Aivo

Run familiar coding agents with your choice of hosted or local model through one CLI.

Source repo
yuanchuan/aivo
Stars
★ 193
Last updated
6d ago
License
MIT
Primary language
Rust

At a glance

Works with
Universal · cross-platformCodex · Claude Code
You'll need
Shell / CLINetwork accessLocal filesystemMCP Server
Typical use
A developer who alternates between Claude Code and Codex and wants to launch both from one CLI while choosing a model per task.
Main limitation
Models beyond the starter option generally require users to obtain and configure the relevant provider credentials.

What does this agent do, and when should you use it?

Aivo is a terminal tool that launches coding agents including Claude Code, Codex, Gemini, OpenCode, Pi, and Grok while letting the user select the model and provider. The project also ships Aivo Code, its own terminal coding agent with session tools, skills, and MCP server support. Its model boundary spans hosted APIs, AI gateways, and local GGUF files; the examples include Vercel AI Gateway and a Hugging Face model intended for LM Studio. Aivo keeps API keys in encrypted local storage and provides a consolidated view of sessions, logs, and token usage. It is delivered as a command-line application for macOS, Linux, and Windows rather than a documented graphical development environment.

The user runs aivo in a terminal and selects an agent plus an optional provider or model. Aivo then launches the corresponding Claude Code, Codex, Gemini, OpenCode, Pi, or Grok workflow and routes model access through the selected hosted service, AI gateway, or local GGUF model. For additional providers, aivo keys add collects credentials and Aivo manages them in encrypted local storage. Running aivo code invokes the built-in Aivo Code agent, which can use session tools, skills, and MCP servers. Aivo also brings sessions, logs, and token-usage information into one view.

  1. A developer who alternates between Claude Code and Codex and wants to launch both from one CLI while choosing a model per task.
  2. A team evaluating hosted models or AI gateways without wanting to abandon the entry points of its existing coding agents.
  3. A new user who wants a first trial without provisioning an API key, using the built-in aivo/starter provider.
  4. A developer with a local GGUF model who wants to use it from the terminal through Aivo Code.
  5. A multi-agent user who wants sessions, logs, and token usage collected in a unified view.
  6. A terminal-focused engineer who wants a built-in coding agent with session tools, skills, and MCP server support.

How do you install or deploy this agent?

On macOS or Linux, run curl -fsSL https://getaivo.dev/install.sh | bash. With Homebrew, run brew install yuanchuan/tap/aivo. In Windows PowerShell, run irm https://getaivo.dev/install.ps1 | iex. The supplied material does not state detailed OS-version requirements for the packaged installs; the repository badge lists rustc 1.97+ as its minimum Rust version for source builds.

How do you use this agent?

For a first run without an API key, execute aivo "tell me a short story" or start Claude Code with aivo claude. To access more models, run aivo keys add, supply the relevant provider credential, and then use a command such as aivo claude --model moonshotai/kimi-k2.5. Other documented launch commands are aivo codex, aivo gemini, aivo opencode, aivo pi, and aivo grok. Start the built-in agent with aivo code; documented model examples include aivo code vercel::zai/glm-5.2 for Vercel AI Gateway and aivo code hf:lmstudio-community/Olmo-3-1025-7B-GGUF for a local GGUF model. A one-shot invocation is shown as aivo code -e "今天成都的天气".

What are this agent's strengths and limitations?

Pros
  • One CLI directly covers multiple named coding agents, including Claude Code, Codex, Gemini, OpenCode, Pi, and Grok.
  • Model access spans hosted APIs, AI gateways, and local GGUF files, reducing dependence on one model provider.
  • Aivo Code provides an included terminal agent with skills, session tools, and MCP server support.
  • It combines encrypted local API-key handling with unified session, log, and token-usage visibility.
  • The built-in aivo/starter provider enables a first run without an API key.
Limitations
  • Models beyond the starter option generally require users to obtain and configure the relevant provider credentials.
  • Only terminal workflows are documented; no desktop UI, web UI, or native IDE extension is described.
  • Local GGUF support is stated, but hardware requirements, expected performance, and detailed model compatibility are not documented in the supplied material.
  • There is no evidence showing whether every native agent feature survives a model-provider substitution, so important agent/model combinations require validation.
  • Source builders need to account for the stated rustc 1.97+ minimum.

How does this agent compare with similar options?

Compared with invoking Claude Code, Codex, Gemini, OpenCode, Pi, or Grok separately, Aivo adds a common launcher, model and provider selection, local credential management, and a unified view of sessions, logs, and token usage. Aivo Code is an additional built-in terminal agent that can work with remote or local models. No quality, latency, or cost benchmarks are provided, so the source does not establish that Aivo Code outperforms any of the standalone agents.

Key facts side by side with the most closely related agents.

Agent Source review Stars Updated Language Full support on
Aivo This agent 57 · Major gaps ★ 193 6d ago Rust Codex · Claude Code
zerostack 57 · Major gaps ★ 1.7k today Rust OpenAI API · Claude API
ClawCodex 51 · Major gaps ★ 902 today TypeScript ChatGPT · OpenAI API · Claude API
Supercode 46 · Major gaps ★ 214 4d ago TypeScript Claude API

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
57/ 100 5-point scale 2.9 / 5
Trust 13/29
Reliability 9/14
Adaptability 10/18
Convention 11/18
Effectiveness 9/13
Verifiability 5/8
Why each dimension lost points
Trust13 / 29 · 2.2/5

The supplied manifest shows Linux write confinement, signature verification for self-updates, OS randomness, secret zeroization, and local cryptographic components including AES-GCM and Argon2/PBKDF2, supporting partial credit for least privilege, secret handling, and dependency protection. The README only says keys are encrypted locally; it does not document key lifecycle, log redaction, the exact data sent to providers, or telemetry. Ordinary user-confirmation behavior is also not shown. Because the product launches coding agents capable of file modification without documenting effects, recovery, or undo semantics here, confirmation, transparency, external-effects, and rollback scores are reduced. Authorship, repository metadata, and MIT attribution agree, but fuller publisher and supply-chain attribution is absent.

Reliability9 / 14 · 3.2/5

The README, Cargo metadata, and workflows are broadly consistent about supported agents, the Rust requirement, and product purpose. A scheduled canary checks several upstream CLIs at liveness, tool-call, and protocol-conversion layers and emits layer-specific diagnostics, providing meaningful evidence for routine integration reliability. Full credit is withheld because operation depends on latest npm packages, an external starter service, and providers, while the supplied files do not show comprehensive runtime error messages, retries, recovery, or degradation behavior.

Adaptability10 / 18 · 2.8/5

The terminal coding-agent audience is clear, with examples for hosted APIs, gateways, local GGUF models, multiple agents, and three operating-system families. Triggers are explicit CLI commands, and manifest comments address Termux, proxy-backed networks, and platform-specific filesystem behavior. However, the README does not systematically distinguish agent capabilities, sandbox degradation, supported combinations, or unsupported scenarios; important prerequisites and boundaries are deferred to external documentation. Capability-boundary and environment-fit scores are therefore reduced.

Convention11 / 18 · 3.1/5

The README has a compact, navigable structure covering installation, quick start, the built-in agent, and further documentation. Aivo, the aivo command, and package naming are stable. Installation covers macOS, Linux, Homebrew, and Windows, but remote scripts are piped directly to shells without documented verification, uninstall, or manual-install instructions. Examples are useful but no FAQ is supplied, and limitations appear only incidentally in manifest comments. The complete MIT text and matching metadata justify full license credit. A package version and release badge exist, but no changelog, compatibility policy, support route, or maintenance commitment is included; only the author name is identifiable, while publisher identity remains unknown as stipulated.

Effectiveness9 / 13 · 3.5/5

A unified launcher, model/provider switching, local key management, session visibility, and a built-in terminal agent offer clear utility to the stated audience. The starter provider and local-model path lower initial adoption costs, and examples form directly usable terminal workflows. The files do not quantify improvement over using each CLI directly, performance overhead, provider expense, resource consumption, or output quality, so output usability, marginal value, and cost-benefit are assessed as adequate rather than thorough.

Verifiability5 / 8 · 3.1/5

Core claims can often be mapped across the README, Cargo configuration, and workflows, including supported agents, toolchain requirements, cryptographic components, and integration checks. Workflow comments explain their intent, while sentinel-file and request-path assertions improve traceability. Full credit is withheld because no workflow results, artifact-verification record, independent source, or implementation files are supplied; claims such as binary size, unified log visibility, and key security cannot be fully closed from this evidence alone.

Risks and how to mitigate them
  • Not found in source: rollback or recovery pathBack up first, or work on a git branch or snapshot, so its changes can be undone.
  • Installation pipes network-delivered scripts directly into a shell; pin and inspect the script or use verifiable release artifacts before execution.
  • Coding agents can modify a workspace, while the supplied files do not document default confirmations, undo, or backup behavior; use version control or an isolated directory.
  • The README does not fully disclose which providers receive prompts, source code, logs, and token-usage data or whether telemetry is collected.
  • Cryptographic components are visible, but the supplied evidence does not establish the key-store format, master-key source, unlock policy, log redaction, or migration process.
  • The scheduled canary installs the latest upstream CLIs, which detects drift but introduces variable supply-chain exposure; no pinning or emergency rollback policy is shown.
Evidence confidence: Low Reviewed Sep 17, 2026 Reviewed revision 8a60627f2f99 New commits since this review; the score may not cover them
See the full review method →

FAQ

Do I need an API key for the first run?
No. The built-in aivo/starter provider works on first run. Additional models require the appropriate provider credentials through aivo keys add.
Where are provider credentials stored?
Aivo states that API keys are managed locally with encrypted storage, but the supplied material does not specify the storage path or encryption design.
Can it run a fully local model?
Aivo Code explicitly supports local GGUF models and shows an LM Studio community GGUF example. The source does not state the hardware requirements or every condition needed for offline operation.
Does Aivo replace Claude Code or Codex?
Not necessarily. It can launch those agents as a common front end, while Aivo Code is a separate built-in option. Users can choose between the existing agent workflow and Aivo Code.
What license does the repository use?
It is licensed under MIT.
View on GitHub ↗ Install ↓

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