diff --git a/.devcontainer/ollama/Dockerfile b/.devcontainer/ollama/Dockerfile
new file mode 100644
index 0000000..487550e
--- /dev/null
+++ b/.devcontainer/ollama/Dockerfile
@@ -0,0 +1,2 @@
+FROM mcr.microsoft.com/devcontainers/python:3-3.13-bookworm
+RUN apt-get update && apt-get install -y --no-install-recommends zstd && rm -rf /var/lib/apt/lists/*
diff --git a/.devcontainer/ollama/devcontainer.json b/.devcontainer/ollama/devcontainer.json
new file mode 100644
index 0000000..22ac1a9
--- /dev/null
+++ b/.devcontainer/ollama/devcontainer.json
@@ -0,0 +1,46 @@
+{
+  "name": "Python MCP Demos (Ollama)",
+  "build": {
+    "dockerfile": "Dockerfile"
+  },
+  "features": {
+    "ghcr.io/va-h/devcontainers-features/uv:1": {},
+    "ghcr.io/devcontainers/features/node:1": { "version": "lts" },
+    "ghcr.io/devcontainers/features/docker-in-docker:2": {},
+    "ghcr.io/azure/azure-dev/azd:latest": {},
+    "ghcr.io/prulloac/devcontainer-features/ollama:1": {
+      "pull": "qwen3.5:9b"
+    }
+  },
+  "postCreateCommand": "uv sync && cp .env.sample.ollama .env",
+  "forwardPorts": [6277, 6274],
+  "portsAttributes": {
+    "6277": {
+      "label": "MCP Proxy Server",
+      "visibility": "public",
+      "onAutoForward": "silent"
+    },
+    "6274": {
+      "label": "MCP Inspector UI",
+      "visibility": "public"
+    }
+  },
+  "customizations": {
+    "vscode": {
+      "extensions": [
+        "ms-python.python",
+        "ms-python.vscode-pylance",
+        "github.copilot",
+        "github.copilot-chat"
+      ],
+      "settings": {
+        "python.defaultInterpreterPath": "${workspaceFolder}/.venv/bin/python",
+        "chat.mcp.autostart": "never"
+      }
+    }
+  },
+  "hostRequirements": {
+    "memory": "64gb"
+  },
+  "remoteUser": "vscode"
+}
diff --git a/.env.sample.ollama b/.env.sample.ollama
new file mode 100644
index 0000000..341ef4f
--- /dev/null
+++ b/.env.sample.ollama
@@ -0,0 +1,14 @@
+# API Host Selection
+API_HOST=ollama
+
+# Ollama Configuration
+OLLAMA_MODEL=qwen3.5:9b
+OLLAMA_ENDPOINT=http://localhost:11434/v1
+OLLAMA_API_KEY=no-key-needed
+
+# GitHub MCP Configuration (for Langchain+GitHub example)
+GITHUB_TOKEN=your_github_token_here
+
+# OpenTelemetry Configuration (for Aspire Dashboard)
+# Uncomment to enable tracing, metrics, and logs export
+# OTEL_EXPORTER_OTLP_ENDPOINT=http://localhost:4317
diff --git a/README.md b/README.md
index a27f936..de2971a 100644
--- a/README.md
+++ b/README.md
@@ -26,9 +26,17 @@ You have a few options for setting up this project. The quickest way to get star
 
 ### GitHub Codespaces
 
-You can run this project virtually by using GitHub Codespaces. Click the button to open a web-based VS Code instance in your browser:
+You can run this project virtually by using GitHub Codespaces. Click one of the buttons below to open a web-based VS Code instance in your browser:
 
-[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/pamelafox/python-mcp-demo)
+**Default (Azure OpenAI):**
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/Azure-Samples/python-mcp-demos)
+
+**Ollama (local models, requires 64GB+ memory):**
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/Azure-Samples/python-mcp-demos?devcontainer_path=.devcontainer/ollama/devcontainer.json)
+
+The Ollama Codespace pre-installs Ollama and pulls the `qwen3.5:9b` model, and copies `.env.sample.ollama` as your `.env` file. Note that the 64GB memory requirement will consume your Codespace quota faster.
 
 Once the Codespace is open, open a terminal window and continue with the deployment steps.
 
@@ -37,7 +45,7 @@ Once the Codespace is open, open a terminal window and continue with the deploym
 A related option is VS Code Dev Containers, which will open the project in your local VS Code using the [Dev Containers extension](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers):
 
 1. Start Docker Desktop (install it if not already installed)
-2. Open the project: [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/pamelafox/python-mcp-demo)
+2. Open the project: [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/Azure-Samples/python-mcp-demos)
 3. In the VS Code window that opens, once the project files show up (this may take several minutes), open a terminal window.
 4. Continue with the deployment steps.
 
diff --git a/spanish/README.md b/spanish/README.md
index 33fcf3a..bfee1ca 100644
--- a/spanish/README.md
+++ b/spanish/README.md
@@ -25,9 +25,17 @@ Hay varias opciones para configurar este proyecto. La forma más rápida es GitH
 
 ### GitHub Codespaces
 
-Puedes ejecutar este proyecto de forma virtual usando GitHub Codespaces. Haz clic en el botón para abrir una instancia web de VS Code en tu navegador:
+Puedes ejecutar este proyecto de forma virtual usando GitHub Codespaces. Haz clic en uno de los botones para abrir una instancia web de VS Code en tu navegador:
 
-[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/pamelafox/python-mcp-demo)
+**Predeterminado (Azure OpenAI):**
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/Azure-Samples/python-mcp-demos)
+
+**Ollama (modelos locales, requiere 64GB+ de memoria):**
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/Azure-Samples/python-mcp-demos?devcontainer_path=.devcontainer/ollama/devcontainer.json)
+
+El Codespace de Ollama pre-instala Ollama y descarga el modelo `qwen3.5:9b`, y copia `.env.sample.ollama` como tu archivo `.env`. Ten en cuenta que el requisito de 64GB de memoria consumirá tu cuota de Codespace más rápido.
 
 Una vez abierto el Codespace, abre una terminal y continúa con los pasos de despliegue.
 
@@ -36,7 +44,7 @@ Una vez abierto el Codespace, abre una terminal y continúa con los pasos de des
 Otra opción relacionada es VS Code Dev Containers, que abre el proyecto en tu VS Code local usando la extensión [Dev Containers](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers):
 
 1. Inicia Docker Desktop (instálalo si todavía no lo tienes)
-2. Abre el proyecto: [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/pamelafox/python-mcp-demo)
+2. Abre el proyecto: [![Open in Dev Containers](https://img.shields.io/static/v1?style=for-the-badge&label=Dev%20Containers&message=Open&color=blue&logo=visualstudiocode)](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/Azure-Samples/python-mcp-demos)
 3. En la ventana de VS Code que se abre, cuando aparezcan los archivos (puede tardar varios minutos), abre una terminal.
 4. Continúa con los pasos de despliegue.