Kodi MCP Connector
Overview
This skill enables Claude to interact with Kodi through the Model Context Protocol (MCP). It provides a bridge between Claude's AI capabilities and Kodi's JSON-RPC, allowing natural language control of Kodi operations, intelligent automation, and AI-powered assistance for Kodi workflows.
When to Use This Skill
- Smart playlist creation from natural language
- Library scanning and metadata correction
- Addon discovery and installation
- Remote control and playback management
- Skin and appearance customization
Architecture
┌─────────────┐ ┌─────────────────┐ ┌──────────────────┐
│ Claude │────▶│ MCP Server │────▶│ Kodi │
│ (Client) │◀────│ (TypeScript) │◀────│ (JSON-RPC )│
└─────────────┘ └─────────────────┘ └──────────────────┘
Core Concepts
MCP Server Setup
The connector implements an MCP server that exposes Kodi operations as tools Claude can invoke. The server translates natural language intentions into JSON-RPC calls.
Key Endpoints/Interfaces
VideoLibrary.GetMovies, AudioLibrary.GetSongs, Playlist.Add, Addons.GetAddons, Player.Open
Implementation
// Kodi MCP Server Implementation
import { McpServer } from "@modelcontextprotocol/sdk/server/mcp.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { z } from "zod";
const server = new McpServer({
name: "kodi-mcp-connector",
version: "1.0.0",
});
// Tool: List/Query Resources
server.tool(
"list_resources",
"List and query Kodi resources with optional filters",
{
query: z.string().optional().describe("Search query or filter"),
limit: z.number().optional().describe("Max results to return"),
},
async ({ query, limit }) => {
// Call Kodi JSON-RPC
const response = await fetch(`${BASE_URL}VideoLibrary.GetMovies`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
// Tool: Create Resource
server.tool(
"create_resource",
"Create a new resource in Kodi",
{
name: z.string().describe("Resource name"),
config: z.object({}).passthrough().optional().describe("Resource configuration"),
},
async ({ name, config }) => {
const response = await fetch(`${BASE_URL}VideoLibrary.GetMovies`, {
method: "POST",
headers: {
"Authorization": `Bearer ${API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({ name, ...config }),
});
const data = await response.json();
return {
content: [{ type: "text", text: `Created: ${JSON.stringify(data)}` }],
};
}
);
// Tool: Analyze/Report
server.tool(
"analyze",
"AI-powered analysis of Kodi data",
{
type: z.string().describe("Analysis type"),
timeframe: z.string().optional().describe("Time range for analysis"),
},
async ({ type, timeframe }) => {
// Fetch data and provide AI analysis
const response = await fetch(`${BASE_URL}VideoLibrary.GetMovies`, {
headers: { "Authorization": `Bearer ${API_KEY}` },
});
const data = await response.json();
return {
content: [{ type: "text", text: JSON.stringify(data, null, 2) }],
};
}
);
// Start server
const transport = new StdioServerTransport();
await server.connect(transport);
Claude Desktop Configuration
{
"mcpServers": {
"kodi-mcp-connector": {
"command": "node",
"args": ["path/to/kodi-mcp-connector/index.js"],
"env": {
"KODI_API_KEY": "your-api-key",
"KODI_BASE_URL": "https://your-instance-url"
}
}
}
}
Best Practices
- Authentication: Store API keys securely using environment variables; never hardcode credentials
- Rate Limiting: Implement request throttling to respect Kodi API rate limits
- Error Handling: Provide clear, actionable error messages for common failure scenarios
- Pagination: Handle paginated responses for large datasets efficiently
- Caching: Cache frequently accessed read-only data to reduce API calls
- Security: Validate all inputs before passing to the Kodi API; sanitize outputs
- Logging: Log all API interactions for debugging and audit purposes
Example Prompts
"Create a smart playlist of all unwatched sci-fi movies released in the last 5 years sorted by rating"
Security Considerations
- All API credentials must be stored as environment variables
- Implement input validation and sanitization for all tool parameters
- Use HTTPS for all API communications
- Follow the principle of least privilege for API token permissions
- Audit log all write operations for compliance tracking
Resources
- Kodi Official Documentation
- MCP SDK Documentation: https://modelcontextprotocol.io
- MCP Server Examples: https://github.com/modelcontextprotocol/servers
- SkillGalaxy Repository: https://github.com/Sandeeprdy1729/skill_galaxy
Changelog
| Version | Date | Changes |
|---|---|---|
| 1.0.0 | 2026-04-01 | Initial MCP connector skill |
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