298c3eade4
* feat: add /add-ollama skill for local model inference Adds a skill that integrates Ollama as an MCP server, allowing the container agent to offload tasks to local models (summarization, translation, general queries) while keeping Claude as orchestrator. Skill contents: - ollama-mcp-stdio.ts: stdio MCP server with ollama_list_models and ollama_generate tools - ollama-watch.sh: macOS notification watcher for Ollama activity - Modifications to index.ts (MCP config) and container-runner.ts (log surfacing) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: rename skill from /add-ollama to /add-ollama-tool Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: gavrielc <gabicohen22@yahoo.com>
153 lines
4.4 KiB
Markdown
153 lines
4.4 KiB
Markdown
---
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name: add-ollama-tool
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description: Add Ollama MCP server so the container agent can call local models for cheaper/faster tasks like summarization, translation, or general queries.
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---
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# Add Ollama Integration
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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.
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Tools added:
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- `ollama_list_models` — lists installed Ollama models
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- `ollama_generate` — sends a prompt to a specified model and returns the response
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## Phase 1: Pre-flight
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### Check if already applied
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Read `.nanoclaw/state.yaml`. If `ollama` is in `applied_skills`, skip to Phase 3 (Configure). The code changes are already in place.
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### Check prerequisites
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Verify Ollama is installed and running on the host:
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```bash
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ollama list
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```
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If Ollama is not installed, direct the user to https://ollama.com/download.
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If no models are installed, suggest pulling one:
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> You need at least one model. I recommend:
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>
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> ```bash
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> ollama pull gemma3:1b # Small, fast (1GB)
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> ollama pull llama3.2 # Good general purpose (2GB)
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> ollama pull qwen3-coder:30b # Best for code tasks (18GB)
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> ```
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## Phase 2: Apply Code Changes
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Run the skills engine to apply this skill's code package.
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### Initialize skills system (if needed)
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If `.nanoclaw/` directory doesn't exist yet:
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```bash
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npx tsx scripts/apply-skill.ts --init
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```
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### Apply the skill
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```bash
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npx tsx scripts/apply-skill.ts .claude/skills/add-ollama-tool
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```
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This deterministically:
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- Adds `container/agent-runner/src/ollama-mcp-stdio.ts` (Ollama MCP server)
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- Adds `scripts/ollama-watch.sh` (macOS notification watcher)
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- Three-way merges Ollama MCP config into `container/agent-runner/src/index.ts` (allowedTools + mcpServers)
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- Three-way merges `[OLLAMA]` log surfacing into `src/container-runner.ts`
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- Records the application in `.nanoclaw/state.yaml`
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If the apply reports merge conflicts, read the intent files:
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- `modify/container/agent-runner/src/index.ts.intent.md` — what changed and invariants
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- `modify/src/container-runner.ts.intent.md` — what changed and invariants
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### Copy to per-group agent-runner
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Existing groups have a cached copy of the agent-runner source. Copy the new files:
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```bash
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for dir in data/sessions/*/agent-runner-src; do
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cp container/agent-runner/src/ollama-mcp-stdio.ts "$dir/"
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cp container/agent-runner/src/index.ts "$dir/"
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done
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```
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### Validate code changes
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```bash
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npm run build
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./container/build.sh
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```
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Build must be clean before proceeding.
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## Phase 3: Configure
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### Set Ollama host (optional)
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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`:
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```bash
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OLLAMA_HOST=http://your-ollama-host:11434
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```
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### Restart the service
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```bash
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launchctl kickstart -k gui/$(id -u)/com.nanoclaw # macOS
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# Linux: systemctl --user restart nanoclaw
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```
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## Phase 4: Verify
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### Test via WhatsApp
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Tell the user:
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> Send a message like: "use ollama to tell me the capital of France"
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>
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> The agent should use `ollama_list_models` to find available models, then `ollama_generate` to get a response.
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### Monitor activity (optional)
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Run the watcher script for macOS notifications when Ollama is used:
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```bash
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./scripts/ollama-watch.sh
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```
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### Check logs if needed
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```bash
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tail -f logs/nanoclaw.log | grep -i ollama
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```
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Look for:
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- `Agent output: ... Ollama ...` — agent used Ollama successfully
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- `[OLLAMA] >>> Generating` — generation started (if log surfacing works)
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- `[OLLAMA] <<< Done` — generation completed
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## Troubleshooting
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### Agent says "Ollama is not installed"
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The agent is trying to run `ollama` CLI inside the container instead of using the MCP tools. This means:
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1. The MCP server wasn't registered — check `container/agent-runner/src/index.ts` has the `ollama` entry in `mcpServers`
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2. The per-group source wasn't updated — re-copy files (see Phase 2)
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3. The container wasn't rebuilt — run `./container/build.sh`
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### "Failed to connect to Ollama"
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1. Verify Ollama is running: `ollama list`
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2. Check Docker can reach the host: `docker run --rm curlimages/curl curl -s http://host.docker.internal:11434/api/tags`
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3. If using a custom host, check `OLLAMA_HOST` in `.env`
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### Agent doesn't use Ollama tools
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The agent may not know about the tools. Try being explicit: "use the ollama_generate tool with gemma3:1b to answer: ..."
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