Updating docs.mcp-agent.com for MCP-Agent Cloud

docs/cloud/agent-server.mdx

@@ -17,7 +17,41 @@ When you expose an agent as an MCP server, the framework:
 3. Provides standard workflow management tools
 4. Handles protocol communication
 
-## Default MCP Tools
+## Tools via Decorators
+
+### @app.tool - Synchronous Tools
+
+Synchronous tools execute immediately and return results:
+
+```python
+@app.tool
+def calculate_sum(a: int, b: int) -> int:
+    """Add two numbers together."""
+    return a + b
+```
+
+This creates a single MCP tool `calculate_sum` that executes synchronously.
+
+### @app.async_tool - Asynchronous Tools
+
+Asynchronous tools run as durable workflows:
+
+```python
+@app.async_tool
+async def research_topic(topic: str) -> str:
+    """Research a topic using multiple sources."""
+    # Long-running research operation
+    results = await gather_information(topic)
+    return results
+```
+
+This creates:
+- `research_topic`: Starts the workflow
+- Status tracking via `workflows-get_status`
+- Cancellation via `workflows-cancel`
+
+
+## Built-in MCP Tools
 
 Every agent server automatically provides these workflow management tools:
 
@@ -79,39 +113,6 @@ Cancels a running workflow instance.
 - `run_id`: The run instance ID
 - `workflow_name`: Workflow identifier
 
-## Custom Tools via Decorators
-
-### @app.tool - Synchronous Tools
-
-Synchronous tools execute immediately and return results:
-
-```python
-@app.tool
-def calculate_sum(a: int, b: int) -> int:
-    """Add two numbers together."""
-    return a + b
-```
-
-This creates a single MCP tool `calculate_sum` that executes synchronously.
-
-### @app.async_tool - Asynchronous Tools
-
-Asynchronous tools run as durable workflows:
-
-```python
-@app.async_tool
-async def research_topic(topic: str) -> str:
-    """Research a topic using multiple sources."""
-    # Long-running research operation
-    results = await gather_information(topic)
-    return results
-```
-
-This creates:
-- `research_topic`: Starts the workflow
-- Status tracking via `workflows-get_status`
-- Cancellation via `workflows-cancel`
-
 ## Server Configuration
 
 ### Basic Setup
@@ -145,13 +146,25 @@ uv run mcp-agent serve --app my_agent:app
 uv run mcp-agent serve --app my_agent:app --transport sse
 ```
 
+#### Deploying to **mcp-agent cloud**
+Update your secrets
+```yaml mcp_agent.secrets.yaml
+openai:
+  api_key: !developer_secret
+```
+
+```bash
+uv run mcp-agent login
+uv run mcp-agent deploy my_agent
+```
+
 ## Client Configuration
 
 ### Claude Desktop
 
-Add to `claude_desktop_config.json`:
+For local mcp servers, add to `claude_desktop_config.json`:
 
-```json
+```json claude_desktop_config.json
 {
   "mcpServers": {
     "my-agent": {
@@ -162,6 +175,23 @@ Add to `claude_desktop_config.json`:
 }
 ```
 
+For **mcp-agent cloud**, add to `claude_desktop_config.json`:
+
+```json claude_desktop_config.json
+"my_agent": {
+  "command": "/path/to/npx",
+  "args": [
+    "mcp-remote",
+    "https://[your-agent-server-id].deployments.mcp-agent-cloud.lastmileai.dev/sse",
+    "--header",
+    "Authorization: Bearer ${BEARER_TOKEN}"
+  ],
+  "env": {
+        "BEARER_TOKEN": "your-mcp-agent-cloud-api-token"
+      }
+}
+```
+
 ### Programmatic Access
 
 ```python
@@ -301,4 +331,4 @@ def process_data(
 
 - [Configuration Guide](/configuration)
 - [Workflow Patterns](/workflows/overview)
-- [Cloud Deployment](/cloud/getting-started)
+- [Cloud Deployment](/cloud/getting-started)

docs/cloud/deploying-mcp-servers.mdx

@@ -5,9 +5,9 @@ description: "Deploy standard MCP servers to MCP Agent Cloud infrastructure"
 
 ## Overview
 
-MCP Agent Cloud can deploy both AI agents **and** standard MCP servers. Since agents deployed to MCP Agent Cloud are exposed as MCP servers themselves, the platform naturally supports deploying any MCP-compatible server implementation.
+**mcp-agent cloud** can deploy both AI agents **and** standard MCP servers. Since agents deployed to **mcp-agent cloud** are exposed as MCP servers themselves, the platform naturally supports deploying any MCP-compatible server implementation.
 
-This means you can use MCP Agent Cloud to:
+This means you can use **mcp-agent cloud** to:
 - Deploy regular MCP servers built with FastMCP or other frameworks
 - Host tool servers that don't use AI workflows
 - Deploy resource servers for data access
@@ -44,7 +44,7 @@ async def current_weather_resource():
     """Provide current weather data."""
     return {"temperature": 72, "condition": "sunny"}
 
-# Deploy with MCP Agent Cloud
+# Deploy with mcp-agent cloud
 # mcp-agent deploy my-weather-server
 ```
 
@@ -168,7 +168,7 @@ async def create_ticket(title: str, description: str) -> dict:
 The deployment process is identical whether you're deploying a simple MCP server or a full agent:
 
 ```bash
-# 1. Authenticate with MCP Agent Cloud
+# 1. Authenticate with mcp-agent cloud
 mcp-agent cloud auth login
 
 # 2. Deploy your server
@@ -181,18 +181,17 @@ mcp-agent cloud servers describe <deployment-id>
 mcp-agent configure <server-url> --client claude
 ```
 
-## Benefits of Using MCP Agent Cloud
+## Benefits of Using **mcp-agent cloud**
 
-Even for simple MCP servers, MCP Agent Cloud provides:
+Even for simple MCP servers, **mcp-agent cloud** provides:
 
 ### Infrastructure Management
 - Automatic SSL/TLS termination
 - Load balancing and auto-scaling
-- Regional deployment options
 - High availability
 
 ### Security
-- Secure secrets management via Vault
+- Secure secrets management
 - Authentication and authorization
 - End-to-end encryption
 - Audit logging

docs/cloud/getting-started.mdx

@@ -1,10 +1,10 @@
 ---
-title: Getting Started with MCP Agent Cloud
+title: Getting Started with mcp-agent cloud
 description: "Deploy your first agent to the cloud in under 5 minutes"
 ---
 
 <Info>
-  MCP Agent Cloud is currently in open beta. Follow the instructions below to get started. For feedback, issues and feature requests, visit https://github.com/lastmile-ai/mcp-agent/issues or join our Discord at https://lmai.link/discord/mcp-agent.
+  mcp-agent cloud is currently in open beta. Follow the instructions below to get started. For feedback, issues and feature requests, visit our [github issues](https://github.com/lastmile-ai/mcp-agent/issues) or join [our Discord](https://lmai.link/discord/mcp-agent).
 </Info>
 
 ## Prerequisites
@@ -31,7 +31,7 @@ Before you begin, make sure you have:
 
 <Steps>
   <Step title="Authenticate">
-    Log in to MCP Agent Cloud:
+    Log in to **mcp-agent cloud**:
 
     ```bash
     mcp-agent login
@@ -44,7 +44,7 @@ Before you begin, make sure you have:
     Ensure your project has the required configuration files:
 
     ```yaml mcp_agent.config.yaml
-    execution_engine: temporal  # Cloud uses Temporal
+    execution_engine: temporal
     logger:
       transports: [console]
       level: info
@@ -61,7 +61,9 @@ Before you begin, make sure you have:
       default_model: gpt-4o
     ```
 
-    > [!IMPORTANT] Swap your api_key with !developer_secret to mark what keys will be saved as secrets within mcp-agent cloud.
+    <Note>
+    Swap your api_key with !developer_secret to mark what keys will be saved as secrets within mcp-agent cloud.
+    </Note>
 
     ```yaml mcp_agent.secrets.yaml
     openai:
@@ -81,8 +83,8 @@ Before you begin, make sure you have:
 
     The deployment process will:
     1. Check for existing app with this name or create a new one
-    2. Process your secrets file (transforming !developer_secret tags to secure handles)
-    3. Bundle and upload your code using Wrangler
+    2. Process your secrets file (transforming `!developer_secret` tags to secure handles)
+    3. Bundle and upload your code
     4. Deploy to MCP Agent Cloud's managed infrastructure
 
     You'll see output like:
@@ -224,7 +226,7 @@ Your agent is now available as an MCP server. Here's how to use it:
 
     Then add to your Claude Desktop config (`~/.claude-desktop/config.json`):
 
-    ```json
+    ```json .claude-desktop/config.json
     {
       "servers": {
         "web-summarizer": {
@@ -334,8 +336,7 @@ MCP_API_KEY="your-key" mcp-agent deploy my-agent
 
 MCP Agent Cloud securely handles secrets through the `mcp_agent.secrets.yaml` file:
 
-```yaml
-# mcp_agent.secrets.yaml
+```yaml mcp_agent.secrets.yaml
 openai:
   api_key: !developer_secret  # Will be stored securely