Documentation
This is the SMEme creator guide. It explains how to encode expert judgment as a decision tree, Deploy it for agents, connect MCP clients, and obtain a structured report from evidence — without putting proprietary branching logic inside the model.
You're reading version 1.7.0 of the SMEme documentation. Read the changelog.
Build a decision tree
Use the AI wizard or build and revise through MCP chat. Create question nodes, conclusion nodes, and the edges between them.
Building decision trees → Build or revise through MCP →Deploy, list, & delete
Run readiness checks, deploy your decision tree, set Listed or Hidden, and remove trees you no longer need.
Deploy, list, & delete →Connect your agent
Add the MCP connector, complete OAuth, and let your agent bootstrap via guidance tools.
MCP setup →Guides
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Building decision trees
Create, edit, save, and version your decision trees.
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Plans & usage
Free and Pro limits, MCP tool-call metering, and AI-assisted build credits.
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Deploy, list, & delete
Readiness checks, deploy, Listed/Hidden visibility, and permanent decision tree removal.
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Download your decision tree
Export the saved graph as a JSON file from the dashboard or editor.
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Connect your agent
Build or revise drafts through MCP, add the connector, and run deployed trees against evidence.
About
SMEme is a product of Arista Labs — making expert knowledge machine-readable so high-stakes decisions can scale without losing accountability or human control. Visit aristalabs.ai.