Mermaid

An open-source AI coding assistant with computer use for the terminal. Multi-provider — Ollama (local), Anthropic, Gemini, OpenAI, Groq, OpenRouter, and any OpenAI-compatible endpoint — with native tool calling, subagents, computer-use tools, and a clean TUI.

Features

• Multi-Provider — Ollama (local/cloud), Anthropic Claude, Google Gemini, OpenAI, Groq, OpenRouter, Cerebras, DeepInfra, Together, plus fully-custom OpenAI-compatible endpoints
• Native Tool Calling — read, write, edit, delete, create directories, execute commands, search the web, spawn subagents, and call configured MCP tools
• Computer Use — screenshot, click, type, press keys, scroll, move the mouse, and list windows on supported interactive GUI backends
• Subagents — spawn parallel autonomous agents for independent tasks
• Agent Loop — model calls tools autonomously, sees results, and continues until done
• Image Paste — Ctrl+V to attach images for vision models (X11/Wayland/macOS/Windows)
• Reasoning Levels — seven tiers (none/minimal/low/medium/high/xhigh/max); cycle with Alt+T or set via /reasoning; persisted per-model
• Safety Modes — read_only/ask/auto/full_access; auto is classifier-backed (an LLM vets each borderline action against your intent, auto-running aligned ones and escalating risky ones); cycle live with Shift+Tab or /safety
• Inline approvals — in ask mode (and auto escalations) a gated action pauses and prompts inline (1 Yes · 2 Yes, don't ask again · 3/Esc No); the agent waits for your answer instead of erroring out
• Project Instructions — auto-loads AGENTS.md and MERMAID.md (MERMAID.md wins on conflict); edits take effect on the next turn
• MCP Servers — stdio JSON-RPC client with a built-in registry of 16 popular servers (mermaid add <name>)
• Session Persistence — conversations auto-save and resume with --continue
• Message Queuing — type while the model generates, messages send in order
• Non-Interactive Mode — script with mermaid run "prompt" for CI/automation

Architecture

Mermaid's runtime is an Elm/MVU pattern: one pure reducer (fn update(State, Msg) -> (State, Vec<Cmd>)), effects as data, structured concurrency per turn. Whole classes of bug the old architecture let slip — duplicate error display, 20-press Ctrl+C during tool execution, stale stream events corrupting a new turn — are statically impossible against the new types.

Read docs/architecture.md for the full tour. The adding a tool and adding a provider recipes are one file each; docs/replay_debugging.md covers record/replay for reproducing bugs.

Get started

No Rust or cargo required — the installer downloads a prebuilt binary for your platform from the latest GitHub Release, verifies its checksum, and puts mermaid on your PATH.

macOS / Linux

curl -fsSL https://noahsabaj.github.io/mermaid-cli/install.sh | sh

Windows (PowerShell)

irm https://noahsabaj.github.io/mermaid-cli/install.ps1 | iex

Then run mermaid to start, and mermaid update whenever you want the newest version. (Set MERMAID_INSTALL_DIR to change the install location, or MERMAID_VERSION=vX.Y.Z to pin a specific release.)

cargo install mermaid-cli                                      # from crates.io
cargo install --git https://github.com/noahsabaj/mermaid-cli   # latest from git

Prebuilt binaries (plus .deb/.rpm) are attached to every release; the crates.io release can lag the newest tag.

Local inference requires Ollama (models auto-pull if not found locally). Cloud providers are optional — see Remote Providers below.

First 10 Minutes

mermaid doctor                         # Check model, tools, safety, and project instructions
mermaid                                # Start the full-screen terminal coding agent

Then ask Mermaid to do normal coding-agent work:

• "read the repo and tell me where the test runner lives"
• "find the bug in this failing test and fix it"
• "add this small feature and run the relevant tests"
• "review the current branch for regressions"

Inside the TUI, use /help for grouped commands, /doctor for the current session readiness report, /context to inspect prompt budget and compaction status, /compact [focus] to create a handoff checkpoint, and Esc to interrupt the current agent loop.

Computer Use Dependencies (optional)

For full Linux GUI control via screenshot/click/type tools:

# Linux / X11
sudo apt install scrot xdotool xclip

# Linux / Wayland
sudo apt install grim ydotool wtype wl-clipboard

# Screenshot downscaling (optional, for high-res displays)
sudo apt install imagemagick

Computer-use registration is backend-gated: Linux/X11 and Linux/Wayland are the current full-control backends. macOS currently supports screenshot capture through screencapture plus clipboard image paste through pngpaste/osascript; click/type/scroll are not yet ported there. Windows clipboard paste uses PowerShell, but the computer-use backend is not wired yet. See src/providers/tool/computer_use/ for the implementation matrix.

Usage

mermaid                                         # Start fresh session
mermaid --continue                              # Resume last session
mermaid --sessions                              # Pick a previous session to resume
mermaid --model ollama/qwen3-coder:30b          # Ollama local
mermaid --model anthropic/claude-opus-4-7       # Anthropic (requires ANTHROPIC_API_KEY)
mermaid --model gemini/gemini-3.1-pro-preview   # Gemini (requires GOOGLE_API_KEY)
mermaid --model openai/gpt-5                    # OpenAI (requires OPENAI_API_KEY)
mermaid --model groq/qwen-qwq-32b               # Groq (requires GROQ_API_KEY)
mermaid --reasoning high                        # Override default reasoning depth
mermaid --path /path/to/project                  # Run against a specific project directory
mermaid --record /tmp/session.jsonl              # Record reducer events for replay/debugging
mermaid --append-system-prompt "Prefer small diffs" # Add one-off runtime instructions
mermaid --system-prompt-file ./prompt.md         # Replace the default prompt for one run
mermaid list                                    # List available models across providers
mermaid doctor                                  # First-run readiness check
mermaid status                                  # Lower-level Ollama, MCP, and provider config
mermaid self-test                               # Fast deterministic Mermaid self-test
mermaid init                                    # Create default config file
mermaid cloud-setup                             # Configure Ollama Cloud API key
mermaid run "fix the tests"                     # Non-interactive mode
mermaid run "explain main.rs" -f json           # JSON output
mermaid add <name>                              # Add an MCP server (e.g., context7, git)
mermaid remove <name>                           # Remove a configured MCP server
mermaid mcp                                     # List configured MCP servers
mermaid pr create                               # Open a PR/MR from the current branch (wraps gh/glab)

mermaid add <name> resolves the name through a built-in registry of 16 popular MCP servers (context7, playwright, memory, git, fetch, time, filesystem, notion, slack, postgres, brave-search, supabase, perplexity, docker, sequential-thinking, everything), prompts for any required env vars, validates by spawning the server, and saves it to ~/.config/mermaid/config.toml.

Keyboard Shortcuts

Slash Commands

Type / to open the command palette (shows all commands with live filter); type /<name> to invoke directly. /help shows the same commands grouped in the TUI.

Everyday:

• /doctor — show current model, safety, prompt, instruction, and tool readiness
• /clear, /save [name], /load [id], /list — manage the conversation
• /cancel [id] — cancel the active turn or a durable task
• /handoff [id], /report [id] — write a current-context report or inspect a task report
• /help (/h), /quit (/q)

Model and context:

• /model <name> — switch model; auto-pulls Ollama models if needed
• /reasoning <level> — set reasoning: none, minimal, low, medium, high, xhigh, max
• /visible-reasoning [on|off|toggle] — show or hide reasoning blocks in the transcript
• /usage, /context, /compact [instructions]
• /model-info <model>

Safety and recovery:

• /safety [read_only|ask|auto|full_access] (alias /permission) — show or set the session safety mode; Shift+Tab cycles it
• /approvals, /approve <id>, /deny <id>
• /checkpoint <path...>, /checkpoints, /restore <id>

Integrations:

• /plugins, /cloud-setup

Advanced runtime:

• /tasks, /task <id>, /pause <id>, /resume <id>
• /processes, /logs <id>, /stop <id>, /restart <id>, /open <target>, /ports

Reasoning choices persist per-model: setting /reasoning high on Claude Opus 4.7 and /reasoning low on Ollama is remembered across sessions.

Tools

The model uses these autonomously via native tool calling:

MCP servers contribute additional tools under the mcp__<server>__<tool> prefix when configured. Web tools are registered only when OLLAMA_API_KEY is set in the environment. Computer-use tools are advertised only in interactive TUI sessions when a usable GUI backend is detected.

Project Instructions

Create an AGENTS.md (the cross-tool open standard) and/or a MERMAID.md (mermaid-specific) at your project root with conventions, tool versions, naming patterns, and run commands. Both are loaded from the nearest matching directory — AGENTS.md first, then MERMAID.md, so MERMAID.md overrides on conflict. They auto-reload when the files change (one stat per turn, no filesystem watcher). The walk stops at the .git root or $HOME.

# Project: foo-service

## Conventions
- snake_case for functions, PascalCase for types
- No `unwrap()` outside of tests
- Run `cargo nextest run` for tests (not `cargo test`)

## Build
- `just dev` — dev server on :8080

File size is capped at ~10k tokens; oversized content is truncated with a marker so the model knows context was elided.

Runtime And Background Service

The CLI/TUI is the primary Mermaid app. mermaidd is optional advanced infrastructure for durable runtime state, remote attach, and long-running process ownership; normal chat, mermaid run, and mermaid self-test work without the user service.

mermaidd stores durable runtime state in ~/.local/share/mermaid/runtime.sqlite3 and exposes a local Unix-socket JSONL control surface at ~/.local/share/mermaid/mermaidd.sock. The socket is created mode 0600 and the data dir 0700, so only your user can reach it. A localhost TCP listener on 127.0.0.1:39871 is off by default — enable it with MERMAID_DAEMON_ENABLE_TCP=1. Mutating Unix-socket JSON commands require a pairing token; when TCP is enabled, every command (including health) requires a token. Create one with mermaid pair --label <device> and pass it as MERMAID_DAEMON_TOKEN or auth.token.

The CLI can inspect and manage the same store with mermaid tasks, mermaid task <id>, mermaid approvals, mermaid approve <id>, mermaid deny <id>, mermaid tool-runs, mermaid checkpoints, mermaid restore <id>, mermaid plugin list, mermaid plugin install <path-or-github>, mermaid plugin audit <path>, mermaid models, mermaid model-info <model>, mermaid processes, mermaid logs <process>, mermaid stop <process>, mermaid restart <process>, mermaid open <target>, mermaid ports, mermaid pair, and mermaid daemon. Installing a plugin from a Git URL (rather than a local path) requires an explicit full URL and MERMAID_ALLOW_PLUGIN_FETCH=1, since fetching and later running remote plugin code is a privileged operation.

On Linux, install a per-user systemd unit with mermaid daemon install --start. The installer writes ~/.config/systemd/user/mermaidd.service, points ExecStart at the discovered mermaidd binary, reloads systemd's user manager, and optionally enables/starts the service. Use mermaid daemon status, mermaid daemon logs [-f], mermaid daemon restart, mermaid daemon stop, mermaid daemon uninstall, or mermaid daemon print-unit for day-to-day service management. Set MERMAID_DAEMON_BIN=/absolute/path/to/mermaidd before installing if the background-service binary is not next to mermaid or on PATH.

Release builds keep the existing .tar.gz/.zip archives and add Linux .deb/.rpm artifacts for x86_64 and aarch64. The distro packages install mermaid, mermaidd, docs, and a reference systemd user unit at /usr/lib/systemd/user/mermaidd.service; they do not auto-enable or start the daemon.

Configuration

Config file: ~/.config/mermaid/config.toml (Linux) or platform equivalent via directories crate.

Run mermaid init to create a default config. Important fields in the current config schema:

# Last model picked via `--model` — used by bare `mermaid` on next start
last_used_model = "ollama/qwen3-coder:30b"

[default_model]
provider = "ollama"
name = "qwen3-coder:30b"
temperature = 0.7
max_tokens = 4096
reasoning = "medium"  # none | minimal | low | medium | high | xhigh | max

[ollama]
host = "localhost"
port = 11434
# cloud_api_key = "your-key"  # for :cloud models
# num_gpu = 10
# num_thread = 8
# num_ctx = 8192
# numa = false

[safety]
# Approval policy. Default is "ask": prompt before mutations / shell / network
# actions. "auto" runs an LLM classifier that vets each borderline action
# against your stated intent — aligned actions run automatically, risky ones
# escalate to an approval prompt. "full_access" auto-runs everything (the
# pre-0.8 default); "read_only" blocks all mutations. Change it live with
# Shift+Tab or `/safety <mode>` (session-scoped; this value is the persistent
# default each session starts from).
mode = "ask"
checkpoint_on_mutation = true
# Model the "auto" classifier uses to vet actions. Omit to vet with the
# session's active model; set a smaller/faster model to cut latency and cost.
# auto_classifier_model = "anthropic/claude-haiku-4-5"

[non_interactive]
# Current v0.8 run behavior is controlled by CLI flags:
#   mermaid run "prompt" --format json --max-tokens 4096 --no-execute
# These fields remain in the schema for compatibility but are not the
# source of truth for `mermaid run`.
output_format = "text"
max_tokens = 4096
no_execute = false

# Per-model reasoning preferences (remembered across sessions)
[reasoning_per_model]
"anthropic/claude-opus-4-7" = "high"
"ollama/qwen3-coder:30b" = "low"

# Optional agent/plugin model profiles. A request for `--model fast` or
# `--model profile:fast` resolves through this table when present.
[model_profiles]
fast = "ollama/qwen3-coder:14b"
large-context = "openai/gpt-5"
tool-strong = "anthropic/claude-opus-4-7"
vision = "gemini/gemini-3.1-pro-preview"
cheap = "groq/qwen-qwq-32b"

# Remote providers — override env-var name, base URL, or extra headers
[providers.anthropic]
# api_key_env = "MY_ANTHROPIC_KEY"  # default: ANTHROPIC_API_KEY

[providers.gemini]
# api_key_env = "MY_GOOGLE_KEY"  # default: GOOGLE_API_KEY; GEMINI_API_KEY is accepted as a legacy fallback

[providers.groq]
# api_key_env = "MY_GROQ_KEY"    # default: GROQ_API_KEY
# base_url = "https://api.groq.com/openai/v1"
# extra_headers = { "X-Custom-Header" = "value" }

# Custom OpenAI-compatible provider (e.g., self-hosted vLLM)
[providers.my-vllm]
base_url = "http://192.168.1.42:8000/v1"
api_key_env = "VLLM_KEY"
compat = "openai-effort"   # openai | openai-effort | openrouter
# default_model = "Qwen/Qwen2.5-Coder-32B-Instruct"

# MCP servers — usually managed via `mermaid add <name>`
[mcp_servers.context7]
command = "npx"
args = ["-y", "@upstash/context7-mcp"]

System prompt customization is runtime-only and is not saved to config:

mermaid --append-system-prompt "Prefer minimal diffs"
mermaid --append-system-prompt-file ./extra-instructions.md
mermaid --system-prompt "You are a focused code reviewer."
mermaid --system-prompt-file ./replacement-system-prompt.md

Remote Providers

Set the appropriate environment variable (or override via [providers.<name>].api_key_env in config):

Ollama Cloud models use OLLAMA_API_KEY or cloud_api_key under [ollama]. Web search and web fetch tool registration currently requires OLLAMA_API_KEY in the environment. Use mermaid cloud-setup from your shell to save the config key for cloud models; /cloud-setup in the TUI points back to that shell command.

License

MIT OR Apache-2.0

Built with Ratatui and Ollama. Inspired by Aider and Claude Code.