Update README and docs (including logo) (#122)

* Update README (and add logo)
* Configure MKDocs site to use favicon and additional custom CSS
* Added docs/assets folder for images, CSS etc.

Author: peteski22

.gitignore

@@ -50,3 +50,6 @@ docs/commands/
 .venv/
 # Added by goreleaser init:
 dist/
+
+# Image thumbnails
+.DS_Store

README.md

@@ -1,100 +1,196 @@
-# mcpd
+# <img src="docs/assets/mcpd-logo.png" alt="mcpd" width="300"/>
+
+> **Run your agents, not your infrastructure.**
 
 **mcpd** is a tool to declaratively manage [Model Context Protocol](https://modelcontextprotocol.io/overview) (MCP) servers, providing a consistent interface to define and run tools across environments, from local development to containerized cloud deployments.
 
+Built by [Mozilla AI](https://mozilla.ai)
+
+---
+
 Today, `mcpd` launches MCP servers as subprocesses using STDIO (Standard Input/Output) and acts as an HTTP proxy between agents and the tools they expose. This enables agent-compatible workflows with support for secrets, runtime arguments, and reproducible configurations, no matter where `mcpd` is running.
 
 We're developing a Kubernetes operator, guided by our internal roadmap, to extend `mcpd` for deploying and managing MCP servers as long-lived services in production. It will use the same `.mcpd.toml` configuration and proxy model, making it easier to scale and manage lifecycles without changing the developer experience.
 
-> Built by [Mozilla AI](https://mozilla.ai)
 
-## 🚀 Features
+## The Problem
 
-- Declarative `.mcpd.toml` to define servers/tools
-- Run and manage language-agnostic MCP servers via a single CLI
-- Secure execution context for secrets and runtime args
-- Smooth dev-to-prod transition via the `mcpd` daemon
-- Rich CLI and SDK tooling, see supported languages below:
+ML teams build agents that work perfectly locally. Operations teams get handed Python scripts and told "make this production-ready across dev/UAT/prod." 
+The gap between local development and enterprise deployment kills AI initiatives.
+
+`mcpd` solves this with declarative configuration, secure secrets management, and seamless environment promotion - all while keeping the developer experience simple.
 
 
-| Language   | Repository                                                       | Status             |
-|------------|------------------------------------------------------------------|--------------------|
-| Python     | [mcpd-sdk-python](https://github.com/mozilla-ai/mcpd-sdk-python) | :white_check_mark: |
-| JavaScript | _Coming soon_                                                    | :yellow_circle:    |
+## Why mcpd?
 
-## 📖 Documentation
+**Zero-Config Tool Setup**  
+No cloning repos or installing language-specific dependencies. `mcpd add` and `mcpd daemon` handle everything.
 
-Full documentation available at:
+**Language-Agnostic Tooling**  
+Use MCP servers written in Python, JavaScript, TypeScript via a unified HTTP API.
 
-👉 **[https://mozilla-ai.github.io/mcpd/](https://mozilla-ai.github.io/mcpd/)**
+**Declarative Configuration**  
+Version-controlled `.mcpd.toml` files define your agent infrastructure. Reproducible, auditable, CI-friendly.
 
-Covers setup, CLI usage, configuration, secrets, the daemon, Makefile commands, and full tutorials.
+**Enterprise-Ready Secrets**  
+Separate project configuration from runtime variables, and export sanitized secrets templates. Never commit secrets to Git again.
 
-Explore the Python SDK, with a list of examples using it with different agent frameworks, at:
+**Seamless Local-to-Prod**  
+Same configuration works in development, CI, and cloud environments without modification.
+
+
+## Built for Dev & Production
+
+| Development Workflow                                                              | Production Benefit                                         |
+|-----------------------------------------------------------------------------------|------------------------------------------------------------|
+| `mcpd daemon` runs everything locally                                             | Same daemon runs in containers                             |
+| `.mcpd.toml` version-controlled configs                                           | Declarative infrastructure as code                         |
+| Local secrets in `~/.config/mcpd/`                                                | Secure secrets injection via control plane                 |
+| `mcpd config export` exports version-control safe snapshot of local configuration | Sanitized secrets config and templates for CI/CD pipelines |
+
+## Features
+
+- Focus on Developer Experience via `mcpd` CLI
+- Declarative configuration (`.mcpd.toml`) to define required servers/tools
+- Run and manage language-agnostic MCP servers
+- Secure execution context for secrets and runtime args
+- Smooth dev-to-prod transition via the `mcpd` daemon
+- Rich CLI and SDK tooling, see supported languages below:
 
-👉 **[https://github.com/mozilla-ai/mcpd-sdk-python](https://github.com/mozilla-ai/mcpd-sdk-python)**
 
-## ⚙️ Quickstart
+## 🚀 Quick Start
 
-Install dependencies:
+### Prerequisites
 
-- [Go](https://go.dev/doc/install)
+- [Go](https://go.dev/doc/install) (only required for development of `mcpd`)
 - [npx](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm)
 - [uvx](https://docs.astral.sh/uv/getting-started/installation/)
 
-Clone the repo:
+### Installation
+
+#### via Homebrew
+
+Add the Mozilla.ai tap:
+
 ```bash
-git clone [email protected]:mozilla-ai/mcpd.git
-cd mcpd
+brew tap mozilla-ai/tap
 ```
 
-Build the binary:
+Then install `mcpd`:
+
 ```bash
-make build
-```
+brew install mcpd
+````
+
+Or install directly from the cask:
 
-Install globally:
 ```bash
-sudo make install
+brew install --cask mozilla-ai/tap/mcpd
 ```
 
-In your agentic application code...
+#### via GitHub releases
+
+Official releases can be found on [mcpd's GitHub releases page](https://github.com/mozilla-ai/mcpd/releases).
+
+The following is an example of manually downloading and installing `mcpd` using `curl` and `jq` by running `install_mcpd`:
 
-Initialize a new project:
 ```bash
-mcpd init
+function install_mcpd() {
+    command -v curl >/dev/null || { echo "curl not found"; return 1; }
+    command -v jq >/dev/null || { echo "jq not found"; return 1; }
+
+    latest_version=$(curl -s https://api.github.com/repos/mozilla-ai/mcpd/releases/latest | jq -r .tag_name)
+    os=$(uname)
+    arch=$(uname -m)
+
+    zip_name="mcpd_${os}_${arch}.tar.gz"
+    url="https://github.com/mozilla-ai/mcpd/releases/download/${latest_version}/${zip_name}"
+
+    echo "Downloading: $url"
+    curl -sSL "$url" -o "$zip_name" || { echo "Download failed"; return 1; }
+
+    echo "Extracting: $zip_name"
+    tar -xzf "$zip_name" mcpd || { echo "Extraction failed"; return 1; }
+
+    echo "Installing to /usr/local/bin"
+    sudo mv mcpd /usr/local/bin/mcpd && sudo chmod +x /usr/local/bin/mcpd || { echo "Install failed"; return 1; }
+
+    rm -f "$zip_name"
+    echo "mcpd installed successfully"
+}
 ```
 
-Add a server (e.g. `time`):
+#### via local Go binary build
+
 ```bash
-mcpd add time
+# Clone and build
+git clone [email protected]:mozilla-ai/mcpd.git
+cd mcpd
+make build
+sudo make install # Install mcpd 'globally' to /usr/local/bin
 ```
 
-Start the daemon:
+### Using mcpd
+
 ```bash
-mcpd daemon
+# Initialize a new project
+mcpd init
+
+# Add an MCP server
+mcpd add time
+
+# Set the local timezone for the MCP server
+mcpd config args set time -- --local-timezone=Europe/London
+
+# Start the daemon in dev mode with debug logging
+mcpd daemon --dev --log-level=DEBUG --log-path=$(pwd)/mcpd.log
+
+# You can tail the log file
+tail -f mcpd.log
 ```
 
-API docs will be available at `/docs`, e.g. `http://localhost:8090/docs` 
+API docs will be available at [http://localhost:8090/docs](http://localhost:8090/docs).
 
-## 🧰 Development
 
-Run tests:
+## Deploy Anywhere
+
+`mcpd` is runtime-flexible and infrastructure-agnostic:
+
+- ⚙️ Works in any container or host with `uv` and `npx`
+- ☁️ Multi-cloud ready (AWS, GCP, Azure, on-prem)
+- ♻️ Low resource overhead via efficient server management
+
+
+## 📚 Documentation & SDKs
+
+**Full documentation:** [https://mozilla-ai.github.io/mcpd/](https://mozilla-ai.github.io/mcpd/)
+
+**SDKs available:**
+
+| Language   | Repository                                                       | Status |
+|------------|------------------------------------------------------------------|--------|
+| Python     | [mcpd-sdk-python](https://github.com/mozilla-ai/mcpd-sdk-python) | ✅      |
+| JavaScript | _Coming soon_                                                    | 🟡     |
+
+
+## 💻 Development
+
+Build local code:
 ```bash
-make test
+make build
 ```
 
-Run the local documentation site (requires `uv`):
+Run tests:
 ```bash
-make docs-local
+make test
 ```
 
-Generate CLI documentation and related docs site navigation:
+Run the local documentation site (requires `uv`), dynamically generates command line documentation:
 ```bash
-make docs-cli
-make docs-nav
+make docs
 ```
 
+
 ---
 
 ## 🤝 Contributing

docs/assets/custom.css

@@ -0,0 +1,8 @@
+span.logo-text {
+    display: none;
+}
+
+img.logo-image {
+    width: 300px;
+    height: auto;
+}

docs/assets/mcpd-logo.png

@@ -1,48 +1,49 @@
-# mcpd
+# <span class="logo-text">mcpd</span> ![mcpd](assets/mcpd-logo.png){: .logo-image}
 
 > *Run your agents, not your infrastructure.*
 
 ---
 
 `mcpd` is a toolchain and runtime developed by [Mozilla AI](https://mozilla.ai) that simplifies the configuration, 
-execution and integration of Model Context Protocol (MCP) servers with your agentic application.
-It is intended to provide the same experience across local development and production environments.
+execution and integration of [Model Context Protocol](https://modelcontextprotocol.io/overview) (MCP) servers with your agentic application.
+It is intended to provide the same experience across local, development and production environments.
 
 It removes the friction of cross-language server orchestration, secrets management, version pinning, and lifecycle control.
 
 ---
 
-## ✨ Why `mcpd`?
+## Why `mcpd`?
 
 Traditional agent frameworks often embed complex subprocess logic, brittle startup scripts, and ad-hoc 'desktop style' config. 
 
 `mcpd` replaces this with:
 
-🧪 **Zero-Config Tool Setup**  
+**Zero-Config Tool Setup**  
   No cloning repos or installing language-specific dependencies. `mcpd add` and `mcpd daemon` handle everything.
 
-🌍 **Language-Agnostic Tooling**  
+**Language-Agnostic Tooling**  
   Use MCP servers written in Python (`uvx`), JavaScript/TypeScript (`npx`) in your code via a HTTP REST API that supports routing to MCP Servers.
 
-🧭 **Declarative Tool Management**  
+**Declarative Tool Management**  
   Define version-pinned MCP servers and tools in `.mcpd.toml`. Reproducible, consistent, and CI-friendly.
 
-🔐 **Project config separated from runtime variables**  
-  Args and environment variables per server e.g. `~/.config/mcpd/secrets.dev.toml`. Never commit dev specific vars to Git again.
+**Project config separated from runtime variables**  
+  Exportable args and environment variables per server e.g. `~/.config/mcpd/secrets.dev.toml`. 
+Never commit dev specific vars to Git again.
 
-🛠️ **Unified Dev Experience**  
+**Unified Dev Experience**  
   One command: `mcpd daemon`. Starts and manages all servers behind the scenes.
 
-🧰 **Intuitive SDK Integration**  
+**Intuitive SDK Integration**  
   The Python `mcpd_sdk` makes calling tools feel like native function calls; no HTTP, STDIO, or SSE boilerplate.
   Even easier for users of [any-agent](https://github.com/mozilla-ai/any-agent) via `.agent_tools()`.
 
-🚀 **Seamless Local-to-Prod Transition**  
+**Seamless Local-to-Prod Transition**  
   The same `.mcpd.toml` and agent code work in dev, CI, and cloud environments without modification.
 
 ---
 
-## 🏗️ Built for Dev & Infra
+## Built for Dev & Infra
 
 | Feature                                                          | Dev Workflow                       | Production Benefit                          |
 |------------------------------------------------------------------|------------------------------------|---------------------------------------------|
@@ -55,20 +56,34 @@ Traditional agent frameworks often embed complex subprocess logic, brittle start
 
 ---
 
-## 🌐 Deploy Anywhere
+## Deploy Anywhere
 
 `mcpd` is runtime-flexible and infrastructure-agnostic:
 
-- ⚙️ Works in any container or host with `uv` and `npx` (NodeJS)
+- ⚙️ Works in any container or host with `uv` and `npx`
 - ☁️ Multi-cloud ready (AWS, GCP, Azure, on-prem)
 - ♻️ Low resource overhead via in-process server management
 
 ---
 
-## Install
+## 📦 Install
 
 ### Homebrew
 
+Add the [Mozilla.ai tap](https://github.com/mozilla-ai/homebrew-tap):
+
+```bash
+brew tap mozilla-ai/tap
+```
+
+Then install `mcpd`:
+
+```bash
+brew install mcpd
+```
+
+Or install directly from the cask in a single command:
+
 ```bash
 brew install --cask mozilla-ai/tap/mcpd
 ```
@@ -88,8 +103,8 @@ Use the sidebar to explore:
 
 ---
 
-## 🌐 About Mozilla AI
+## About Mozilla.ai
 
-This project is built and maintained by [Mozilla AI](https://mozilla.ai), a mission-driven organization reimagining AI for the public good.
+This project is built and maintained by [Mozilla.ai](https://mozilla.ai), a mission-driven organization reimagining AI for the public good.
 
 Have ideas or feedback? Contributions welcome via [GitHub](https://github.com/mozilla-ai/mcpd).