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MCP server exposing the smartoption-ai customer APIs (copy-trading, agent ops, signal history, data center, quant strategy R&D) as tools for AI agents (Claude Desktop / Claude Code / any MCP client).

Project description

smartoption-mcp

MCP server exposing smartoption-ai customer APIs as tools for AI agents (Claude Desktop, Claude Code, any MCP client). 37 tools spanning copy-trading rules, agent ops, broker config, signal history, virtual ledger, quant strategy products, quant strategy R&D, and the data center (dark-pool / option flow / trader feeds).

Architecture

Claude / Agent
   │  MCP stdio
   ▼
smartoption-mcp  ──HTTP + Bearer JWT──▶  backend  /api/customer/*

Thin wrapper: each tool maps to one customer API endpoint, authenticated with a per-user JWT (or long-lived API token) loaded from env at startup.

Install

pip install smartoption-mcp
# or, in an isolated venv:
python3.11 -m venv ~/.smartoption-mcp && ~/.smartoption-mcp/bin/pip install smartoption-mcp

Published on PyPI. Installs the smartoption-mcp CLI. Upgrade with pip install -U smartoption-mcp.

Local dev from this repo:

cd mcp-server
python3.11 -m venv .venv && source .venv/bin/activate
pip install -e .

Configure auth

Log into portal.smartoption.ai → 个人中心 → "API Token(用于 MCP / 脚本)" → 起个名字 → 复制 token. 1-year expiry, revocable any time from the same page.

Set:

  • SMARTOPTION_JWT — the token (no Bearer prefix)
  • SMARTOPTION_API_BASEhttps://api.smartoption.ai

Smoke test:

export SMARTOPTION_API_BASE="https://api.smartoption.ai"
export SMARTOPTION_JWT="eyJ..."
.venv/bin/python -c "from smartoption_mcp.client import SmartoptionClient; \
  print(SmartoptionClient().list_agents())"

Register with Claude Code / Claude Desktop

Claude Code — edit ~/.claude.json, add under mcpServers:

{
  "mcpServers": {
    "smartoption": {
      "command": "smartoption-mcp",
      "env": {
        "SMARTOPTION_API_BASE": "https://api.smartoption.ai",
        "SMARTOPTION_JWT": "eyJ..."
      }
    }
  }
}

Restart Claude Code. All 37 smartoption tools should appear.

Claude Desktop — same JSON shape at ~/Library/Application Support/Claude/claude_desktop_config.json. Restart the app after editing.

Once registered, you can ask things like:

  • "查一下最近一周苹果相关的喊单"
  • "我现在的虚拟仓有哪些标的?"
  • "我的跟单 agent 在线吗?最近一次心跳是什么时候?"
  • "今天 agent 跑了几条信号,有没有被跳过的?"
  • "帮我写一个 MA crossover 策略,先 validate 一遍"
  • "解读一下今天 NVDA 的暗盘大单"

Tools

Copy-trading rules

Tool Endpoint Purpose
list_copy_rules GET /copy-rules Current copy-trading rules + toggles
update_copy_rules PUT /copy-rules Replace full settings; confirmed-gated with structured diff

Agent provisioning & ops

Tool Endpoint Purpose
ensure_agent POST /agents/ensure Create / provision the user's agent pod (idempotent; force_redeploy gated)
get_agent_status GET /agents Online / heartbeat / broker snapshot summary
get_agent_logs GET /agents/<id>/logs Tail recent agent-pod stdout
restart_agent_client POST /agents/<id>/restart-client Restart in-pod agent process — gated
stop_agent POST /agents/<id>/stop Scale agent deployment to 0 — gated

Broker configuration

Tool Endpoint Purpose
list_broker_configurations GET /broker-configurations All saved brokers + active flag (no creds returned)
get_active_broker GET /broker-configurations Just the active broker name + display name
set_active_broker PUT /active-broker Switch active broker — gated
test_broker_connection POST /broker-configurations/test-{ib,tiger,futu,moomoo} Verify creds against broker; does NOT save
refresh_broker_snapshot POST /broker-account-snapshot/refresh Ask agent to push fresh broker snapshot

Signal history & run logs

Tool Endpoint Purpose
query_signal_history GET /signal-history Search parsed alerts (大单 / 喊单)
get_signal_detail GET /signal-history/<id> Full SignalForwardRecord for one signal
get_signal_chain GET /signal-history/<id>/chain-slots Paired / chained signal context (ROLL_UP pairs etc.)
list_run_logs GET /copy-run-logs Per-signal execution outcomes

Virtual ledger & followers

Tool Endpoint Purpose
list_virtual_lots GET /virtual-ledger Open virtual lots + qty_by_key
list_virtual_followers GET /virtual-followers User's virtual-follower accounts + equity summary

Quant strategy products (copy-trade catalog)

Tool Endpoint Purpose
list_quant_strategies GET /quant-strategies/list Available / subscribed quant strategies
get_quant_strategy_snapshot GET /quant-strategies/<id>/snapshot One strategy's positions + canonical valuation

Quant strategy R&D

Tool Endpoint Purpose
validate_strategy_code POST /strategy-ai/strategies/validate RestrictedPython compile + protocol check (mirrors deploy gate)
create_strategy POST /strategy-ai/strategies New draft + dedicated VirtualAccount
list_strategies GET /strategy-ai/strategies User's strategies + per-strategy account summary
get_strategy GET /strategy-ai/strategies/<id> One strategy's full doc (draft_code, deployed_code, state)
save_strategy_draft POST /strategy-ai/strategies/<id>/save-draft Persist editor source; does NOT disturb running runner
run_strategy_backtest POST /strategy-ai/strategies/<id>/backtest Submit backtest (queued, returns run_id)
get_backtest_run GET /strategy-ai/strategies/<id>/backtest-runs/<run_id> Summary mode (KPI + equity + capped trades + last 5 days' decisions); mode='full' or decisions_for_day=YYYY-MM-DD for deeper dives
cancel_backtest_run POST /strategy-ai/strategies/<id>/backtest-runs/<run_id>/cancel Cooperative cancel
deploy_strategy POST /strategy-ai/strategies/<id>/deploy Promote draft → deployed + lift K8s runner pod — gated
stop_strategy POST /strategy-ai/strategies/<id>/stop Scale runner to 0 — gated

Paired with the develop-quant-strategy skill (in .claude/skills/), this lets Claude take a strategy from "natural-language intent" to "deployed runner" entirely from chat: validate → create → save_draft → run_backtest → poll get_backtest_run → deploy (with dry-run + operator approval) → observe via list_quant_strategies + get_quant_strategy_snapshot. get_backtest_run defaults to a summary mode (≤100KB) tuned for LLM context; raw replay payloads can be multi-MB.

Data Center (暗盘大单 / 期权大单 / 交易员)

Tool Endpoint Purpose
list_data_center_tags GET /data-center/overview Available tags + counts
list_data_center_channels GET /data-center/overview Active channels under one tag
list_data_center_messages GET /data-center/messages Paged messages with filters
get_data_center_message_detail GET /data-center/messages/<id> One message by id
interpret_data_center_message POST /data-center/messages/<id>/interpret (SSE) LLM "解读"; stream collected server-side
chat_about_data_center_message POST /data-center/messages/<id>/chat (SSE) Per-message free-form chat
list_data_center_message_chat_history GET /data-center/messages/<id>/chat Prior chat turns + quota

Confirmation model

Destructive writes accept a confirmed: bool argument, defaulting to False (dry-run):

  • update_copy_rules(new_settings, confirmed=False) → returns a structured diff (toggle changes + rules added / removed / modified by rule_id). Nothing is written. Show the diff, then re-call with confirmed=True.
  • ensure_agent(force_redeploy=True, confirmed=False) → returns a description of the redeploy. Default force_redeploy=False is idempotent and skips the gate.
  • set_active_broker, restart_agent_client, stop_agent — same dry-run pattern.
  • deploy_strategy, stop_strategy — same dry-run pattern. Deploy also surfaces the current vs target runtime_symbols and deployment_state for the operator preview.
  • refresh_broker_snapshot, cancel_backtest_run — no gate (non-destructive / reversible).

The host (Claude Code / Desktop) also shows tool arguments before each call, so confirmed=True is always visible in the approval UI — the in-tool flag is belt + suspenders.

Full-doc replacement. update_copy_rules rejects partial settings: the proposed doc must contain auto_buy_enabled, auto_sell_enabled, use_all_matched_rules, and rules. Start from list_copy_rules, mutate locally, pass the full doc back — preserving every rule's rule_id so the diff stays stable.

SSE tools

interpret_data_center_message and chat_about_data_center_message hit a backend SSE endpoint but collect the full stream and return one payload:

{status, content, duration_ms, event_count}     # interpret
{status, content, duration_ms, event_count,
 remaining_quota}                                # chat

statusdone / cached / error / quota_exceeded. Time inputs (start_at / end_at) are pass-through ISO 8601 — include timezone offset (e.g. -04:00 for ET); the server does not normalize "today" / "now-7d".

Roadmap

  • Remote MCP server (OAuth 2.1) — deferred until a multi-user use case justifies the operational cost. Until then, each user runs smartoption-mcp locally with their own API token.

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