Bring Coding Stats
to Vercel AI SDK
Learn how to connect Wakapi (WakaTime Alternative) to Vercel AI SDK and start using 4 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Wakapi (WakaTime Alternative) MCP Server?
Connect your Wakapi instance to any AI agent to monitor your development workflow through natural conversation. Wakapi is a self-hosted, open-source alternative to WakaTime that tracks your coding activity across different editors and languages.
What you can do
- Coding Statistics — Retrieve detailed stats including languages, editors, and operating systems used over various time ranges using
get_stats. - Activity Summaries — Fetch granular summaries of your work for specific date ranges or individual projects with
get_summaries. - Project Listing — View all projects you have tracked time for using
list_projectsto keep your portfolio or billable hours organized. - Heartbeat Tracking — Manually send coding activity heartbeats via
send_heartbeatsto ensure your timeline is always accurate.
How it works
- Subscribe to this server
- Enter your Wakapi API URL and API Key
- Start analyzing your coding habits from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Individual Developers — track your own productivity and see which languages you spend the most time on.
- Engineering Managers — get high-level summaries of team activity and project distribution.
- Freelancers — accurately report time spent on specific client projects without manual timers.
Built-in capabilities (4)
Retrieve coding statistics for a user
Retrieve a detailed summary of activity
List all projects tracked by the user
Provide a heartbeat object or an array of heartbeat objects. Send coding activity heartbeats to Wakapi
Why Vercel AI SDK?
The Vercel AI SDK gives every Wakapi (WakaTime Alternative) tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 4 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
- —
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Wakapi (WakaTime Alternative) integration everywhere
- —
Built-in streaming UI primitives let you display Wakapi (WakaTime Alternative) tool results progressively in React, Svelte, or Vue components
- —
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Wakapi (WakaTime Alternative) in Vercel AI SDK
Wakapi (WakaTime Alternative) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Wakapi (WakaTime Alternative) to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Wakapi (WakaTime Alternative) in Vercel AI SDK
The Wakapi (WakaTime Alternative) MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 4 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
Wakapi (WakaTime Alternative) for Vercel AI SDK
Every tool call from Vercel AI SDK to the Wakapi (WakaTime Alternative) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How can I see my coding statistics for the last 7 days?
You can use the get_stats tool and specify 'last_7_days' as the range. The agent will return a breakdown of your languages, editors, and projects for that period.
Can I get a list of all projects I have ever tracked in Wakapi?
Yes! Use the list_projects tool. It will retrieve all project names associated with your account, allowing you to see the scope of your tracked work.
Is it possible to track activity for a specific date range?
Absolutely. Use the get_summaries tool by providing a 'start' and 'end' date in YYYY-MM-DD format. You can even filter this by a specific project name.
How does the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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