Add MCP server for AI assistant integration

Cargo.toml

@@ -1,6 +1,6 @@
 [package]
 name = "screenly"
-version = "1.0.5"
+version = "1.1.0"
 edition = "2021"
 
 [[bin]]
@@ -30,28 +30,32 @@ rayon = "1.7.0"
 regex = "1.9.3"
 reqwest = { version = "0.12.22", features = ["json", "blocking", "multipart"] }
 rpassword = "7.2.0"
-sentry = "0.42.0"
-sentry-anyhow = "0.42.0"
+sentry = "0.46"
+sentry-anyhow = "0.46"
 serde = { version = "1.0.147", features = ["derive"] }
 serde_json = "1.0.87"
 serde_with = "3.8.3"
 serde_yaml = "0.9.17"
 sha1 = "0.10.5"
 sha2 = "0.10.7"
-simple_logger = { version = "4.0.0", features = ["colors"] }
+simple_logger = { version = "5", features = ["colors"] }
 strum = "0.27"
 strum_macros = "0.27"
 temp-env = "0.3.6"
 term = "1.1.0"
 thiserror = "2.0.12"
-tokio = { version = "1.32.0", features = ["rt-multi-thread"] }
+tokio = { version = "1.32.0", features = ["rt-multi-thread", "macros"] }
 tokio-stream = "0.1.14"
 walkdir = "2.3.3"
-warp = "0.3.5"
+warp = "0.3"
+
+# MCP server dependencies
+rmcp = { version = "0.12", features = ["schemars", "server", "transport-io"] }
+schemars = "0.8"
 
 [dev-dependencies]
 envtestkit = "1.1.2"
-httpmock = "0.6"
-swc_common = { version = "14.0.4", default-features = false, features = [] }
-swc_ecma_parser = { version = "24.0.2", default-features = false, features = [] }
+httpmock = "0.8"
+swc_common = { version = "18", default-features = false, features = [] }
+swc_ecma_parser = { version = "32", default-features = false, features = ["typescript"] }
 tempfile = "3.8"

Dockerfile

@@ -3,7 +3,7 @@ FROM alpine:3 as builder
 
 WORKDIR /usr/src/screenly-cli
 RUN apk add --no-cache wget tar
-ARG RELEASE=v1.0.5
+ARG RELEASE=v1.1.0
 RUN wget "https://github.com/Screenly/cli/releases/download/$RELEASE/screenly-cli-x86_64-unknown-linux-musl.tar.gz"
 RUN tar xfz screenly-cli-x86_64-unknown-linux-musl.tar.gz
 

README.md

@@ -67,6 +67,57 @@ $ API_SERVER_NAME=local cargo build --release
 
 Explore available commands [here](https://developer.screenly.io/cli/#commands).
 
+## MCP Server (AI Assistant Integration)
+
+The Screenly CLI includes a built-in [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) server, enabling AI assistants like Claude, Cursor, and others to interact with your Screenly digital signage network.
+
+### Starting the MCP Server
+
+```bash
+$ screenly mcp
+```
+
+The server communicates over stdio and exposes the full Screenly API as tools.
+
+### Available Tools
+
+| Category | Tools |
+|----------|-------|
+| **Screens** | `screen_list`, `screen_get` |
+| **Assets** | `asset_list`, `asset_get`, `asset_create`, `asset_update`, `asset_delete` |
+| **Asset Groups** | `asset_group_list`, `asset_group_create`, `asset_group_update`, `asset_group_delete` |
+| **Playlists** | `playlist_list`, `playlist_create`, `playlist_update`, `playlist_delete` |
+| **Playlist Items** | `playlist_item_list`, `playlist_item_create`, `playlist_item_update`, `playlist_item_delete` |
+| **Labels** | `label_list`, `label_create`, `label_update`, `label_delete`, `label_link_screen`, `label_unlink_screen`, `label_link_playlist`, `label_unlink_playlist` |
+| **Shared Playlists** | `shared_playlist_list`, `shared_playlist_create`, `shared_playlist_delete` |
+| **Edge Apps** | `edge_app_list`, `edge_app_list_settings`, `edge_app_list_instances` |
+
+### Configuration Examples
+
+#### Cursor / Claude Desktop
+
+Add to your MCP configuration file:
+
+```json
+{
+  "mcpServers": {
+    "screenly": {
+      "command": "screenly",
+      "args": ["mcp"],
+      "env": {
+        "API_TOKEN": "your-api-token-here"
+      }
+    }
+  }
+}
+```
+
+#### Authentication
+
+The MCP server uses the same authentication as the CLI:
+- Set the `API_TOKEN` environment variable, or
+- Run `screenly login` to store credentials in `~/.screenly`
+
 ## GitHub Action
 
 Integrate Screenly CLI into your GitHub workflows: