OpenClaude Model Access and Configuration Options
OpenClaude provides flexible model access through cloud APIs, OpenAI-compatible gateways, and local Ollama servers, allowing users to configure their preferred provider via environment variables and settings files.
Model Access and Configuration
OpenClaude provides flexible model access through cloud APIs, OpenAI-compatible gateways, and local Ollama servers, allowing users to configure their preferred provider via environment variables and settings files. Users can set up cloud inference by defining $env:CLAUDE_CODE_USE_OPENAI="1" and providing an API key and model ID. For local inference, installing Ollama and pulling a coding model is required. Model roles, such as Explore and Plan, can be configured in ~/.openclaude/settings.json. Model-only entries use the currently selected provider credentials. Additionally, OpenClaude includes experimental smart routing, which selects between two configured models for each interaction based on context.
Local and Cloud Model Integration
OpenClaude integrates both local and cloud-based models, offering users flexibility in how they deploy and interact with AI coding tools. By default, OpenClaude requests a 32,768-token Ollama context, which is suitable for complex coding tasks. For local sessions, users can leverage Ollama Web Search when signed in, enhancing the tool's utility for research and development. Installation involves cloning the OpenClaude repository and running a series of commands, as outlined in the project's documentation. One advantage of this approach is that local models, such as those hosted via Ollama or LM Studio, do not require a cloud API key, reducing dependency on external services. However, local coding models do require adequate hardware and reliable tool calling, as noted by the developers. After installation, users can verify the setup by running openclaude --version in a new terminal session.
Agent Skills and Repo Map Features
OpenClaude's agent skills are modular instruction sets stored in reusable folders, each containing a SKILL.md file that defines its purpose and usage. Users can install, show, or verify skills using commands like openclaude skills install gitlawb/ci-fix and openclaude skills verify. For large codebases, the optional Repo Map feature can be enabled with REPO_MAP=1, generating a structural summary accessible via /repomap. This helps developers quickly understand and navigate complex repositories. OpenClaude supports both cloud and local models, with the mini model (gpt-5-mini) used for exploration tasks and the main model (gpt-5) for planning and execution. To build OpenClaude from source, Node.js 22 or later and Bun 1.3.13 or later are required. Additional tools and alternatives are listed in resources such as 10 Best CLI AI Coding Agents in 2026 and The Ultimate Claude Code Resource List 2026.
Sources and reporting notes
Based on published source material. No independent hands-on testing is claimed.
