Add Pi ACP devcontainer with local-LLM + jupyter-mcp support and E2E test

.devcontainer/pi/Dockerfile

@@ -0,0 +1,66 @@
+# syntax=docker/dockerfile:1.7
+#
+# Pi devcontainer for agent-client-kernel.
+#
+# Installs:
+#   * Node.js 22 (required by pi-acp >= 20 and recommended by pi)
+#   * pi (the coding agent) from @earendil-works/pi-coding-agent
+#   * pi-acp (the ACP adapter) — bridges ACP <-> pi --mode rpc
+#   * pi-mcp-adapter — wires MCP servers (incl. jupyter-mcp-server) through to pi
+#
+# Pi's default config dir (~/.pi/agent) is populated from the project root
+# (.pi/agent/{models,settings,mcp}.json) by COPYing the repo into /home/jovyan,
+# matching the pattern used by the Codex devcontainer.
+
+FROM quay.io/jupyter/minimal-notebook:latest
+
+USER root
+
+# Install Node.js 22 (NodeSource), graphviz (used by example notebooks), git, curl.
+RUN apt-get update && apt-get install -y --no-install-recommends \
+        ca-certificates curl git graphviz gnupg \
+    && curl -fsSL https://deb.nodesource.com/setup_25.x | bash - \
+    && apt-get install -y --no-install-recommends nodejs \
+    && rm -rf /var/lib/apt/lists/*
+
+USER jovyan
+
+# Install pi, pi-acp, and the MCP adapter globally as jovyan.
+# We use NPM_CONFIG_PREFIX=$HOME/.local so npm doesn't try to write to /usr.
+ENV NPM_CONFIG_PREFIX=/home/jovyan/.local
+ENV PATH=/home/jovyan/.local/bin:${PATH}
+
+RUN mkdir -p "$HOME/.local" \
+    && npm install -g \
+        @earendil-works/pi-coding-agent \
+        pi-acp \
+        pi-mcp-adapter \
+    && pi --version \
+    && test -x "$HOME/.local/bin/pi-acp"
+
+# Copy project files into jovyan's home (matches the Codex devcontainer layout).
+# Crucially, this makes .pi/agent/{models,settings,mcp}.json from the repo land
+# at ~/.pi/agent/... so pi picks them up as user-global config.
+# Note: --chown does not expand ENV from the base image, so use literal user:group.
+COPY --chown=jovyan:users . /home/jovyan/
+WORKDIR /home/jovyan
+
+# Install uv and the project (with deps from pyproject.toml) into the
+# conda base environment.
+SHELL ["conda", "run", "-n", "base", "/bin/bash", "-c"]
+
+# graphviz is used by some example notebooks.
+RUN conda install -y -c conda-forge graphviz && conda clean -afy
+
+# `pip install uv` is just bootstrap (the base image has pip but not uv).
+# After that we use `uv pip install -e .`, which resolves dependencies
+# directly from pyproject.toml.
+RUN pip install --upgrade "uv>=0.9.15" \
+    && uv pip install --system -e .
+
+# Register pi-mcp-adapter as a pi extension so the adapter loads on startup.
+# Best-effort: failure here should not break the image build.
+RUN pi install npm:pi-mcp-adapter || true
+
+# Install the kernel for the current user.
+RUN python -m agent_client_kernel install --user

.devcontainer/pi/devcontainer.json

@@ -0,0 +1,73 @@
+{
+  "name": "JupyterLab: Pi ACP",
+  "build": {
+    "dockerfile": "Dockerfile",
+    "context": "../.."
+  },
+  "runArgs": [
+    "--cpus=4",
+    "--memory=10g"
+  ],
+  "forwardPorts": [
+    8888
+  ],
+  "portsAttributes": {
+    "8888": {
+      "label": "JupyterLab",
+      "requireLocalPort": false,
+      "onAutoForward": "openBrowser"
+    }
+  },
+  "remoteEnv": {
+    // Remote LLM provider keys (optional — pi also supports local providers).
+    "ANTHROPIC_API_KEY": "${localEnv:ANTHROPIC_API_KEY}",
+    "OPENAI_API_KEY": "${localEnv:OPENAI_API_KEY}",
+    "GOOGLE_API_KEY": "${localEnv:GOOGLE_API_KEY}",
+    "DEEPSEEK_API_KEY": "${localEnv:DEEPSEEK_API_KEY}",
+    // Local LLM provider hosts. Defaults assume the host machine runs LM Studio
+    // / Ollama on its standard ports; override locally if needed.
+    "LM_STUDIO_BASE_URL": "${localEnv:LM_STUDIO_BASE_URL}",
+    "OLLAMA_HOST": "${localEnv:OLLAMA_HOST}"
+  },
+  "secrets": {
+    "ANTHROPIC_API_KEY": {
+      "description": "Your Anthropic API key (optional — for Claude models in pi).",
+      "documentationUrl": "https://docs.github.com/en/codespaces/managing-your-codespaces/managing-your-account-specific-secrets-for-github-codespaces"
+    },
+    "OPENAI_API_KEY": {
+      "description": "Your OpenAI API key (optional — for OpenAI models in pi).",
+      "documentationUrl": "https://docs.github.com/en/codespaces/managing-your-codespaces/managing-your-account-specific-secrets-for-github-codespaces"
+    },
+    "GOOGLE_API_KEY": {
+      "description": "Your Google API key (optional — for Gemini models in pi).",
+      "documentationUrl": "https://docs.github.com/en/codespaces/managing-your-codespaces/managing-your-account-specific-secrets-for-github-codespaces"
+    },
+    "DEEPSEEK_API_KEY": {
+      "description": "Your DeepSeek API key (optional).",
+      "documentationUrl": "https://docs.github.com/en/codespaces/managing-your-codespaces/managing-your-account-specific-secrets-for-github-codespaces"
+    }
+  },
+  "containerEnv": {
+    "JUPYTER_PORT": "8888",
+    "GRANT_SUDO": "yes",
+    "ACP_AGENT_COMMAND": "/home/jovyan/.local/bin/pi-acp",
+    "ACP_AGENT_ARGS": "",
+    "RESTARTABLE": "false",
+    // pi-acp option: let ACP clients send embedded resource blocks. The
+    // kernel currently doesn't, but enabling this is harmless and matches
+    // the recommended pi-acp setup.
+    "PI_ACP_ENABLE_EMBEDDED_CONTEXT": "true",
+    // pi-mcp-adapter (auto-loaded as a pi extension) opens browser tabs on
+    // the host via $BROWSER / xdg-open for its MCP-UI sessions and OAuth
+    // helpers. In a Codespaces / VS Code remote container, $BROWSER is
+    // wired to a helper that opens a real tab on the user's machine, so
+    // any tool-call retry loop floods the host (and can OOM it). Force a
+    // no-op browser hook here. The explicit forwardPorts/openBrowser
+    // notification for port 8888 is independent of $BROWSER and still
+    // fires once when JupyterLab comes up.
+    "BROWSER": "/bin/true"
+  },
+  // Codespaces ports are private by default so skip the auth token.
+  // Need to disable XSRF check for Jupyter MCP servers if auth token is disabled.
+  "postStartCommand": "nohup start.sh jupyter lab --NotebookApp.token='' --ServerApp.disable_check_xsrf=True > /tmp/jupyter.log 2>&1 &"
+}

.github/workflows/ci.yml

@@ -86,3 +86,41 @@ jobs:
           tags: agent-client-kernel:ci
           cache-from: type=gha
           cache-to: type=gha,mode=max
+
+  pi-acp-e2e:
+    name: Pi ACP end-to-end integration test
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Set up Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: "22"
+
+      - name: Install pi and pi-acp
+        run: |
+          npm install -g \
+            @earendil-works/pi-coding-agent \
+            pi-acp
+          pi --version
+          test -x "$(which pi-acp)"
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: ">=0.9.15"
+          enable-cache: true
+
+      - name: Install project (locked, with dev extras)
+        run: uv sync --locked --extra dev
+
+      - name: Run pi-acp end-to-end tests
+        run: uv run pytest -v tests/e2e/test_pi_acp_integration.py

.pi/agent/mcp.json

@@ -0,0 +1,9 @@
+{
+  "mcpServers": {
+    "jupyter": {
+      "command": "uvx",
+      "args": ["jupyter-mcp-server@latest"],
+      "lifecycle": "lazy"
+    }
+  }
+}

README.md

@@ -41,6 +41,7 @@ This project provides multiple devcontainer configurations for different ACP age
 - `.devcontainer/goose/` - Block's Goose agent (Apache 2.0)
 - `.devcontainer/kimi/` - MoonshotAI's Kimi CLI (Apache 2.0)
 - `.devcontainer/cagent/` - Docker's cagent (Apache 2.0)
+- `.devcontainer/pi/` - Pi coding agent via [pi-acp](https://github.com/svkozak/pi-acp) (MIT). Includes [pi-mcp-adapter](https://github.com/nicobailon/pi-mcp-adapter) and ships with the Datalayer [jupyter-mcp-server](https://github.com/datalayer/jupyter-mcp-server) preconfigured. Supports remote LLM API providers (Anthropic / OpenAI / Google / DeepSeek) and local providers (LM Studio / Ollama) — see `.pi/agent/models.json`.
 
 **To use a devcontainer:**
 1. Open the repository in GitHub Codespaces or VS Code with Dev Containers extension