen_auction_0900`	High	09:02	20m
`open_volatility_0930`	High	09:35	20m
`venue_degradation_1030`	Critical	10:32	30m
`twap_slippage_1000`	High	10:05	20m
`ssr_and_split_1130`	Critical	11:34	35m
`vwap_vol_spike_1130`	Critical	11:35	25m
`iex_recovery_1400`	Medium	14:03	15m
`is_dark_failure_1415`	High	14:15	25m
`eod_moc_1530`	High	15:31	20m
`afterhours_dark_1630`	Medium	16:32	15m

MCP Tools (22)

Category	Tools
Diagnostic	`run_premarket_check`, `check_fix_sessions`, `check_ticker`, `query_orders`, `validate_orders`, `dump_session_state`
Session Recovery	`fix_session_issue`, `session_heartbeat`, `reset_sequence`
Order Actions	`send_order`, `cancel_replace`, `release_stuck_orders`
Algo Suite	`send_algo_order`, `check_algo_status`, `modify_algo`, `cancel_algo`
Reference/Venue	`update_ticker`, `load_ticker`, `update_venue_status`, `list_scenarios`

AI Copilot

The SRE Copilot is FIX-aware with:

Full decision trees for session diagnostics, order triage, and algo management
Scenario-specific context injection (situation, key problems, flag meanings, common mistakes, success criteria)
Tool call approval gates for irreversible operations
Concise, actionable output — quantitative impact with FIX message types

Architecture

┌──────────────────────────────────────────────┐
│              Mission Control (Next.js)       │
│          http://localhost:3000               │
└──────────────────────┬───────────────────────┘
                       │ REST proxy
┌──────────────────────▼───────────────────────┐
│              REST API                        │
│         http://localhost:8000                │
│  /api/status /api/orders /api/                │
│  /api/scenarios /api/scenario/{name}         │
│  /api/tool (POST) /api/reset (POST)          │
└──────────────────────┬───────────────────────┘
                       │
┌──────────────────────▼───────────────────────┐
│        FIX Engine (Python)                   │
│  OMS · FIXSessionManager                     │
│  ReferenceDataStore · AlgoEngine             │
└──────────────────────┬───────────────────────┘
                       │
┌──────────────────────▼───────────────────────┐
│  PostgreSQL (orders) · Redis (pub/sub)       │
└──────────────────────────────────────────────┘

Tech Stack

Backend: Python 3.11, MCP SDK, asyncio, stdlib http.server
Frontend: Next.js 16, React 19, React Flow, Zustand 5, Tailwind CSS v4, lucide icons
Infra: PostgreSQL 16, Redis 7, Docker Compose
Protocol: FIX 4.2 / 4.4 simulation
AI: OpenRouter API (any compatible model; default qwen/qwen3.6-plus)

MCP Integration (external clients)

{
  "mcpServers": {
    "fix-mcp": {
      "command": "npx",
      "args": ["-y", "@anthropic-ai/mcp-remote@latest"],
      "env": { "MCP_URL": "http://localhost:8000/mcp" }
    }
  }
}

Development

# Backend (Python)
pip install -e .
python -m fix_mcp.api           # REST on :8000

# Frontend (Node)
npm install
npm run dev                     # Next.js on :3000

The Next.js route handler reads BACKEND_URL — defaults to http://127.0.0.1:8000 for local dev.

Built by Henry Urlo.

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