Prerequisites
- fracta CLI installed and on PATH (
fracta --helpworks). See installation. - Docker — for running FalkorDB (the knowledge graph).
- A runtime CLI — at least one of:
claude(Claude Code):npm install -g @anthropic-ai/claude-codecodex(OpenAI Codex):npm install -g @openai/codexopencode(OpenCode):npm install -g opencode-ai
- A git repository to scaffold into.
fracta initruns in your own project root, not in the fracta repo.
1. Initialize fracta in your project
From the root of any git repository:fracta.yaml is yours to edit. The defaults work for getting started; later you’ll tune agents.agent_runtimes, auth.credentials.profiles, and project.allowed_tools.
2. Start FalkorDB
The knowledge graph powers graph tools and strategy execution. Start it with Docker:3. Wire fracta into your AI CLI
Each runtime CLI has its own MCP-server config format. The simplest approach is to add a fracta entry that runsfracta serve from your project root.
Claude Code (.mcp.json at the project root):
fracta serve reads ./fracta.yaml by default. To pass a different config or extra flags, add them to args.
Codex (.codex/config.toml):
opencode.json setup.
Secret injection (optional)
If you use a secret manager, wrap the command. For 1Password:["run", "--", "fracta", "serve"]. For plain env vars, set them in your shell before starting the AI CLI — fracta inherits the environment.
4. Auth credentials
Agents need credentials to talk to their LLM provider. The default scaffoldedfracta.yaml ships an example auth profile that points at deployment/auth-helpers/fetch-token-example — a deliberately non-functional template that fails loudly until you edit it.
Add a real helper script for your provider. For example, for Anthropic API:
fracta.yaml to reference it:
deployment/auth-helpers/fetch-token-example. The full pipeline is documented in the credential pipeline guide.
5. Connect from your AI CLI
Restart Claude Code (or press/mcp to reconnect MCP servers). Fracta auto-starts the control plane daemon when fracta serve runs and no daemon is detected.
You should see fracta tools available — fracta_spawn, fracta_list, graph_query, etc.
If using Codex, restart Codex. Same auto-start behavior applies.
6. Spawn your first agent
From the CLI:fracta_list() and fracta_peek(name="hello-world").
What just happened
- The spawn request went to the control plane daemon via HTTP.
- The control plane created a git worktree at
.fracta/worktrees/hello-worldon branchfeature/hello-world. - It wrote runtime workspace files (
.mcp.json,.claude/settings.json) into the worktree. - It launched a Claude subprocess pointed at the worktree.
- The agent connected to the gateway at
:8080for MCP tools. - The agent executed the task and completed.
- The reaper will eventually clean up the worktree.
Strategy runner gateway plumbing
Local mode runs the gateway and the strategy runner in one process, so the runner can in principle reach the gateway directly. The framework still relies on the per-requestgateway_url and agent_task to be set, which only happens when strategy.gateway_access: true is in fracta.yaml. Since v0.5.2 the local scaffold ships with that flag enabled by default:
requires.mcp: true (e.g. highlight-distill, notion-publish) will refuse to start without it.
Next steps
- Full local-process reference: deployment overview (Section 1)
- Multi-runtime configuration: runtime configuration
- Credential deep dive: credential pipeline
- Ready for the full stack? Try Docker Compose Quickstart

