Let an AI agent manage your MetaTrader 5 account over Model Context Protocol - with configurable human approval gate.

A Hermes agent placing then closing a real 0.01-lot trade on a demo account, end-to-end over MCP on Linux.

Not a mock-up - the same round-trip in MetaTrader 5's own History tab; the tickets and balance match the recording.
β οΈ This software places real trades through your MetaTrader 5 terminal with real orders and irreversible fills. Read DISCLAIMER.md and SECURITY.md before connecting it to a live account. Always test using your demo account first.
Runs locally - in the same process tree as your agent, no cloud, no telemetry. Windows (native) or Linux (via Docker); Python 3.10+.
π The story behind this: this project is built step by step in Wiring AI agent into MetaTrader 5, Part 1 of the Trade with AI agent series on the Fintrix engineering blog.
mt5-mcp lets an AI agent read your MetaTrader 5 account and place trades
through it, over the Model Context Protocol.
- 12 read-only tools: account, quotes, positions, orders, history, OHLC bars, broker-authoritative margin estimates, and native chart screenshots (Windows). No consent gate.
- 4 mutating tools:
place_order,modify_order,cancel_order,close_position, each behind a preflight + human-consent + idempotency + audit layer. - 3 subscribable resources: live
account://,positions://, andquotes://{symbol}snapshots that push change notifications. - 2 ready-to-use Claude Code skills ship in
.claude/skills/:mt5-market-dataandmt5-tradingteach an agent how to read the account and run the consent flow safely.
Full catalogue and the consent flow: docs/tools.md.
- A safety layer, not just an API wrapper. Every mutating call routes through preflight checks -> an opt-in human-consent gate (arm it to require approval) -> idempotency -> an append-only audit log, so you can put a human in the loop on trades and always keep a replayable record of what the agent did.
- An honest threat model. It treats an LLM wired to
place_orderas a live attack surface and says so plainly - the MCP is explicitly not the security boundary (see SECURITY.md). - Verifiable proof, not a mock-up. The demo above is a real round-trip; the tickets and balance match MetaTrader 5's own History tab.
- Local-first. No cloud, no telemetry; runs beside your agent. Windows-native
or Linux via an all-in-one Docker image (no
rpycversion-matching).
pip install mt5-trading-mcp- Launch MetaTrader 5 and log into your broker. Enable AlgoTrading (toolbar button green).
- Verify the terminal is reachable:
python -m mt5_mcp doctor: expect[INFO] backend: nativeand[PASS]lines. - Run it:
python -m mt5_mcp serve.
Wire it to OpenClaw in one command (registers the mcp.servers entry):
openclaw mcp set mt5-mcp '{"command":"python","args":["-m","mt5_mcp","serve"]}'The MT5 terminal + the MCP run headless in an all-in-one image; your agent talks MCP over HTTP. No host Python, no bridge.
cp deploy/.env.example deploy/.env # add MT5_LOGIN / MT5_PASSWORD / MT5_SERVER
docker compose -f deploy/docker-compose.yml up -dLog the terminal in once via the KasmVNC web UI at http://127.0.0.1:3001
(File -> Login to Trade Account; persists across restarts), then point your
agent at http://127.0.0.1:8765/mcp. Wire it to OpenClaw in one command:
openclaw mcp set mt5-mcp '{"url":"http://127.0.0.1:8765/mcp","transport":"streamable-http"}'Full walkthrough: docs/installation.md.
get_chart_screenshot(symbol, timeframe, annotations?) returns a PNG of the
native MT5 chart, optionally annotated, so an LLM can read it visually
(candles, support/resistance, patterns). Because the MetaTrader5 Python API
cannot capture charts, this uses a small MQL5 Expert Advisor that runs inside
a GUI terminal and calls ChartScreenShot().
See Chart annotations for marking up support/resistance lines, trendlines and notes before capture.
Setup (one time):
- Install and attach the
AgentScreenshotEA - seemql5/README.md. - Optionally set a template so your indicators/drawings appear in the shot:
[screenshot]template = "agent.tpl"in your config, or leave it unset for the default chart.
Config knobs ([screenshot] section): width (default 1600), height
(default 900), template (default none), timeout_s (default 10).
Not available on the headless Linux/Docker deployment: it needs a GUI
terminal. Off Windows the tool returns SCREENSHOT_NOT_SUPPORTED.
If you've been handed this repository to install and run, follow the runbook in docs/agents.md. It covers platform detection, install, verification, registering the server, and the hard safety rules for trades - read it before calling any mutating tool.
| Guide | What's in it |
|---|---|
| Installation & setup | Requirements, Windows + Linux/Docker setup, wiring to an agent. |
| For AI agents | Step-by-step runbook for an agent installing and running the server. |
| Configuration | config.toml schema, storage paths, hot-reload. |
| Tools & resources | Read tools, mutating tools + consent flow, subscribable resources. |
| MCP client setup | Per-client config snippets and Claude Code usage. |
| Transports & deployment | stdio/HTTP transports and Windows VPS patterns. |
| Contributing | How to contribute and run the tests. |
| Changelog | Release history and known limitations. |
mt5-mcp is not the security boundary, the broker's MT5 server enforces
the hard limits (margin, max-lot, symbol permissions). Pre-flight checks in the
policy engine are UX guardrails to catch agent mistakes early, not security
controls.
The human-consent gate is opt-in and off by default: auto_approve_notional
defaults to 0, so mutating calls auto-execute (full-open) - intended for trusted
or unattended agents. Arm the gate by setting auto_approve_notional > 0:
orders/closes whose notional is at or above it then return an ApprovalPreview
you must confirm, and modifying a stop to widen or remove it also requires
approval. The pre-flight limits (max_*) and symbol allow/deny lists are likewise
opt-in (0 / empty = off). Every mutating call is recorded in an append-only audit
JSONL log regardless. For vulnerability disclosure, see
SECURITY.md.
mt5-mcp wraps the MetaTrader 5 Python library behind a FastMCP server. A single MT5Client (src/mt5_mcp/adapter/) owns the terminal connection, broker-timezone inference, and type conversions; everything else sits on top of it. The Pydantic models in src/mt5_mcp/types.py / src/mt5_mcp/config.py are the source of truth for the data and config schemas.
Agent / MCP client (Hermes, OpenClaw, Claude Code, Claude Desktop, β¦)
β
β stdio Β· loopback HTTP
βΌ
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β FastMCP server β
β β
β tools/ resources/ policy/ β
β read + subscribable consent Β· idempotency β
β mutating account/quotes Β· audit (JSONL) β
β β
β streaming/ - change-detection poller + dispatcher β
β types.py Β· config.py - Pydantic schemas: source of β
β truth for data + config β
β β
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β β
β adapter/ MT5Client β
β one terminal connection Β· broker-TZ inference Β· β
β type conversions Β· transparent reinit β
β β
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MetaTrader 5 Python library -> broker terminal -> broker server
The module paths shown (tools/, resources/, policy/, streaming/,
adapter/, types.py, config.py) all live under src/mt5_mcp/.
Contributions are welcome, see CONTRIBUTING.md for the dev setup, test workflow, and project principles.
MIT - see LICENSE.