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AI-native risk intelligence for trading agents MCP Server

@System-R-AI

RepositoryHomepage

Basic information

Category

Finance & Commerce

Last updated

License

MIT

Transports

stdio

Author

System-R-AI

Submitted by

Ashim Nandi

About AI-native risk intelligence for trading agents MCP Server

Python SDK for the System R AI API Toolkit.

#finance#trading#risk-management#position-sizing#ai-agents#mcp

AI-native risk intelligence for trading agents MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "systemr": {
      "url": "https://agents.systemr.ai/mcp",
      "headers": {
        "X-API-Key": "sr_agent_YOUR_KEY"
      }
    }
  }
}

AI-native risk intelligence for trading agents MCP Server tools

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Overview

What is AI-native risk intelligence for trading agents?

System R AI is a decision intelligence system for trading and investing. Its public API Toolkit provides free finance compute tools for agents, Python workflows, notebooks, and backend services. The SDK is designed for structured decision-support workflows using user-supplied inputs.

How to use AI-native risk intelligence for trading agents?

Install the Python package with pip install systemr (requires Python 3.9+). Instantiate SystemRClient with an API key, then call tools like pre_trade_gate for combined position sizing and risk validation, or use client.call_tool() for generic tool calls. The same public API is accessible via MCP-compatible clients and REST endpoints.

Key features of AI-native risk intelligence for trading agents

  • Combines position sizing, risk validation, and system-health context into one response
  • Public tool catalog for risk, sizing, performance diagnostics, and scenario planning
  • Supports derivatives sizing, P&L, equity curves, compliance checks, and signal scoring
  • User-supplied data: no market data or LLM access in the public toolkit
  • Free compute for agent workflows, notebooks, and backend services
  • Available via Python SDK, MCP, and REST API

Use cases of AI-native risk intelligence for trading agents

  • Pre-trade risk gates for position sizing and stop-loss validation
  • Performance diagnostics and equity curve analysis from supplied trade data
  • Market structure analytics on user-provided tick data
  • Scenario planning and derivatives sizing for structured options workflows
  • Compliance checks and scanner evaluation for algorithmic trading strategies

Frequently asked questions

1

What does the public API Toolkit provide?

Free compute tools for user-supplied data—no premium market data, LLM access, Python execution, or trade execution. It covers risk, sizing, diagnostics, scenario planning, and more.

2

What are the runtime requirements?

Python 3.9 or higher. Install via `pip install systemr`. An API key (starting with `sr_agent_...`) is required to use the client.

3

Is this financial advice or a broker?

No. System R is software for decision support only. It is not financial advice, a broker, a signal service, or a guarantee of profits. Users remain responsible for their trading decisions.

4

Can I use this with MCP clients?

Yes. The same public API Toolkit is available through MCP-compatible clients. See https://docs.systemr.ai/mcp/overview for details.

5

Where does the data live?

All tools operate on user-supplied data. The public toolkit does not access internal data, LLM services, or premium market data. Premium features require the System R Workspace.

Comments

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