Skip to main content
Glama

DillyDallyMCP

by DIodide
README.md2.82 kB
# DillyDallyMCP A Model Context Protocol (MCP) server ready for Dedalus deployment. ## Setup ### 1. Initialize Git Repository ```bash cd dedalus-mcp git init git add . git commit -m "Initial commit: Dedalus MCP server" ``` ### 2. Create Remote Repository Create a new repository on GitHub/GitLab/etc. named `DillyDallyMCP`, then: ```bash git remote add origin <your-repo-url> git branch -M main git push -u origin main ``` ### 3. Configure Environment Variables Create a `.env.local` file in the `dedalus-mcp` folder: ```bash CONVEX_URL=https://your-deployment.convex.cloud ``` You can find your Convex URL in: - The monorepo root `.env.local` file (if running locally) - Your Convex dashboard - By running `npx convex dev` from the monorepo root **Note:** The `.env.local` file is gitignored and should not be committed. ### 4. Install Dependencies ```bash npm install ``` ### 5. Build ```bash npm run build ``` ## Testing Locally ### STDIO Mode (for MCP clients) ```bash npm run dev:stdio ``` ### HTTP Mode (for testing/debugging) ```bash npm run dev:http ``` The server will start on `http://localhost:3002` ### Using MCP Inspector ```bash npm run build npm run inspector ``` ## Deployment to Dedalus This server follows Dedalus deployment standards: - ✅ Entry point: `src/index.ts` (or `index.ts` at root) - ✅ TypeScript server structure - ✅ Proper package.json configuration Simply connect your repository to Dedalus and it will automatically detect and deploy the MCP server. ## Project Structure ``` dedalus-mcp/ ├── index.ts # Main entry point ├── server.ts # MCP server implementation ├── cli.ts # CLI argument parsing ├── lib/ # Shared utilities │ └── convexClient.ts # Convex client setup ├── tools/ # MCP tools │ ├── index.ts │ ├── addIntegers.ts │ ├── getRecentActivity.ts │ ├── getLastSession.ts │ ├── getProductivityStats.ts │ ├── getSessionDetails.ts │ └── getAttentionMetrics.ts ├── transport/ # Transport implementations │ ├── index.ts │ ├── http.ts │ └── stdio.ts ├── package.json ├── tsconfig.json └── .env.local # Environment variables (create this) ``` ## Available Tools - `add_integers`: Adds two integers together - `get_recent_activity`: Get recent activity snapshots from DillyDally - `get_last_session`: Get details of the most recent DillyDally session - `get_productivity_stats`: Get productivity statistics over a time range - `get_session_details`: Get detailed information about a specific session - `get_attention_metrics`: Get attention/focus metrics from camera snapshots ## License MIT

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DIodide/DillyDallyMCP'

If you have feedback or need assistance with the MCP directory API, please join our Discord server