ByteRover CLI

Interactive REPL CLI for AI-powered context memory

Overview

ByteRover CLI (brv) gives AI coding agents persistent, structured memory. It lets developers curate project knowledge into a context tree, sync it to the cloud, and share it across tools and teammates.

Run brv in any project directory to start an interactive REPL powered by your choice of LLM. The agent understands your codebase through an agentic map, can read and write files, execute code, and store knowledge for future sessions.

📄 Read the paper for the full technical details.

Or download our self-hosted PDF version of the paper here.

Key Features:

• 🌐 Web dashboard for curating and querying context (brv webui)
• 🖥️ Interactive TUI with REPL interface (React/Ink)
• 🧠 Context tree and knowledge storage management
• 🔀 Git-like version control for the context tree (branch, commit, merge, push/pull)
• 🤖 20 LLM providers (Anthropic, OpenAI, Google, Groq, Mistral, xAI, DeepSeek, and more)
• 🛠️ 24 built-in agent tools (code exec, file ops, knowledge search, memory management)
• 🔄 Cloud sync with push/pull
• 👀 Review workflow for curate operations (approve/reject pending changes)
• 🔌 MCP (Model Context Protocol) integration
• 📦 Hub and connectors ecosystem for skills and bundles
• 🤝 Works with 22+ AI coding agents (Cursor, Claude Code, Windsurf, Cline, and more)
• 🏢 Enterprise proxy support

Benchmark Results

All benchmarks are run using the production byterover-cli codebase in this repository - no separate research prototype.

We evaluate on two long-term conversational memory benchmarks:

• LoCoMo - ultra-long conversations (~20K tokens, 35 sessions) testing single-hop, multi-hop, temporal, and open-domain retrieval.
• LongMemEval-S - large-scale benchmark (23,867 docs, ~48 sessions per question) testing 6 memory abilities including knowledge update, temporal reasoning, and multi-session synthesis.

LoCoMo - 96.1% overall accuracy (1,982 questions, 272 docs).

LongMemEval-S - 92.8% overall accuracy (500 questions, 23,867 docs).

All metrics are LLM-as-Judge accuracy (%). See the paper, or self-hosted PDF for full details.

Quick Start

Shell Script (macOS & Linux)

No Node.js required - everything is bundled.

curl -fsSL https://byterover.dev/install.sh | sh

Supported platforms: macOS ARM64, macOS x64 (Intel), Linux x64, Linux ARM64.

npm (All Platforms)

Requires Node.js >= 20.

npm install -g byterover-cli

Verify

brv --version

First Run

cd your/project
brv

The REPL auto-configures on first run - no setup needed. Type / to discover all available commands:

/curate "Auth uses JWT with 24h expiry" @src/middleware/auth.ts
/query How is authentication implemented?

ByteRover Cloud

ByteRover Cloud is a hosted platform for teams to sync, share, and manage context knowledge across projects and machines. Everything works locally by default - Cloud adds collaboration and persistence without changing your workflow.

Sign in from the dashboard, or run brv login with an API key.

• 🔄 Team context sync — push and pull shared knowledge across teammates
• 📂 Shared spaces — organize context across multiple projects and teams
• 💻 Multi-machine access — sync your context tree across devices with cloud backup
• 💻 Multi-machine access — sync your context tree across devices
• 🧠 Built-in hosted LLM — start immediately with limited free usage
• 👥 Team management — manage members, spaces, and permissions via the web app
• 📊 Usage analytics — track seat allocation and monthly credit consumption
• 🔒 SOC 2 Type II certified infrastructure with privacy mode

brv                  # Start interactive REPL
brv webui            # Open the ByteRover dashboard (primary UI)
brv status           # Show project and daemon status
brv curate           # Add context to knowledge storage
brv curate view      # View curate history
brv query            # Query context tree and knowledge
brv review pending   # List pending review operations
brv review approve   # Approve curate operations
brv review reject    # Reject curate operations

brv push             # Legacy — migrate or snapshot context to cloud
brv pull             # Legacy — restore context from cloud snapshot

brv vc init              # Initialize version control for context tree
brv vc status            # Show version control status
brv vc add               # Stage files for the next commit
brv vc commit            # Save staged changes as a commit
brv vc log               # Show commit history
brv vc branch            # List, create, or delete branches
brv vc checkout          # Switch branches
brv vc merge             # Merge a branch into the current branch
brv vc clone             # Clone a ByteRover space repository
brv vc push              # Push commits to ByteRover cloud
brv vc pull              # Pull commits from ByteRover cloud
brv vc fetch             # Fetch refs from ByteRover cloud
brv vc remote            # Show current remote origin
brv vc remote add        # Add a named remote
brv vc remote set-url    # Update a remote URL
brv vc config            # Get or set commit author
brv vc reset             # Unstage files or undo commits

brv providers list       # List available LLM providers
brv providers connect    # Connect to an LLM provider
brv providers switch     # Switch active provider
brv providers disconnect # Disconnect a provider
brv model list           # List available models
brv model switch         # Switch active model

brv hub list             # List available hub packages
brv hub install          # Install a hub package
brv hub registry add     # Add a custom registry
brv hub registry list    # List registries
brv hub registry remove  # Remove a registry
brv connectors list      # List connectors
brv connectors install   # Install a connector

brv space list       # Deprecated — use web dashboard
brv space switch     # Deprecated — use brv vc clone

brv mcp              # Start MCP server
brv login            # Authenticate to ByteRover
brv logout           # Disconnect and clear credentials
brv locations        # List registered projects
brv restart          # Restart daemon
brv debug            # Debug mode

Worktrees and Knowledge Sources

Vocabulary

• Worktree link — a subdirectory pointer to a parent project (brv worktree)
• Source — a read-only reference to another project's knowledge (brv source)
• Origin — where an indexed search result came from (local vs shared)

ByteRover can run from a linked subdirectory without creating a nested .brv/.

• projectRoot: the directory that owns .brv/config.json
• worktreeRoot: the linked worktree directory, or projectRoot when unlinked
• clientCwd: the shell cwd where you ran brv

When you run brv query or brv curate from a linked worktree, implicit defaults use worktreeRoot so scope stays stable even if clientCwd drifts deeper into the package. Explicit relative paths that you pass yourself, such as brv curate -f ./src/auth.ts, still resolve from clientCwd to match normal shell behavior.

Use brv worktree add from the project root to register a subdirectory (or sibling) as a worktree. This creates a .brv pointer file in the target directory that redirects to the parent project — the same pattern git uses for git worktree. Use brv worktree remove to unregister, and brv worktree list to inspect. To search another project's knowledge from here, use brv source add <path> (with brv source list / brv source remove to inspect or detach).

Documentation

Visit docs.byterover.dev for full guides on setup, integrations, and advanced usage.

Contributing

We welcome contributions! See our Contributing Guide for development setup, coding standards, and the PR workflow.

Community & Support

ByteRover CLI is built and maintained by the ByteRover team.

• Join our Discord to share projects, ask questions, or just say hi
• Report issues on GitHub
• If you enjoy ByteRover CLI, please give us a star on GitHub — it helps a lot!
• Follow @kevinnguyendn on X

Contributors

Star History

License

Elastic License 2.0. See LICENSE for full terms.