add-ollama-tool

name	add-ollama-tool
description	Add Ollama MCP server so the container agent can call local models for cheaper/faster tasks like summarization, translation, or general queries.

Add Ollama Integration

This skill adds a stdio-based MCP server that exposes local Ollama models as tools for the container agent. Claude remains the orchestrator but can offload work to local models.

Tools added:

• ollama_list_models — lists installed Ollama models
• ollama_generate — sends a prompt to a specified model and returns the response

Phase 1: Pre-flight

Check if already applied

Check if agent/runner/src/ollama-mcp-stdio.ts exists. If it does, skip to Phase 3 (Configure).

Check prerequisites

Verify Ollama is installed and running on the host:

ollama list

If Ollama is not installed, direct the user to https://ollama.com/download.

If no models are installed, suggest pulling one:

You need at least one model. I recommend:

ollama pull gemma3:1b    # Small, fast (1GB)
ollama pull llama3.2     # Good general purpose (2GB)
ollama pull qwen3-coder:30b  # Best for code tasks (18GB)

Phase 2: Apply Code Changes

Ensure upstream remote

git remote -v

If upstream is missing, add it:

git remote add upstream https://github.com/sbusso/claudeclaw.git

Merge the skill branch

git fetch upstream skill/ollama-tool
git merge upstream/skill/ollama-tool

This merges in:

• agent/runner/src/ollama-mcp-stdio.ts (Ollama MCP server)
• scripts/ollama-watch.sh (macOS notification watcher)
• Ollama MCP config in agent/runner/src/index.ts (allowedTools + mcpServers)
• [OLLAMA] log surfacing in src/orchestrator/container-runner.ts
• OLLAMA_HOST in .env.example

If the merge reports conflicts, resolve them by reading the conflicted files and understanding the intent of both sides.

Copy to per-group agent-runner

Existing groups have a cached copy of the agent-runner source. Copy the new files:

for dir in data/sessions/*/agent-runner-src; do
  cp agent/runner/src/ollama-mcp-stdio.ts "$dir/"
  cp agent/runner/src/index.ts "$dir/"
done

Validate code changes

npm run build
./src/runtimes/docker/build.sh

Build must be clean before proceeding.

Phase 3: Configure

Set Ollama host (optional)

By default, the MCP server connects to http://host.docker.internal:11434 (Docker Desktop) with a fallback to localhost. To use a custom Ollama host, add to .env:

OLLAMA_HOST=http://your-ollama-host:11434

Service name: Derived from the directory name: com.claudeclaw.<dirname> (macOS) / claudeclaw-<dirname> (Linux). For example, if cwd is my-assistant, the service is com.claudeclaw.my-assistant. Determine the correct service name before running service commands below.

Restart the service

launchctl kickstart -k gui/$(id -u)/com.claudeclaw  # macOS
# Linux: systemctl --user restart claudeclaw

Phase 4: Verify

Test via WhatsApp

Tell the user:

Send a message like: "use ollama to tell me the capital of France"

The agent should use ollama_list_models to find available models, then ollama_generate to get a response.

Monitor activity (optional)

Run the watcher script for macOS notifications when Ollama is used:

./scripts/ollama-watch.sh

Check logs if needed

tail -f logs/claudeclaw.log | grep -i ollama

Look for:

• Agent output: ... Ollama ... — agent used Ollama successfully
• [OLLAMA] >>> Generating — generation started (if log surfacing works)
• [OLLAMA] <<< Done — generation completed

Troubleshooting

Agent says "Ollama is not installed"

The agent is trying to run ollama CLI inside the container instead of using the MCP tools. This means:

1. The MCP server wasn't registered — check agent/runner/src/index.ts has the ollama entry in mcpServers
2. The per-group source wasn't updated — re-copy files (see Phase 2)
3. The container wasn't rebuilt — run ./src/runtimes/docker/build.sh

"Failed to connect to Ollama"

1. Verify Ollama is running: ollama list
2. Check Docker can reach the host: docker run --rm curlimages/curl curl -s http://host.docker.internal:11434/api/tags
3. If using a custom host, check OLLAMA_HOST in .env

Agent doesn't use Ollama tools

The agent may not know about the tools. Try being explicit: "use the ollama_generate tool with gemma3:1b to answer: ..."