Model Context Protocols (MCPs) - Overview

Model Context Protocols (MCPs) Framework

Architecture Overview

Model Context Protocols (MCPs) form the foundation of INTUE's intelligence capabilities. Each protocol specializes in processing specific market data into contextually relevant signals through standardized interfaces.

// MCP base interface
interface ModelContextProtocol {
  process(data: RawData): Signal[];
  configure(options: ConfigOptions): void;
  getMetadata(): ProtocolMetadata;
  getStatus(): ProtocolStatus;
}

MCPs are organized into four primary categories:

1. Category MCPs: Focus on specific token categories with specialized metrics

2. Metric MCPs: Process standardized market metrics across assets

3. Correlation MCPs: Identify relationships between different data points

4. Analysis MCPs: Apply advanced statistical methods to market data

Protocol Composition

MCPs are designed for composition, allowing complex analyses through the combination of simpler protocols:

// Example of protocol composition
const volumeSentimentCorrelation = new CorrelationMCP({
  source1: new VolumeMCP({ granularity: '1h' }),
  source2: new SentimentMCP({ source: 'twitter' }),
  method: 'pearson',
  windowSize: 24  // hours
});

This compositional architecture enables:

• Reusable building blocks for complex analyses

• Standardized interfaces between components

• Independent development and improvement of protocols

• Efficient computational resource allocation

Data Flow

┌─────────────────┐
│ Raw Market Data │
└────────┬────────┘
         ▼
┌─────────────────────┐
│ Category             │
│ Classification       │
└────────┬─────────────┘
         ▼
┌─────────────────────┐
│ Metric Processing    │
└────────┬─────────────┘
         ▼
┌─────────────────────┐
│ Correlation          │
│ Detection            │
└────────┬─────────────┘
         ▼
┌─────────────────────┐
│ Advanced Analysis    │
└────────┬─────────────┘
         ▼
┌─────────────────────┐
│ Agent Consumption    │
└─────────────────────┘

Each MCP transforms input data according to its specialized function and outputs standardized signals that can be consumed by agents or other protocols.

Protocol Lifecycle

MCPs implement a standard lifecycle:

1. Initialization: Protocol is instantiated with default parameters

2. Configuration: Protocol is configured with specific options

3. Data Ingestion: Raw data is provided to the protocol

4. Processing: Protocol applies its specialized algorithms

5. Signal Generation: Processed results are output as standardized signals

6. Metadata Updating: Protocol updates its internal state and performance metrics

This standardized lifecycle ensures consistent behavior across all protocols and simplifies agent integration.

Performance Monitoring

Each MCP maintains internal performance metrics:

• Processing latency

• Signal accuracy (where applicable)

• Resource utilization

• Data quality assessment

These metrics enable continuous optimization and help agents make informed decisions about protocol utilization.