smartoption-mcp 0.8.1

MCP server exposing the smartoption-ai customer + admin APIs (copy-trading, agent ops, signal history, data center, quant strategy R&D, admin self-deploy platform, cloud-broker onboarding + manual trade) as tools for AI agents (Claude Desktop / Claude Code / any MCP client). Bundles the develop-quant-strategy Claude Code skill for one-command install.

smartoption-mcp

MCP server exposing smartoption-ai customer APIs as tools for AI agents (Claude Desktop, Claude Code, any MCP client). 54 tools spanning copy-trading rules, agent ops, broker config, signal history, virtual ledger, quant strategy products, quant strategy R&D, the data center (dark-pool / option flow / trader feeds), cloud-broker MCP onboarding (Tiger / Futu / Moomoo / IB / smartoption_virtual), and cloud-broker manual trade (list/detail/submit_order/cancel_order). Also ships the develop-quant-strategy Claude Code skill as wheel data — one command (smartoption-mcp install-skill) drops it into ~/.claude/skills/.

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_BASE — https://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 44 smartoption tools should appear.

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

Install the develop-quant-strategy Claude Code skill

The wheel ships the develop-quant-strategy skill (SKILL.md + reference docs + strategy templates) so Claude Code can drive end-to-end quant strategy development from chat (validate → save draft → backtest → deploy). Install it with one command:

smartoption-mcp install-skill
# Installed develop-quant-strategy skill:
#   target:     /Users/<you>/.claude/skills/develop-quant-strategy
#   files:      9
#   ...
# Restart Claude Code; the skill should appear as /develop-quant-strategy.

Custom target dir (e.g. for Claude Code in a non-standard config):

smartoption-mcp install-skill --target-dir /path/to/my/skills

Or run from inside a Claude conversation via the install_strategy_dev_skill MCP tool. Either way, restart Claude Code after install so the new skill is picked up; then trigger it by typing /develop-quant-strategy. Re-running the install is the upgrade path — it overwrites the previously installed copy.

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

Admin self-deploy platform

Lets admins (super_admin / admin role) push a local Python project as a persistent K8s Deployment in the isolated admin-deployments namespace. Paired with the smartoption-deploy Claude Code skill (see .claude/skills/smartoption-deploy/), the admin can say "deploy this folder as my-cron" and the skill tars + base64-encodes + calls deploy_admin_project for them.

Tool	Endpoint	Purpose
list_admin_deployments	GET /admin/admin-deployments	List deployments visible to caller (super_admin sees all)
deploy_admin_project	POST /admin/admin-deployments	Upload tar.gz bundle + apply K8s Deployment + Secret
get_admin_deployment	GET /admin/admin-deployments/<name>	Metadata + live pod-status snapshot
get_admin_deployment_logs	GET /admin/admin-deployments/<name>/logs	Tail bundle-fetch + runner container logs
restart_admin_deployment	POST /admin/admin-deployments/<name>/restart	kubectl rollout restart equivalent — gated
delete_admin_deployment	DELETE /admin/admin-deployments/<name>	Tear down Deployment + Secret — gated

The pod runs as a zero-permission admin-runner ServiceAccount; no platform credentials (Mongo / Redis / broker / OpenRouter) are injected. NetworkPolicy permits egress only.

Local maintenance

Tool	Purpose
install_strategy_dev_skill	Copy bundled develop-quant-strategy skill into ~/.claude/skills/ (or target_dir). No network call. Re-run = overwrite = upgrade.

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.
• restart_admin_deployment, delete_admin_deployment — same dry-run pattern. Restart preview includes current bundle_version + status; delete preview warns that the latest bundle in COS will be removed.
• 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

status ∈ done / 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.