Use Claude Code with Ollama for local coding help
They configured Claude Code to talk to a local Ollama model and used it on a small Java project inside IntelliJ.
- What they did
- The person installed Claude Code through npm and launched it from IntelliJ’s terminal. They set up Ollama, loaded qwen3.5:9b, and pointed Claude Code at Ollama’s Anthropic-compatible local endpoint with environment variables. As a trial, they asked it to create a Java console task manager and confirmed each step before it moved ahead.
- How it went
- The agent mapped out the work, created the needed files, executed the program, and repaired its own mistakes. The app ran successfully. The author said this local setup is only practical for smaller jobs, and performance depends on the machine.
- Tips
- If you want to try this, begin with a small project and make sure your hardware can handle the model. Ask the agent to show planned commands and edits first, then approve each irreversible action separately.
Try it yourself with Claude Code
I want to run Claude Code against a local Ollama model on my [Mac/Windows/Linux] computer while working in [IntelliJ/my editor]. Show me how to install Ollama, choose a coding model that fits my [RAM/GPU], and configure Claude Code to use Ollama’s local Anthropic-compatible endpoint. After that, test it on a small request in [my project folder], but pause before any file creation, edits, launches, deletions, or submissions and wait for my approval. Before each change, show me the exact command or config update you plan to use.
Fill in the [brackets]. Agents can make mistakes, so review anything before it is sent, paid or deleted.
Get 3 agent uses like this every morning
With the day's top AI news. Free, and one click to unsubscribe.
Related agent uses
Set up layered agent code reviews
A team had Claude Code write most code, then used multiple review layers to catch bugs before merge.
Build a five-step feature pipeline with approval gates
A solo SaaS founder used chained Claude Code commands to turn ideas into shipped features with less token use and faster turnaround.
Review a pull request with staged sub-agents
Use parallel checks and a validation pass to review a branch or PR before you decide what to fix.
Build a lean skill layer from CLI help output
A developer swapped token-heavy Jira and GitLab MCPs for Markdown-based skills generated from the Atlassian and GitLab CLIs.
Add a judge subagent and two review passes
A solo developer used Claude Code to build an app with fresh sessions, a read-only judge, and two review layers for tighter quality control.
Match a pull request to repo style
A developer used Claude Code to bring a pull request in line with a repo’s style, but it only altered comments and left the code unchanged.