DillyDallyMCP
The DillyDallyMCP server is a Model Context Protocol server that integrates with DillyDally and Convex to provide productivity tracking data and basic mathematical operations.
Available Capabilities:
Basic Math Operations: Add two integers using the
add_integerstoolActivity Monitoring: Retrieve recent activity snapshots from DillyDally (
get_recent_activity)Session Management: Get details of the most recent session (
get_last_session) or retrieve information about specific sessions (get_session_details)Productivity Analytics: Access productivity statistics over customizable time ranges (
get_productivity_stats)Focus Metrics: Analyze attention and focus metrics derived from camera snapshots (
get_attention_metrics)Multiple Transport Options: Supports STDIO mode for MCP clients and HTTP mode for testing/debugging
Dedalus Deployment Ready: Pre-configured for seamless platform deployment
Note: The server schema currently only exposes the add_integers tool, while five additional DillyDally-related tools are implemented but not yet available in the active schema.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@DillyDallyMCPadd 15 and 27"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
DillyDallyMCP
A Model Context Protocol (MCP) server ready for Dedalus deployment.
Setup
1. Initialize Git Repository
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:
git remote add origin <your-repo-url>
git branch -M main
git push -u origin main3. Configure Environment Variables
Create a .env.local file in the dedalus-mcp folder:
CONVEX_URL=https://your-deployment.convex.cloudYou can find your Convex URL in:
The monorepo root
.env.localfile (if running locally)Your Convex dashboard
By running
npx convex devfrom the monorepo root
Note: The .env.local file is gitignored and should not be committed.
4. Install Dependencies
npm install5. Build
npm run buildRelated MCP server: MCP Boilerplate
Testing Locally
STDIO Mode (for MCP clients)
npm run dev:stdioHTTP Mode (for testing/debugging)
npm run dev:httpThe server will start on http://localhost:3002
Using MCP Inspector
npm run build
npm run inspectorDeployment to Dedalus
This server follows Dedalus deployment standards:
✅ Entry point:
src/index.ts(orindex.tsat 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 togetherget_recent_activity: Get recent activity snapshots from DillyDallyget_last_session: Get details of the most recent DillyDally sessionget_productivity_stats: Get productivity statistics over a time rangeget_session_details: Get detailed information about a specific sessionget_attention_metrics: Get attention/focus metrics from camera snapshots
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
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