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run_strategy

Execute a Python strategy code asynchronously. The code can: - Read live prices from LTP_STORE using: key = f"{scrip_code}_{exchange}" - Place orders using the async function func_place_order: - subscribe(scrip_code, exchange) → async function to subscribe to a symbol - unsubscribe(scrip_code, ex...

Risk signalsBulk/mass operation — affects multiple targets

Part of the Blinkxmcp server.

run_strategy can trigger actions in Blinkxmcp, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke run_strategy to trigger processes or run actions in Blinkxmcp. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

run_strategy can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "run_strategy": {
      "limits": [
        {
          "counter": "run_strategy_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access run_strategy gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so run_strategy only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the run_strategy tool do? +

Execute a Python strategy code asynchronously. The code can: - Read live prices from LTP_STORE using: key = f"{scrip_code}_{exchange}" - Place orders using the async function func_place_order: - subscribe(scrip_code, exchange) → async function to subscribe to a symbol - unsubscribe(scrip_code, exchange) → async function to unsubscribe from a symbol - get_token(session_id: str) -> to get token for order placement, session id always to be sent by ai agent, possible output {"status": "ok", "access_token": access_token} or return {"status": "error", "access_token": None, "message": "Session ID not found in tokens file"} Arguments for func_place_order: - api_url: string, API endpoint (default: BlinkX regular order URL) - token: string, authentication token - tradingsymbol: string, symbol of the instrument (required) - exchange: string, exchange (e.g., NSE, BSE) - transaction_type: BUY or SELL - order_type: LIMIT or MARKET - quantity: int, number of shares/contracts - product: string, product type - validity: string, DAY or IOC - price: float, price for LIMIT orders Example strategy code: key = f'-1_NSE' ltp = LTP_STORE.get(key, 0) if ltp > 26100: await func_place_order(tradingsymbol='-1', exchange='NSE', transaction_type='BUY', price=ltp, quantity=1) always unsubscribe to symbol after placing order and always ensure proper logging for every iteration to get status of execution in format session ID: "Required logs" and use default logging ie already existing 'logger'. It is categorised as a Execute tool in the Blinkxmcp MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_strategy? +

Register the Blinkx MCP server in PolicyLayer and add a rule for run_strategy: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Blinkxmcp. Nothing to install.

What risk level is run_strategy? +

run_strategy is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit run_strategy? +

Yes. Add a rate_limit block to the run_strategy rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block run_strategy completely? +

Set action: deny in the PolicyLayer policy for run_strategy. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides run_strategy? +

run_strategy is provided by the Blinkx MCP server (ai/blinkxmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Blinkxmcp tool call.

Deterministic rules across all 12 Blinkxmcp tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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