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Model Context Protocol (MCP)

Integrate Data Agents into AI applications using the Model Context Protocol. Access all Data Agents—whether you built them, replicated them, instantiated them, or they exist in the marketplace—through a unified MCP interface.

Available Data Agents​

Once connected via MCP, you can query any Data Agent in your account, including:

  • Data Agents you built - Custom agents developed with the Python SDK
  • Replicated agents - Agents you've replicated from existing blueprints
  • Instantiated agents - Running agent instances you've created
  • Marketplace agents - Pre-built agents from the Data Agent Marketplace

How MCP Works with Data Agents​

MCP acts as a universal connector between AI applications and your Data Agents. When you configure the Heisenberg MCP connector, you gain access to all Data Agents in your account through a standardized interface.

The Connector​

The Heisenberg Connector provides MCP access to your Data Agents. Once configured in your AI application, it automatically discovers and makes available:

  • All agents you've created or deployed
  • All agents you've replicated or instantiated
  • All marketplace agents you have access to

Unified Access​

Instead of integrating each Data Agent individually, MCP provides a single connection point. Your AI application connects once to the Heisenberg MCP server, then can query any of your available Data Agents through the same interface.

Integration Steps​

1. Configure the Heisenberg Connector​

Add the Heisenberg MCP connector to your AI application:

For Claude Desktop:

  1. Open Claude Desktop settings
  2. Navigate to "Developer" → "Model Context Protocol"
  3. Add new MCP server:
    • Name: Heisenberg
    • Transport: SSE (Server-Sent Events)
    • URL: Your Heisenberg MCP endpoint URL
    • API Key: Your Heisenberg API key
  4. Save and restart Claude

For Other Applications: Configure your MCP client to connect to the Heisenberg MCP endpoint with your API key for authentication.

2. Authenticate​

The connector authenticates using your Heisenberg API key, establishing a session that provides access to all your Data Agents.

3. Discover Available Agents​

Once connected, your AI application can list all available Data Agents:

  • Agents you built with the Python SDK
  • Agents you replicated from blueprints
  • Agents you instantiated
  • Marketplace agents you have access to

4. Query Any Agent​

Select and query any Data Agent through natural language or structured queries. The MCP interface handles routing queries to the correct agent and returning structured results.

Query Methods​

Semantic Retrieval​

Query Data Agents using natural language:

  • "Show me trending tweets about AI in the last 24 hours"
  • "What are the top Reddit posts on r/cryptocurrency this week?"
  • "Find YouTube videos mentioning Bitcoin from the past 3 days"

Parameterized Retrieval​

Query with structured parameters for precise control:

{
  "duration": "last_day",
  "category": "defi",
  "min_score": 100
}

Workflow​

A typical MCP session with Data Agents:

1. Configure Heisenberg Connector
   ↓
2. Authenticate with API key
   ↓
3. List all available Data Agents
   ↓
4. Select the agent you want to query
   ↓
5. Perform retrieval (semantic or parameterized)
   ↓
6. Process results in your application

Getting Started​

Prerequisites​

  • Active Heisenberg account
  • API key for authentication
  • At least one Data Agent (built, replicated, instantiated, or from marketplace)

Quick Start​

  1. Get API Key - Generate an API key from your Heisenberg dashboard
  2. Configure Connector - Add Heisenberg MCP connector to your AI application
  3. List Agents - Discover all available Data Agents
  4. Start Querying - Select an agent and begin retrieving data

Next Steps​