StatHat Connector for AI agents.
4 live capabilities
Track application performance and business KPIs in real-time.
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Why people use StatHat
StatHat : Stop manual data entry for app metrics
With this Connector, that manual process disappears. You just tell your agent what happened in plain English. It handles the API call and updates your stats immediately. You get a live feed of your progress without ever leaving your workspace.
What Vinkius changes
Your AI handles the data entry so you don't have to.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Logging errors during a hotfix
A developer asks their agent to log a specific error.
- Real-world use case 02
Updating business KPIs
An analyst tells their agent to update the daily signup count to 500.
- Real-world use case 03
Monitoring system health
A DevOps engineer wants to increment a 'Requests Handled' counter.
Complete set · 4capabilities
The complete StatHat capability set.
These are the exact actions your AI can choose when you ask it to work with StatHat.
01—04
4 capabilities in this set.
Part of 4 available through StatHat.
- 01 Capability
Post classic counter
Post a counter stat using the StatHat Classic API. This lets you increment specific metrics with unique keys.
- 02 Capability
Post classic value
Post a value stat using the StatHat Classic API. Use this to send specific numerical data like response times.
- 03 Capability
Post ez stat
Creates the stat automatically if it doesn't exist. This is perfect for quick logging where you don't want to pre-define keys.
- 04 Capability
Post json stats
Pass a JSON array of objects containing stat/key, count/value, and optional t (timestamp). This lets you update multiple stats in one go for better efficiency.
Set up in minutes
One URL. Then ask StatHat to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use StatHat from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it StatHat, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable StatHat for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the StatHat URL.
- Step 03
Save and start
Save the connection and enable StatHat in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"stathat": {
"url": "https://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using StatHat
Open Agent mode in chat and ask: "Using StatHat, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"stathat": {
"url": "https://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using StatHat
Ask Copilot: "Using StatHat, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"stathat": {
"url": "https://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using StatHat
Open Cascade and ask: "Using StatHat, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"stathat": {
"url": "https://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using StatHat
Ask Cline: "Using StatHat, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add stathat --transport http "https://edge.vinkius.com/vk_preview_9nbOVIYYenpFsByD28JMgOZQqElzpJceAGuRHFs0/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using StatHat
Ask Claude: "Using StatHat, show me...". 4 tools are ready
Where the request belongs
Work StatHat can move forward.
This is for the developer who's tired of manual logging, the data analyst who needs real-time updates, and the DevOps engineer monitoring system health.
Software Engineer
Logging function execution counts or errors during a hotfix without leaving the IDE.
Data Analyst
Updating business KPIs or experimental results from a chat interface during a sprint.
DevOps Engineer
Tracking event counts and system health metrics without leaving the terminal.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsCountly
Manage product analytics via Countly. track user sessions, record custom events, and query deep behavioral metrics directly from your AI agent.
GoatCounter
Privacy-friendly web analytics. track pageviews, analyze visitor stats, and manage your sites directly through any AI agent.
Amplitude
Track user behavior, analyze product metrics, and manage cohorts directly from your AI agent using Amplitude's powerful analytics suite.
Matomo
Open-source web analytics via Matomo. track visits, goals, and user behavior directly from any AI agent.
PostHog
Analyze product data via PostHog. list insights, track persons, inspect feature flags, and monitor experiments directly from any AI agent.
Umami Cloud
Privacy-focused web analytics alternative to Google Analytics.
Bring your own AI
Change the model, client or framework. Keep StatHat connected.
-
Claude -
ChatGPT -
Gemini -
Cursor -
VS Code -
Windsurf -
ZCode -
Cline -
Zed -
Continue -
Kiro -
Roo Code -
Zencoder -
Goose -
Void -
Augment Code -
Amp -
Qodo -
Tabnine -
Pieces -
Sourcegraph Cody -
JetBrains -
Warp -
Amazon Q -
Antigravity -
BoltAI -
Raycast -
Jan -
LM Studio -
AnythingLLM -
Open WebUI -
Msty -
Cherry Studio -
LibreChat -
TypingMind -
Chorus -
5ire -
n8n -
LangChain -
LlamaIndex -
CrewAI -
Vercel AI SDK
Before you connect
Questions about StatHat.
The practical details behind the request, access and result.
How does the StatHat MCP help with my app tracking?
It lets your AI agent log metrics directly to your StatHat dashboard. Instead of you typing in numbers, your agent handles the updates as it performs tasks.
Can I use StatHat MCP to create new stats automatically?
Yes, the Connector includes a feature that creates a new stat automatically if it doesn't already exist, so you don't have to pre-define every single key.
Is StatHat MCP good for high-volume data logging?
Yes, it supports batch updates. You can send multiple statistics in a single request, which is much more efficient for logging large amounts of data at once.
Do I need to be a developer to use the StatHat MCP?
No, anyone who uses AI agents to help with work can use it. You just need your StatHat keys to let your agent start logging data for you.
What kind of metrics can I track with StatHat MCP?
You can track anything from simple counters, like signups or errors, to specific numerical values like response times, temperatures, or any other business KPI.
Will using StatHat MCP slow down my AI agent?
No, it's designed to be a fast bridge to your data. The updates happen in the background so your agent can keep working without delay.
What is the difference between the EZ API and the Classic API?
The EZ API (post_ez_stat) allows you to post stats using a simple human-readable name and your EZ Key. The Classic API (post_classic_counter, post_classic_value) requires a unique Stat Key for each specific metric, providing more granular control.
Do I need to create a stat on the website before posting to it?
No! When using the post_ez_stat capability, StatHat will automatically create the statistic for you if it doesn't already exist in your account.
Can I send multiple metrics at once to save time?
Yes, you can use the post_json_stats capability to send an array of multiple stat updates in a single network request.
One connection away
Give your agent a direct line to StatHat.
Connect StatHat once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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