emergent.strategy

Manage Emergent runtime agents and agent definitions — create, trigger, monitor runs, respond to questions, and manage agent configurations. Use when the user wants to run, inspect, or configure AI agents in an Emergent project.

Apply and export Emergent Blueprints — declarative directories of template packs, agent definitions, and seed data applied with `memory blueprints`. Use when setting up a project from a blueprint, seeding graph data, or exporting an existing project's graph as re-applyable seed files.

Full Memory CLI command reference with all subcommands and flags. Use when you need exact command syntax, flag names, or usage examples for any `memory` CLI command.

Manage MCP (Model Context Protocol) servers in an Emergent project — register, inspect, sync tools, and delete servers. Use when the user wants to add, configure, or troubleshoot MCP servers connected to their Emergent project.

Onboard a project into Memory — understand what the project is, choose or create a Memory project, design and install a schema (template pack), then guide on creating objects and relationships. Use when setting up Memory for a new project or codebase for the first time.

Manage LLM provider credentials and browse available models in Emergent. Use when the user wants to configure API keys, set up Vertex AI, check which models are available, or review LLM usage and costs.

Query an Emergent project knowledge base using natural language or direct hybrid search. Use when the user wants to search, explore, or ask questions about content in an Emergent project.

Manage Emergent schemas (template packs) — discover, install, and remove reusable sets of object and relationship types in a project. Use when the user wants to configure what types of knowledge objects a project can contain.