Open Interpreter

A terminal coding agent for low-cost models, with switchable Rust harnesses plus ACP and Codex exec compatibility.

Stars
★ 69k
Last updated
2d ago
License
Apache-2.0
Primary language
Rust

At a glance

How it runs
CLI
Works with
Universal · cross-platformCodexClaude Code (Partial support)
Cost
Free software; you pay for model usage
Setup effort
Low · running in minutes
You'll need
Shell / CLINetwork accessLocal filesystemMCP Server
Typical use
A developer using lower-cost hosted models for terminal coding can switch models and harnesses from one session.
Not a fit if
  • Users committed to the original Python Open Interpreter
  • Environments that forbid install scripts piping remote shell code

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

Open Interpreter is a Rust-based terminal coding agent positioned to get stronger agent behavior from low-cost models. It is a fork of OpenAI Codex and lets users switch the active harness with /harness, including native, kimi-code, qwen-code, deepseek-tui, and claude-code. The agent runs commands in native sandboxing on macOS, Linux, and Windows, and supports exec, MCP, skills, hooks, permissions, and AGENTS.md. It can serve ACP-compatible editors and clients through interpreter acp, or replace the executable behind an existing Codex SDK integration through codexPathOverride. Product-specific configuration and runtime state live under ~/.openinterpreter, while repository instructions and skills can use AGENTS.md and .agents/skills.

After installation, i or interpreter starts a terminal session. In that session, /model changes the provider and model, while /harness selects a native or emulated harness; the listed harnesses include native, kimi-code, qwen-code, deepseek-tui, claude-code, and minimal. It executes commands in native sandboxing, reads repository AGENTS.md and shared .agents/skills directories, supports MCP, skills, hooks, and permissions, and stores product-only configuration and session state under ~/.openinterpreter. For ACP clients, it launches as interpreter acp. For an application already using the OpenAI Codex SDK, new Codex({ codexPathOverride: "interpreter" }) routes execution to Open Interpreter over the same Codex exec protocol. Its QA skill can test web applications with agent-browser or operate and test native applications with trycua.

  1. A developer using lower-cost hosted models for terminal coding can switch models and harnesses from one session.
  2. A team with an existing OpenAI Codex SDK integration can keep its SDK calls and set codexPathOverride to "interpreter".
  3. A developer using an ACP-compatible editor or client can configure it to launch interpreter acp.
  4. An engineering team testing a web or desktop application can use the included QA skill with agent-browser or trycua.
  5. A team standardizing repository instructions and reusable skills across compatible coding tools can retain AGENTS.md and .agents/skills.

How do you install or deploy this agent?

macOS or Linux: curl -fsSL https://www.openinterpreter.com/install | sh
Windows PowerShell: irm https://www.openinterpreter.com/install.ps1 | iex

Then run i or interpreter to start a session. The supplied material says live model sources for hosted providers require the credentials documented in the provider guides, but it does not specify the exact credential or configuration values.

How do you use this agent?

Run interpreter in a terminal, then use /model to choose a provider and model and /harness to inspect or switch harnesses. To use it as an ACP agent, launch interpreter acp and configure the ACP-compatible client to start that command. In a Codex SDK application, replace new Codex() with new Codex({ codexPathOverride: "interpreter" }). Run scripts/test-codex-sdk-compat.sh for a local compatibility check that does not require a provider.

What are this agent's strengths and limitations?

Pros
  • Includes a Rust implementation of the provider-recommended Kimi Code harness behind a Codex-like interface.
  • Lets one terminal agent switch among several named harness styles instead of fixing the workflow to one interface.
  • Explicitly supports ACP and the Codex exec protocol; an existing Codex SDK integration has a documented one-line executable override.
  • Runs commands in native sandboxing across macOS, Linux, and Windows, with documented web and native-app QA paths.
  • Prefers shared conventions such as AGENTS.md, .agents/skills, and MCP instead of requiring new skills in a product-only directory.
Limitations
  • Live hosted-model sources require provider credentials, but the supplied material does not provide exact authentication configuration.
  • The documented installation paths download and execute a remote shell or PowerShell script, which may conflict with restrictive installation policies.
  • Web and native-app QA respectively use agent-browser and trycua, so those capabilities depend on the relevant tool path.
  • This is a new Rust version distinct from the original Python project, which continues as the community-maintained endolith/open-interpreter fork; existing users need to assess that boundary.

How does this agent compare with similar options?

Compared with OpenAI Codex, this repository identifies itself as a Codex fork focused on emulating high-performing agent harnesses for low-cost models while retaining Codex exec protocol compatibility. The original Python Open Interpreter project continues as the community-maintained endolith/open-interpreter fork; this repository is the newer Rust version.

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

Agent Source review Form / cost Stars Updated Language Full support on
Open Interpreter This agent 45 · Major gaps CLIFree + model costs ★ 69k 2d ago Rust Codex
Grok Build (grok CLI) 40 · Major gaps CLIFree + model costs ★ 28k 1mo ago Rust —
Codync 51 · Major gaps Desktop appFree ★ 1.9k 1d ago Rust ChatGPT · Codex · Claude Code · Claude.ai
fx Coding Agent 63 · Some gaps CLIFree + model costs ★ 3.8k today Zig ChatGPT · Codex · OpenAI API

How does FollowAgents rate this agent?

FollowAgents source review · FARS-2.1
Major gaps
45/ 100 5-point scale 2.3 / 5
This review covers the source as of Aug 09, 2026. The project has shipped 14 stable release(s) since, which have not been re-reviewed. The score and verdict describe the reviewed version only. Recent releases ↓
Trust 8/29
Reliability 6/14
Adaptability 10/18
Convention 9/18
Effectiveness 9/13
Verifiability 3/8
Why each dimension lost points
Trust8 / 29 · 1.4/5

Evidence shows support for native sandboxing (macOS/Linux/Windows), permissions system, hooks, approvals, and shared AGENTS.md and skills directories, indicating mechanisms for least privilege and user confirmation. However, implementation details are not provided, and it is unverified whether sandboxing is enabled by default or permissions are minimal by default. Data flow transparency is partial: README mentions product config and session state stored under ~/.openinterpreter but does not detail data flows. Sensitive data handling is not explicitly addressed. Dependency security: package.json includes version pins and overrides, but no vulnerability scanning or security audit evidence. External effects: supports executing commands and network operations, but default restrictions are unclear. Rollback is not mentioned. Source attribution: project is based on OpenAI Codex, but code provenance and contributors are not clearly stated. Therefore, most criteria scored 1, rollback 0.

Reliability6 / 14 · 2.1/5

Self-consistency: README descriptions align with documentation links, but no code-level verification. Dependency availability: many dependencies, but no lockfile or integrity checks. Failure messages: no examples of error handling or user prompts. Therefore, self-consistency scored 2, others 1.

Adaptability10 / 18 · 2.8/5

Audience and scenarios: README targets developers and end-users, with multiple use cases (ACP, Codex SDK, QA skill). Capability boundaries: clearly lists supported features and limitations (e.g., sandboxing, permissions). Trigger precision: provides commands like /harness and /model, but detailed trigger conditions are not specified. Environment fit: supports macOS, Linux, Windows, with install scripts. Therefore, most scored 2, trigger precision 1.

Convention9 / 18 · 2.5/5

Information architecture: README is well-structured with installation, features, and documentation links. Install notes: provides curl and PowerShell commands. Naming stability: project name and commands are stable, but no version history. Examples and FAQ: multiple documentation links and examples. Known limitations: not explicitly listed. License: Apache-2.0, but copyright notice is OpenAI, which may cause confusion. Versioning/changelog: not provided. Maintenance responsibility: maintainers or contribution guidelines not clearly stated. Therefore, most scored 2, naming stability, known limitations, versioning/changelog, maintenance responsibility 1.

Effectiveness9 / 13 · 3.5/5

Output usability: provides CLI and TUI, supports multiple models and providers. Marginal value: as a fork of Codex, adds harness emulation and ACP support. Cost-benefit: optimized for low-cost models, potentially reducing usage costs. Therefore, all scored 2.

Verifiability3 / 8 · 1.9/5

Claim traceability: claims in README lack specific evidence or test results. Cross-source corroboration: no third-party verification. Fact-inference separation: does not clearly distinguish facts from inferences. Therefore, all scored 1.

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.
  • It is unverified whether sandboxing is enabled by default or permissions are minimal by default.
  • Dependency security lacks evidence of vulnerability scanning or audits.
  • Rollback mechanism is not mentioned, which may affect failure recovery.
  • Copyright notice is OpenAI, but project is a fork; license compliance should be confirmed.
Evidence confidence: Low Reviewed Aug 09, 2026 Reviewed revision 984acc698cd0 New commits since this review; the score may not cover them
See the full review method →

Recent releases

Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.

  1. rust-v0.0.59 Open Interpreter 0.0.59
    Release notes excerpt
    Open Interpreter 0.0.59 Models - No model-provider catalog or request-admission behavior changes are included in this release. App server - Add owner-bound, read-only background-terminal status with bounded terminal metrics and fail-closed thread ownership.
    View on GitHub ↗
  2. rust-v0.0.58 Open Interpreter 0.0.58
    Release notes excerpt
    Open Interpreter 0.0.58 Models - Validate the maintained Codex 0.159.0 compatibility profile for Open Interpreter model discovery and request admission. Feedback - Preserve legacy feedback delivery alongside optional signed attachment uploads, with protocol and streaming-guide coverage.
    View on GitHub ↗
  3. rust-v0.0.57 Open Interpreter 0.0.57
    Release notes excerpt
    Open Interpreter 0.0.57 Models - Validate the maintained Codex 0.159.0 compatibility profile for Open Interpreter model discovery and request admission.
    View on GitHub ↗

FAQ

Is Open Interpreter limited to Kimi K3?
No. The README says /model switches providers and models, and it lists harnesses associated with Kimi, Qwen, and DeepSeek as well as other modes. Hosted live-model sources require the relevant provider credentials.
Can it work with an existing Codex SDK application?
Yes. The documented change is new Codex({ codexPathOverride: "interpreter" }), and the repository states that Open Interpreter speaks the same Codex exec protocol.
Can I use it from an editor?
Yes, with an ACP-compatible editor or client configured to launch interpreter acp.
Are command permissions and sandboxing covered?
The README states that commands run in native sandboxing on macOS, Linux, and Windows and lists permissions support. It links to sandbox and approvals documentation, but the supplied material does not specify the default permission policy.
View on GitHub ↗ Install ↓

Compare agents like this one

The same FARS review applied across the shortlist this agent qualifies for.

Related agents