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EmidLabs
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About EmidLabs
EmidLabs provides programmable infrastructure for quantitative research and market execution, allowing users to define trading strategies using a JSON domain-specific language and execute them against real market data. The platform supports backtesting, live execution, and strategy storage through dedicated API endpoints, eliminating the need for users to build or maintain their own backtesting environments. Strategies are defined using a composable DSL that includes inputs, conditions, score weights, and decision rules, and results are returned in structured JSON format. The system operates server-side with low latency (~260ms for 5 years of BTC data) and supports concurrent workflows without queuing. Outputs include trades, win rates, expectancy in R-units, profit factors, and detailed diagnostics such as condition frequency and score distributions. The platform is designed for dev-traders, independent quants, and companies, offering multiple entry points including direct API integration, MCP client connections, or AI agent interactions.
Key features
- Backtesting API for historical strategy evaluation
- Live Execution API for real-time signal generation
- Strategy Storage for validated strategies
- MCP servers for AI agent integration
- R-unit based risk and performance metrics
- Condition diagnostics and score distribution tracking
- Configurable risk model (1% stop, 1:3 reward default)
- Cross-asset and cross-timeframe strategy support
Use cases
- Quantitative research workflow automation
- AI-assisted strategy generation and testing
- Real-time market signal subscription for execution
Pros
- JSON DSL for strategy definition
- Server-side execution with low latency (~260ms)
- Concurrent workflow support without queuing
- Structured quantitative outputs (trades, metrics, diagnostics)
- Multiple integration options (API, MCP, AI agents)
Cons
- No free tier explicitly mentioned
- Limited to server-side execution (no local processing)
- Requires JSON DSL knowledge for strategy definition
Frequently asked questions about EmidLabs
What is EmidLabs and what does it do?
EmidLabs provides programmable infrastructure for quantitative research and market execution, allowing users to define trading strategies using a JSON domain-specific language and execute them against real market data. It supports backtesting, live execution, and strategy storage through dedicated API endpoints.
Who is EmidLabs designed for?
The platform is designed for dev-traders, independent quants, and companies, offering multiple entry points including direct API integration, MCP client connections, or AI agent interactions.
How does EmidLabs handle backtesting and live execution?
Backtesting and live execution are performed server-side with low latency (~260ms for 5 years of BTC data), supporting concurrent workflows without queuing. Strategies are defined using a composable DSL and results are returned in structured JSON format.
Can I integrate EmidLabs with AI agents like Claude or ChatGPT?
Yes, EmidLabs supports native MCP servers for direct integration with AI agents such as Claude, ChatGPT, or Cursor without requiring custom SDKs or integration code.
What kind of outputs does EmidLabs provide after running a backtest?
Outputs include trades, win rates, expectancy in R-units, profit factors, and detailed diagnostics such as condition frequency and score distributions.
How do I get started with EmidLabs?
Users can start by accessing the Backtesting API to define and test strategies using the JSON DSL, then proceed to live execution or strategy storage via API endpoints or MCP connections.
