Aporia Connector for AI agents.
7 live capabilities
Monitor LLM performance and enforce safety guardrails in real time.
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Why people use Aporia
Aporia for solving the LLM observability headache
This Connector changes that by bringing the data to you. Instead of hunting for metrics, you can just ask your agent to pull the latest drift numbers or check a specific prompt for toxicity. It turns your AI client into a command center where you can audit your infrastructure and trigger monitors with a simple sentence.
What Vinkius changes
You get a direct line to your model observability data inside your favorite chat interface.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Pre-deployment safety check
An AI engineer sends a batch of test prompts to validate_guardrails to ensure no PII is leaked before pushing to production.
- Real-world use case 02
Sudden accuracy drop investigation
An MLOps engineer asks their agent to get_metrics for the churn predictor to see if a specific feature is drifting.
- Real-world use case 03
Real-time toxicity auditing
A risk officer asks the agent to list_dashboards to review the latest toxicity trends across all customer-facing bots.
Complete set · 7capabilities
The complete Aporia capability set.
These are the exact actions your AI can choose when you ask it to work with Aporia.
01—04
4 capabilities in this set.
Part of 7 available through Aporia.
- 01 Capability
List dashboards
Get a list of all the custom observability dashboards you've built in your workspace.
- 02 Capability
List models
See every machine learning and LLM model currently tracked in your Aporia workspace.
- 03 Capability
Get model
Pull out the specific architectural details and metadata for a single monitored model.
- 04 Capability
List monitors
View the specific monitors you've set up for a particular model to see what's being watched.
05—07
3 capabilities in this set.
Part of 7 available through Aporia.
- 05 Capability
Trigger monitor
Run a specific monitor immediately to check for data integrity or performance issues right now.
- 06 Capability
Validate guardrails
Send a batch of messages to check for toxicity, PII leaks, or off-topic content against your rules.
- 07 Capability
Get metrics
Fetch real-time performance and data drift numbers for any model you're tracking.
Set up in minutes
One URL. Then ask Aporia to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Aporia 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_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Aporia for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia URL.
- Step 03
Save and start
Save the connection and enable Aporia in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"aporia": {
"url": "https://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia
Open Agent mode in chat and ask: "Using Aporia, help me...". 7 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"aporia": {
"url": "https://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia
Ask Copilot: "Using Aporia, help me...". 7 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"aporia": {
"url": "https://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia
Open Cascade and ask: "Using Aporia, help me...". 7 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"aporia": {
"url": "https://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia
Ask Cline: "Using Aporia, help me...". 7 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add aporia --transport http "https://edge.vinkius.com/vk_preview_xK4X7s8PmKOy9iRpjDUr4oudy86jlYzJmpsm9w0q/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 Aporia
Ask Claude: "Using Aporia, show me...". 7 tools are ready
Where the request belongs
Work Aporia can move forward.
This is for the engineers and risk officers who are tired of switching tabs to see if their LLMs are behaving or leaking data in production.
AI Engineer
Testing prompt chains for safety violations and PII leaks during the development cycle.
MLOps Engineer
Monitoring data drift and performance metrics across a fleet of production models.
Risk Officer
Ensuring compliance by auditing toxicity levels and safety guardrail triggers.
Data Scientist
Analyzing model accuracy and identifying feature drift in real time.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
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Monitor LLM apps via Langfuse. track traces, manage prompt templates, and audit evaluation scores.
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Monitor LLM performance via Datadog. track token usage, audit prompts, and monitor AI model metrics directly from any AI agent.
Portkey
AI gateway observability: monitor logs, costs, and manage LLM configurations via agents.
LangSmith (LLM Observability & Hub)
Monitor LLM apps via LangSmith. track traces, audit prompt templates, and manage evaluation datasets.
Bring your own AI
Change the model, client or framework. Keep Aporia 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 Aporia.
The practical details behind the request, access and result.
How does Aporia MCP help with LLM safety?
It connects your safety rules directly to your AI client. You can ask your agent to check prompts for toxicity or PII leaks on the fly, ensuring your model stays within your defined guardrails.
Can I use Aporia MCP to detect PII?
Yes. The Connector allows your agent to run validation checks on messages to identify and block sensitive information like PII before it's processed or stored.
How do I check for model drift with Aporia MCP?
You can simply ask your agent to pull the latest metrics for any model in your workspace. It will return real-time data on performance and identify specific features where drift is occurring.
Can I trigger a manual check with Aporia MCP?
Absolutely. You can tell your agent to run a specific monitor immediately. This is great for verifying data integrity after a system update or a manual data injection.
Is Aporia MCP good for MLOps teams?
It's designed for MLOps. It streamlines how teams monitor model health, manage model inventories, and audit custom dashboards without needing to switch between different monitoring capabilities.
How does Aporia MCP handle toxicity?
It uses your configured guardrails to scan messages for hateful content or off-topic responses, providing an instant pass/fail check directly in your chat interface.
Can my AI agent check for PII vulnerabilities in my conversation logs?
Yes. Provide a message context and prompt the agent to validate guardrails for a specific Aporia project. It will query the Aporia rules engine and return actionable insights immediately. ensuring that your outputs remain safe and compliant before deployment.
How quickly can I review data drift alerts triggered over the weekend?
In seconds. During your Monday stand-up, ask your AI agent to fetch metrics for your primary model and list its monitors. The agent will pull up statistical variations and active alerts directly into your chat, saving you from navigating complex visual dashboards when you need a quick situational report.
If a monitor seems stuck, can the agent force its execution?
Absolutely. If you suspect an anomaly, ask the agent to manually trigger the specific monitor ID. Instead of scheduling a redundant pipeline, the agent hits the Aporia backend to force a run, ensuring your MLOps workflow isn't blocked by cadence limitations.
One connection away
Give your agent a direct line to Aporia.
Connect Aporia once. Keep it beside 5,900+ managed Connectors when the next task needs more.
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