A keyboard-driven AI agent for the terminal and desktop. Built in Rust, sven
works as an interactive TUI, a Slint desktop GUI (sven-ui), a headless CI
runner, a networked node that teams up with other sven instances, and a
proactive personal automation platform — two binaries, one agent.
Give sven a task in plain English. It reads your code, runs commands, writes files, searches the web, and delegates subtasks to peer agents — all autonomously, all in your terminal. Beyond interactive sessions, sven runs 24/7 as a proactive agent: checking email and calendar, sending briefings via Telegram, making voice calls, and running scheduled workflows.
- Interactive TUI — Full-screen Ratatui interface with scrollable markdown chat, vim-style navigation, and live-streamed responses. Swap to an embedded Neovim buffer with
--nvim. - Desktop GUI —
sven-uiis a native Slint window with the full agent and tool suite, no terminal required. - Headless / CI — Reads from stdin or a markdown workflow file, writes clean text to stdout. Pipeable: chain sven instances to build multi-agent pipelines.
- Markdown workflow files —
##-headed steps, YAML frontmatter, per-step directives, and variable templating make.mdfiles first-class agent programs (unique to sven). - Agent networking — Multiple sven nodes discover each other via mDNS (or a relay), and the LLM gains
list_peersanddelegate_tasktools to route work across machines. - GDB hardware debugging — First AI agent with native GDB integration: connects to a target, loads firmware, sets breakpoints, and inspects registers, all autonomously.
- Proactive automation — Scheduler, email (IMAP/Gmail), calendar (CalDAV/Google), voice (TTS/STT/calls), semantic memory, and 6 messaging channels run 24/7 as a node.
- Skills system — Markdown instruction files the agent loads on demand for coding standards, project conventions, or multi-step procedures.
- 32 model providers — OpenAI, Anthropic, Gemini, Ollama, and 28 more — no external gateway, pure Rust.
- MCP — server and client — Expose sven's tools to Cursor, Claude Desktop, and other MCP hosts; or connect sven to external MCP servers (including OAuth-protected ones) and use their tools directly inside any session.
- ACP — Drive sven from Zed, VS Code, or JetBrains via the Agent Client Protocol; no daemon, no IDE key, sven manages its own model.
- Large-content analysis — RLM context tools (
context_open,context_query,context_reduce) memory-map files and codebases far larger than any context window and analyse them via parallel sub-agent chunking. - Knowledge base —
.sven/knowledge/*.mddocuments encode project facts; sven auto-detects drift when source files change after a document'supdated:date and warns at session start. - Terminal-native, zero runtime deps — Structured text in, structured text out. No Node.js, no Python, no screenshots, no pixel-clicking.
Prerequisites: Rust toolchain, API key for at least one supported provider (e.g. OPENROUTER_API_KEY for zero-config start with openrouter/auto).
# Build and run
make release && ./target/release/sven
# Pipe a one-shot task
echo "Summarise the project" | sven
# Run a multi-step workflow file
sven --file plan.mdSee Installation and Quick Start for full setup details.
Install shell completions:
sven completions bash >> ~/.bashrc # also: zsh, fish, powershell| Mode | Behaviour |
|---|---|
research |
Read-only tools. Good for exploration and analysis. |
plan |
No file writes. Produces structured plans without side effects. |
agent |
Full read/write access. Default for interactive use. |
Set with --mode or cycle live in the TUI with F4.
sven chats # list saved conversations (ID, date, turns, title)
sven --resume # pick a conversation to resume with fzf
sven --resume <ID> # resume a specific conversation directlySven is the first AI agent with native GDB integration for autonomous embedded hardware debugging. Give it a plain-English task and it will start a GDB server, connect to the target, load your firmware, set breakpoints, inspect registers and variables, and report its findings — all without leaving your terminal.
| Tool | What it does |
|---|---|
gdb_start_server |
Start JLinkGDBServer / OpenOCD / pyocd (auto-discovers config from project files) |
gdb_connect |
Connect gdb-multiarch --interpreter=mi3 and optionally load an ELF |
gdb_command |
Run any GDB/MI command and return structured output |
gdb_interrupt |
Send Ctrl+C to a running target |
gdb_wait_stopped |
Poll until the target halts (after a step, breakpoint, or interrupt) |
gdb_status |
Query the current run state and any pending stop events |
gdb_stop |
Kill the debug session and free the probe |
See Example 11 and the GDB section of the User Guide.
Multiple sven nodes find each other on a local network via mDNS — or across networks via a relay — and each node automatically gains two tools the LLM can use during any session:
| Tool | What it does |
|---|---|
list_peers |
List connected peer agents with their name, description, and capabilities |
delegate_task |
Send a task to a named peer; the remote agent runs it through its own model+tool loop and returns the full result |
Declarative agent teams are defined in .sven/teams/*.yaml. Manage them with:
sven team start --file .sven/teams/myteam.yaml # spawn all team members
sven team status myteam # show live task board
sven peer chat backend-agent # interactive session with any peerSee docs/08-node.md for setup, relay configuration, and security.
When running as a node (sven node start), sven gains a full automation stack:
| Integration | What it does | Docs |
|---|---|---|
| Messaging (Telegram, Discord, WhatsApp, Signal, Matrix, IRC) | Reach your agent or let it reach you via any channel | docs/12-channels.md |
| Scheduler (cron, intervals, one-shot) | Run prompts on a schedule; the agent can also schedule jobs at runtime | docs/13-scheduler.md |
| Email (IMAP/SMTP, Gmail API) | List, read, send, reply to, and search email | docs/14-email.md |
| Calendar (CalDAV, Google Calendar) | Query schedule, create and update events | docs/15-calendar.md |
| Voice (ElevenLabs TTS, Whisper STT, Twilio calls) | Synthesize speech, transcribe audio, make outbound phone calls | docs/16-voice.md |
| Semantic memory (SQLite + FTS5 + embeddings) | Remember anything; recall with natural-language queries | docs/17-memory.md |
| Webhooks | Trigger the agent from any external system via a generic HTTP hook | docs/18-webhooks.md |
See docs/19-use-cases.md for seven complete real-world automation patterns.
sven treats markdown files as first-class workflow definitions:
# Security Audit
## Understand the codebase
<!-- sven: timeout=60 -->
Read the project structure and summarise the architecture.
## Identify risks
{{context}}
Look for OWASP Top-10 issues and insecure defaults.
## Write report
Produce a structured security report with severity ratings.sven --file audit.md --var context="Focus on authentication."Each ## heading is a step. YAML frontmatter sets mode and model. Per-step
<!-- sven: ... --> directives control timeouts. Variable templating with
{{key}} fills values at runtime.
sven validate --file audit.md # parse and lint a workflow file without running itSee docs/04-ci-pipeline.md for output formats, exit codes, and CI integration.
sven ships three commands for fan-out/fan-in agent pipelines:
# Run one agent per input line in parallel, substituting {} with each line
git diff --name-only HEAD~1 | sven map 'review {} for security issues'
sven map --concurrency 8 --model groq/llama-3.3-70b-versatile 'summarise {}'
# Broadcast one stdin to N commands in parallel and merge the results
sven tee "sven 'find security issues'" "sven 'find performance issues'"
# Synthesise all stdin into a single agent (fan-in)
git diff --name-only HEAD~1 | sven map 'review {}' | sven reduce 'prioritise findings and write a report'sven index builds a fast symbol-search index over the current repo:
sven index build # create/update .sven/index/index.json
sven index query "Handler" # search symbol names and signatures
sven index stats # show index statistics| Category | Tools |
|---|---|
| Files | read_file, write_file, edit_file, delete_file, list_dir |
| Search | find_file, grep, search_codebase |
| Shell | run_terminal_command, shell |
| Web | web_fetch, web_search |
| Images | read_image |
| Sub-agents | task — spawn a focused sub-agent for a self-contained subtask |
| GDB / hardware | gdb_start_server, gdb_connect, gdb_command, gdb_interrupt, gdb_wait_stopped, gdb_status, gdb_stop |
| Agent networking | list_peers, delegate_task (node mode only) |
| Messaging | send_message — send to any configured channel |
| Scheduler | schedule — create, list, enable, disable, delete jobs |
email — list, read, send, reply to, and search email |
|
| Calendar | calendar — query schedule, create/update/delete events |
| Voice | voice — TTS, STT, outbound calls |
| Memory | semantic_memory — remember, recall (BM25 + vector), forget, list, get |
| Large content | context_open, context_read, context_grep, context_query, context_reduce — memory-map files/dirs and analyse content larger than the context window |
| Streaming buffers | buf_status, buf_read, buf_grep — inspect live output from running sub-agents or shell commands |
| Knowledge | list_knowledge, search_knowledge — query .sven/knowledge/ project knowledge documents |
| Collaboration | send_message (peer), wait_for_message, search_conversation, list_conversations, post_to_room, read_room_history (node mode only) |
| Session | switch_mode, todo, update_memory, ask_question†, read_lints, load_skill |
†ask_question is only available in interactive TUI sessions.
Each tool call goes through a configurable approval policy — auto-approved, denied, or presented for confirmation based on glob patterns.
| Key | Action |
|---|---|
F4 |
Cycle agent mode (research → plan → agent) |
--nvim |
Launch with embedded Neovim buffer |
Ctrl+b |
Toggle chat list sidebar; n new, d delete, a archive |
/ |
In-chat search; n/N next/previous match |
Ctrl+t |
Full-screen transcript pager (vim navigation + / search) |
d / x |
Truncate history from focused segment / remove focused segment |
r |
Truncate to just before the focused segment and re-submit |
e / Enter |
Edit a sent message in-place |
y / Y |
Copy focused segment / entire chat to clipboard |
| Mouse | Click to select, drag to copy, scroll wheel in input pane |
? |
Show full key-binding reference |
Sven supports 32 model providers natively in Rust — no external gateway required.
| Category | Providers |
|---|---|
| Major cloud | OpenAI, Anthropic, Google Gemini, Azure OpenAI, AWS Bedrock, Cohere |
| Gateways | OpenRouter, LiteLLM, Portkey, Vercel AI, Cloudflare |
| Fast inference | Groq, Cerebras |
| Open models | Together AI, Fireworks, DeepInfra, Nebius, SambaNova, Hugging Face, NVIDIA NIM |
| Specialized | Mistral, xAI (Grok), Perplexity |
| Regional | DeepSeek, Moonshot, Qwen/DashScope, GLM, MiniMax, Baidu Qianfan |
| Local / OSS | Ollama, vLLM, LM Studio |
See docs/providers.md for configuration details.
Sven implements the Agent Client Protocol (ACP), letting ACP-aware editors drive it directly over stdio. No daemon, no relay, no IDE API key required — sven manages its own model.
// Zed: add to ~/.config/zed/settings.json
{
"agents": {
"sven": { "command": "sven", "args": ["acp", "serve"] }
}
}The same sven acp serve command works for VS Code (ACP extension) and JetBrains (AI Assistant plugin). See the IDE integration guide.
As a server — expose sven's full tool suite to Cursor, Claude Desktop, opencode, and any other MCP-compatible host:
{
"mcpServers": {
"sven": { "command": "sven", "args": ["mcp", "serve"] }
}
}As a client — connect sven to any external MCP server and use its tools transparently in every session. OAuth 2.0 PKCE, Dynamic Client Registration, and token refresh are handled automatically. Configure servers in ~/.config/sven/config.yaml:
mcp_servers:
- name: atlassian
command: npx
args: ["-y", "@atlassian/mcp-server"]
- name: github
url: https://api.githubcopilot.com/mcp/| Section | Topic |
|---|---|
| Introduction | What sven is and how it works |
| Installation | Getting sven onto your machine |
| Quick Start | Your first session in five minutes |
| User Guide | TUI navigation, modes, tools, conversations |
| CI and Pipelines | Headless mode, workflow files, and CI integration |
| Configuration | All config options explained |
| Examples | Real-world use cases |
| Troubleshooting | Common issues and fixes |
| Node / P2P | Remote access, device pairing, agent networking |
| Agent Collaboration | Peer conversations, rooms, and gossipsub broadcast |
| Large-Content Analysis | RLM context tools for files larger than the context window |
| Teams and Tasks | Declarative agent teams, task board, git worktree isolation |
| Messaging Channels | Telegram, Discord, WhatsApp, Signal, Matrix, IRC |
| Scheduler | Cron jobs, intervals, heartbeat |
| IMAP/SMTP and Gmail integration | |
| Calendar | CalDAV and Google Calendar integration |
| Voice | TTS, STT, and outbound voice calls |
| Semantic Memory | SQLite + FTS5 "second brain" knowledge store |
| Webhooks | Generic HTTP hooks for external integrations |
| Automation Use Cases | Seven complete real-world automation patterns |
| Providers | Model provider configuration |
Build the full user guide locally:
make docs # → target/docs/sven-user-guide.md
make docs-pdf # → target/docs/sven-user-guide.pdf (requires pandoc)make build # debug build
make release # optimised release build
make deb # Debian packageRequires a recent stable Rust toolchain. No other system dependencies.
make test # unit and integration tests
make tests/e2e # end-to-end tests (requires bats-core)
make check # clippy lintssven merges YAML config from /etc/sven/config.yaml → ~/.config/sven/config.yaml → .sven/config.yaml → sven.yaml → --config <path>. Run sven show-config to inspect the resolved result.
See docs/05-configuration.md for all options.
Contributions are welcome. Open an issue or pull request on GitHub. For larger changes, open an issue first to discuss the approach.
Licensed under the Apache License 2.0. See CHANGELOG.md for version history.