Agent skill

Setup Ollama Local

Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac.

MITAuto-check: notesAI & LLM Engineering

Install Setup Ollama Local

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/setup-ollama-local .claude/skills/setup-ollama-local && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .claude/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/setup-ollama-local .agents/skills/setup-ollama-local && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .agents/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/setup-ollama-local .cursor/skills/setup-ollama-local && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .cursor/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/receptron/mulmoclaude.git --path .claude/skills/setup-ollama-local

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/setup-ollama-local .gemini/skills/setup-ollama-local && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .gemini/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/setup-ollama-local .github/skills/setup-ollama-local && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .github/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add receptron/mulmoclaude --skill setup-ollama-local -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install receptron/mulmoclaude setup-ollama-local --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/receptron/mulmoclaude.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/setup-ollama-local .opencode/skills/setup-ollama-local && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "setup-ollama-local" agent skill from https://github.com/receptron/mulmoclaude/tree/main/.claude/skills/setup-ollama-local into .opencode/skills/setup-ollama-local/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "setup-ollama-local", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: setup-ollama-local
GitHub stars: 371
Token cost: ~1.9k tokens
SKILL.md length: 785 words
Files: 1
Skills in repo: 17
Repo updated: Oct 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac.

Works in 8 steps: Verify / install Ollama → Verify Claude Code → Choose and pull a model → …
Tasks that involve LLM inference and serving
SKILL.md covers Prerequisites / 前提知識, Step 1: Verify / install Ollama, Step 2: Verify Claude Code and Step 3: Choose and pull a model, plus 7 more sections
Calls ollama, brew and claude; reaches claude.ai; needs ANTHROPIC_API_KEY and ANTHROPIC_AUTH_TOKEN

What it does

Setup Ollama Local is an agent skill from receptron/mulmoclaude. Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac. NOTE — This is for the standalone Claude Code CLI itself, NOT MulmoClaude (MulmoClaude does not currently support Ollama as a backend). Covers Ollama install, model pull, env switching, and verification. Respond in the user's language.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering LLM inference and serving. It works with Ollama and Homebrew. The repository describes itself as: Nurture your own AI assistant on your own computer. Local-first and MIT: memories, data and apps stay as plain files in your workspace. Chat summons the right GUI — wiki… The licence is MIT.

When your agent uses it

Tasks that involve LLM inference and serving

Example prompts

“/setup-ollama-local”

Requirements

Node.js
A credential in ANTHROPIC_AUTH_TOKEN
A credential in ANTHROPIC_API_KEY
Pre-approved tools (allowed-tools): Read, Bash, Glob, Grep

Workflow steps

8 steps, taken from the step headings in SKILL.md.

Verify / install Ollama
Verify Claude Code
Choose and pull a model
Start Ollama with the right context window
Warm up the model
Run Claude Code against Ollama
Switching back to cloud Claude
(optional): Convenience alias

What it can do on your machine

Read from SKILL.md and the folder at commit 3c609e5. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Read
- Bash
- Glob
- Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- ollama
- brew
- claude
- curl
- npm
- sh
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
- claude.ai
Also links to:
- ollama.com
- docs.ollama.com
- code.claude.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- ANTHROPIC_API_KEY
- ANTHROPIC_AUTH_TOKEN
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Setup Ollama Local loads about 1.9k tokens when it runs. Until then it costs about 86 tokens; SKILL.md has 785 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~86
When it runs · the whole SKILL.md, loaded when a task matches: ~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePipes a well-known installer script into a shellSKILL.md:58
```
- `curl -fsSL https://claude.ai/install.sh | sh`
```
NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Read, Bash, Glob, Grep
```

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from receptron/mulmoclaude at commit 3c609e5, republished under its MIT licence (© receptron). 785 words, ~1,933 tokens.

Download SKILL.mdSave it as .claude/skills/setup-ollama-local/SKILL.md (or your agent's skills folder).

name: setup-ollama-local
description: Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac. NOTE — This is for the standalone Claude Code CLI itself, NOT MulmoClaude (MulmoClaude does not currently support Ollama as a backend). Covers Ollama install, model pull, env switching, and verification. Respond in the user's language.
allowed-tools: Read, Bash, Glob, Grep

Setup Claude Code × Ollama (local LLM)

Scope / 適用範囲

This skill sets up the standalone claude CLI to talk to a local Ollama server. It is independent of MulmoClaude; MulmoClaude itself does not currently support Ollama (see plans/feat-mulmoclaude-ollama-support.md for a tentative plan).

このスキルは claude CLI 単体をローカルの Ollama サーバに接続するセットアップです。MulmoClaude とは独立しており、MulmoClaude 本体は現在 Ollama 接続をサポートしていません（実装案は plans/feat-mulmoclaude-ollama-support.md を参照）。

For detailed findings and pitfalls, see docs/tips/claude-code-ollama.md (Japanese) / docs/tips/claude-code-ollama.en.md (English).

Prerequisites / 前提知識

Ollama v0.14.0 or later is required (Anthropic Messages API compatibility was added in that version).
Claude Code sends roughly 50,000–57,000 tokens per request, so the model needs at least a 64k context window.
3B-class small models effectively cannot drive Claude Code (no tool calling, broken templates).
Even on supported models, the first turn often takes 10+ minutes on a MacBook Air; subsequent turns benefit from KV cache and drop to 1–3 minutes.

Step 1: Verify / install Ollama

1-1. Check existing install

bash

which ollama && ollama --version

Installed and v0.14.0+: proceed to 1-2.
Older version: brew upgrade ollama and then brew services restart ollama (Homebrew installs).
Not installed: suggest one of:
- Official installer (recommended): https://ollama.com/download/mac
- Homebrew: brew install ollama

1-2. Verify the server is running

bash

curl -s http://localhost:11434/api/tags | head -c 200

Got JSON back: server is up, go to Step 2.
Empty / connection refused: start it.
- Official app: click the Ollama menu-bar icon.
- Homebrew: brew services start ollama or ollama serve.

Step 2: Verify Claude Code

bash

which claude && claude --version

Installed: continue to Step 3.
Not installed: install via npm (recommended), the official script, or Homebrew:
- npm install -g @anthropic-ai/claude-code
- curl -fsSL https://claude.ai/install.sh | sh
- brew install anthropic/tap/claude-code

Step 3: Choose and pull a model

Confirm the user's RAM and use case before recommending. Verified working models on a MacBook Air M4 32GB are summarized in docs/tips/claude-code-ollama.md. Quick picks:

RAM	Recommended	Size	Notes
8–16GB	(Claude Code × Ollama is impractical here)	—	Cold start exceeds 10 min timeout
32GB	`qwen3.5:9b`	6.6GB	Most practical, lightest fit
32GB	`qwen3.6:35b-a3b`	23GB	MoE (3B active), heavier but works
16–32GB	`gemma4:e4b`	3GB on disk (~10.9 GiB resident)	Verified on 32GB; thinking blocks render correctly
24GB+ (NVIDIA)	`glm-4.7-flash`	19GB	198k context, untested on Mac

Avoid: qwen3:14b (40k training limit), qwen2.5-coder:14b (older runner ignores OLLAMA_CONTEXT_LENGTH), gemma4:26b (Content block parse errors — note: gemma4:e4b is fine), gpt-oss:20b (Ollama template bug). See findings doc for details.

bash

ollama pull <model>
ollama list

Step 4: Start Ollama with the right context window

Claude Code requires ≥64k context. The default is 32k, so always extend it when launching Ollama for Claude Code:

bash

brew services stop ollama   # if running under brew services
OLLAMA_CONTEXT_LENGTH=65536 ollama serve

This terminal must stay open for the duration of the session. For longer sessions add OLLAMA_KEEP_ALIVE=30m so the KV cache survives idle gaps.

Step 5: Warm up the model

In a second terminal, load the model into memory and confirm it responds at all:

bash

ollama run <model> "hello"

Expect a response within a few seconds. If this hangs, the model is unsuitable for Claude Code.

Show full SKILL.md (339 more words)Show less

Step 6: Run Claude Code against Ollama

In a third terminal, set the env vars and launch:

bash

export ANTHROPIC_AUTH_TOKEN="ollama"
export ANTHROPIC_API_KEY=""
export ANTHROPIC_BASE_URL="http://localhost:11434"
claude --verbose --model <model>

Role of each variable:

Variable	Value	Purpose
`ANTHROPIC_AUTH_TOKEN`	`"ollama"`	Enables Ollama mode
`ANTHROPIC_API_KEY`	`""` (empty)	Disables the cloud API key (prevents collision)
`ANTHROPIC_BASE_URL`	`http://localhost:11434`	Routes API calls to the local server

Send a simple message (e.g. "Hello, what model are you?") to confirm. The first turn can take 10+ minutes; subsequent turns drop to 1–3 minutes once the KV cache is warm.

While waiting, watch the Ollama log in another terminal to see what's happening:

bash

tail -f /opt/homebrew/var/log/ollama.log    # Homebrew install
# or just watch the terminal where `ollama serve` is running

Key log signals:

KvSize:65536 ✓ — context is correctly extended
truncating input prompt limit=XXXXX ✗ — model/runner ignores the env var; switch model
POST /v1/messages 200 ✓ — successful turn
POST /v1/messages 500 ✗ — template incompatibility; switch model

Step 7: Switching back to cloud Claude

The local mode is scoped to the terminal where the env vars were set:

Easiest: close that terminal and open a fresh one — back to cloud.

Or unset explicitly:

bash

unset ANTHROPIC_AUTH_TOKEN ANTHROPIC_API_KEY ANTHROPIC_BASE_URL

Step 8 (optional): Convenience alias

If the user wants a one-liner, suggest an alias in ~/.zshrc. Do not put bare export ANTHROPIC_BASE_URL=... lines in a startup file — that breaks normal cloud usage everywhere.

bash

alias claude-local='ANTHROPIC_AUTH_TOKEN="ollama" ANTHROPIC_API_KEY="" ANTHROPIC_BASE_URL="http://localhost:11434" claude'

After source ~/.zshrc, usage is:

bash

claude-local --model qwen3.5:9b   # local
claude                            # cloud, unchanged

Key pitfalls to highlight

Ollama < v0.14.0 has no Anthropic API compatibility — always check the version first.
ANTHROPIC_API_KEY must be explicitly empty; otherwise an existing cloud key may collide.
3B-class models cannot reliably emit Claude's tool-use JSON, so file edits and shell commands fail.
Even tool-capable open models (Gemma 4, gpt-oss) are not fully aligned with Anthropic's response format — complex skill chains misbehave.
Large models (20B+) eat memory; watch with vm_stat or Activity Monitor.
Permanent export ANTHROPIC_BASE_URL=... in .zshrc / .bashrc will silently break normal cloud Claude usage. Use an alias instead.
The first-turn 10-minute Claude Code timeout is unavoidable, but Ollama keeps processing in the background, so a retry usually succeeds via cache reuse.

Reference links

Ollama Claude Code integration: https://docs.ollama.com/integrations/claude-code
Ollama Anthropic compatibility blog: https://ollama.com/blog/claude
Claude Code official docs: https://code.claude.com/docs/en/overview
Local findings: docs/tips/claude-code-ollama.md (ja) / .en.md (en)

Files

Just SKILL.md in .claude/skills/setup-ollama-local of receptron/mulmoclaude.

Open the folder on GitHubat commit 3c609e5

Compare with similar skills

Setup Ollama Local next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Setup Ollama Local compared with similar skills
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Perfupraullenchai/Rapid-MLX	4k	—	~1.6k	Automated safety check: Notes	Custom licence	today
Debug InferenceNVIDIA/OpenShell	16k	—	~1.9k	Automated safety check: Pass	Apache-2.0	today
Ideer Daily Paper ChatbotAI45Lab/iDeer	416	—	~3k	Automated safety check: Notes	AGPL-3.0	2 mo ago
Integrate Modeltryonlabs/opentryon	551	—	~1.1k	Automated safety check: Pass	Custom licence	today

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Questions about Setup Ollama Local

What does Setup Ollama Local do?

Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac. Setup Ollama Local is an agent skill from receptron/mulmoclaude. Interactively guide setup for connecting the Claude Code CLI to a local Ollama LLM on Mac.

When should I use Setup Ollama Local?

Setup Ollama Local fits situations like: tasks that involve LLM inference and serving.

How do I install Setup Ollama Local in Claude Code?

Run `npx skills add receptron/mulmoclaude --skill setup-ollama-local -a claude-code`. Or copy the skill folder (.claude/skills/setup-ollama-local in receptron/mulmoclaude) into .claude/skills/setup-ollama-local in your project. Claude Code loads it when a task matches its description.

How do I install Setup Ollama Local in Codex?

Run `npx skills add receptron/mulmoclaude --skill setup-ollama-local -a codex`. Or copy the skill folder (.claude/skills/setup-ollama-local in receptron/mulmoclaude) into .agents/skills/setup-ollama-local in your project. Codex loads it when a task matches its description.

Can I use Setup Ollama Local in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add receptron/mulmoclaude --skill setup-ollama-local -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/setup-ollama-local, .gemini/skills/setup-ollama-local, .github/skills/setup-ollama-local and .opencode/skills/setup-ollama-local in your project.

What does Setup Ollama Local need to run?

Going by SKILL.md and its folder, Setup Ollama Local needs the command-line tools its instructions call (ollama, brew, claude, curl, npm and sh) and credentials named ANTHROPIC_API_KEY and ANTHROPIC_AUTH_TOKEN. Our summary lists: Node.js; A credential in ANTHROPIC_AUTH_TOKEN; A credential in ANTHROPIC_API_KEY. Its frontmatter pre-approves these tools: Read, Bash, Glob, Grep.

Does Setup Ollama Local access the network?

SKILL.md names 4 domains. In commands or code: claude.ai; the agent is likely to contact it when it follows the instructions. As links in the text: ollama.com, docs.ollama.com and code.claude.com. This is read from the text; nothing was executed.

Is Setup Ollama Local safe to install?

Our automated static check of SKILL.md found notes only (pipes a well-known installer script into a shell; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Setup Ollama Local use?

Setup Ollama Local is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Setup Ollama Local use?

About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Setup Ollama Local?

Skills that share tags, products or a category with Setup Ollama Local: Aider Delegate (amElnagdy/delegate-skills, 2.3k stars), Perfup (raullenchai/Rapid-MLX, 4k stars), Debug Inference (NVIDIA/OpenShell, 16k stars) and Ideer Daily Paper Chatbot (AI45Lab/iDeer, 416 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Setup Ollama Local?

receptron (a GitHub organization) maintains it in receptron/mulmoclaude, which has 371 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 10, 2026.

Source: receptron/mulmoclaude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Setup Ollama Local

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Setup Claude Code × Ollama (local LLM)

Prerequisites / 前提知識

Step 1: Verify / install Ollama

1-1. Check existing install

1-2. Verify the server is running

Step 2: Verify Claude Code

Step 3: Choose and pull a model

Step 4: Start Ollama with the right context window

Step 5: Warm up the model

Step 6: Run Claude Code against Ollama

Step 7: Switching back to cloud Claude

Step 8 (optional): Convenience alias

Key pitfalls to highlight

Reference links

Files

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