agentdb-init

# Initialize AgentDB Sets up a fresh AgentDB instance for the current project. Creates a single-file `.rvf` Cognitive Container that holds vectors, indexes, learning state, and the audit log. ## When to use - User asks to "set up agentdb", "init memory", "add a vector store" - New project that needs persistent agent memory - Existing project moving from in-memory state to durable memory ## Steps 1. Confirm the storage path (default: `./memory.rvf` at the project root, or `~/.agentdb/<project-name>.rvf` for global memory). 2. Pick the embedder (default: `Xenova/all-MiniLM-L6-v2` at 384d — fast, free, runs in-process). 3. Register the agentdb MCP server in Claude Code: ```bash claude mcp add agentdb -- npx agentdb@latest mcp start ``` 4. Initialize the file via the MCP tool `agentdb_pattern_store` (the first store auto-creates the schema), or via CLI: ```bash npx agentdb@latest init ./memory.rvf ``` 5. Add `*.rvf` to `.gitignore` unless the user explicitly wants memory checked into source control. 6. Confirm with a smoke test: store one pattern and search for it. ## Notes - The `.rvf` is a single binary file. Back it up like a SQLite database. - For multi-agent setups, share one `.rvf` per coordinated namespace; use separate files for trust-boundary isolation. - All AgentDB operations after init go through the MCP tools (`agentdb_pattern_*`, `agentdb_reflexion_*`, etc.) or the npm library (`import { SelfLearningRvfBackend } from 'agentdb'`). ## Don't - Don't commit the `.rvf` file by default — it can hold session-specific data, including content from messages. - Don't run `init` on an existing `.rvf` file without confirming — it will refuse rather than overwrite, but a confused user might delete the existing file thinking it's stale.