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add-ollama-tool
Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
Use Codex (CLI + AppServer) as the full agent provider — planning, tool orchestration, native compaction, MCP tools, session resume — in place of the Claude Agent SDK. ChatGPT subscription or OPENAI_API_KEY. Per-group via agent_provider. Distinct from using OpenAI as an MCP tool (where Claude remains the planner).
Super-easy FamilyClaw family setup — base install (Telegram + native credential proxy) then auto-create a shared-memory family agent with an invite link for the rest of the household. Triggers on "set up family", "family setup", "setup familyclaw for my family".
Efficiently bring upstream FamilyClaw updates into a customized install, with preview, selective cherry-pick, and low token usage.
Add Atomic Chat MCP server so the container agent can call local models served by the Atomic Chat desktop app via its OpenAI-compatible API.
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Add DeltaChat channel integration via @deltachat/stdio-rpc-server. Native adapter — no Chat SDK bridge. Email-based messaging with end-to-end encryption.
| name | add-ollama-tool |
| description | Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library. |
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, and can optionally manage the model library directly.
Core tools (always available):
ollama_list_models — list installed Ollama models with name, size, and familyollama_generate — send a prompt to a specified model and return the responseManagement tools (opt-in via OLLAMA_ADMIN_TOOLS=true):
ollama_pull_model — pull (download) a model from the Ollama registryollama_delete_model — delete a locally installed model to free disk spaceollama_show_model — show model details: modelfile, parameters, and architecture infoollama_list_running — list models currently loaded in memory with memory usage and processor typeCheck if container/agent-runner/src/ollama-mcp-stdio.ts exists. If it does, skip to Phase 3 (Configure).
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)
git remote -v
If upstream is missing, add it:
git remote add upstream https://github.com/w95/familyclaw.git
git fetch upstream skill/ollama-tool
git merge upstream/skill/ollama-tool
This merges in:
container/agent-runner/src/ollama-mcp-stdio.ts (Ollama MCP server)scripts/ollama-watch.sh (macOS notification watcher)container/agent-runner/src/index.ts (allowedTools + mcpServers)[OLLAMA] log surfacing in src/container-runner.tsOLLAMA_HOST in .env.exampleIf the merge reports conflicts, resolve them by reading the conflicted files and understanding the intent of both sides.
pnpm run build
./container/build.sh
Build must be clean before proceeding.
Ask the user:
Would you like the agent to be able to manage Ollama models (pull, delete, inspect, list running)?
- Yes — adds tools to pull new models, delete old ones, show model info, and check what's loaded in memory
- No — the agent can only list installed models and generate responses (you manage models yourself on the host)
If the user wants management tools, add to .env:
OLLAMA_ADMIN_TOOLS=true
If they decline (or don't answer), do not add the variable — management tools will be disabled by default.
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
Run from your FamilyClaw project root:
source setup/lib/install-slug.sh
launchctl kickstart -k gui/$(id -u)/$(launchd_label) # macOS
systemctl --user restart $(systemd_unit) # Linux
Tell the user:
Send a message like: "use ollama to tell me the capital of France"
The agent should use
ollama_list_modelsto find available models, thenollama_generateto get a response.
If OLLAMA_ADMIN_TOOLS=true was set, tell the user:
Send a message like: "pull the gemma3:1b model" or "which ollama models are currently loaded in memory?"
The agent should call
ollama_pull_modelorollama_list_runningrespectively.
Run the watcher script for macOS notifications when Ollama is used:
./scripts/ollama-watch.sh
tail -f logs/familyclaw.log | grep -i ollama
Look for:
[OLLAMA] >>> Generating — generation started[OLLAMA] <<< Done — generation completed[OLLAMA] Pulling model: — pull in progress (management tools)[OLLAMA] Deleted: — model removed (management tools)The agent is trying to run ollama CLI inside the container instead of using the MCP tools. This means:
container/agent-runner/src/index.ts has the ollama entry in mcpServers./container/build.shollama listdocker run --rm curlimages/curl curl -s http://host.docker.internal:11434/api/tagsOLLAMA_HOST in .envThe agent may not know about the tools. Try being explicit: "use the ollama_generate tool with gemma3:1b to answer: ..."
ollama_pull_model times out on large modelsLarge models (7B+) can take several minutes. The tool uses stream: false so it blocks until complete — this is intentional. For very large pulls, use the host CLI directly: ollama pull <model>
Ensure OLLAMA_ADMIN_TOOLS=true is set in .env and the service was restarted after adding it.