Relevance AI Connector for AI agents.
11 live capabilities
Orchestrate autonomous AI workforces and manage multi-agent workflows.
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Why people use Relevance AI
Relevance AI for Multi-Agent Orchestration
This Connector changes that by bringing the dashboard into your chat. You can ask your agent to start a job and then simply ask for a status update whenever you want. You get the results delivered directly to your conversation, letting you stay in your flow instead of hunting for updates.
What Vinkius changes
You get a direct command line to your Relevance AI workforce inside your favorite chat app.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 5,900+ Connectors
- Real-world use case 01
Lead Scoring Automation
An automation engineer triggers a lead scoring agent to analyze 50 new leads and receives a summary of hot versus cold leads in the chat.
- Real-world use case 02
Knowledge Retrieval
A support lead asks the agent to find specific documentation items to answer a complex customer query using the knowledge base search.
- Real-world use case 03
Batch Data Processing
An ops manager runs a custom studio to process a large dataset and then asks the agent for the final completion status.
Complete set · 11capabilities
The complete Relevance AI capability set.
These are the exact actions your AI can choose when you ask it to work with Relevance AI.
01—04
4 capabilities in this set.
Part of 11 available through Relevance AI.
- 01 Capability
Get knowledge
Relevance AI MCP gets the specific details for a knowledge base item. This helps you pull exact facts into your conversation without searching through folders.
- 02 Capability
List executions
Relevance AI MCP views the full history of your agent executions. Use this to see every time an agent ran and what the final result was.
- 03 Capability
Delete task
Relevance AI MCP permanently removes a specific task record from your history. This keeps your workspace clean by getting rid of old logs.
- 04 Capability
Get agent details
Relevance AI MCP pulls metadata and status for a specific AI agent. You can check if an agent is active or see its specific configuration details.
05—08
4 capabilities in this set.
Part of 11 available through Relevance AI.
- 05 Capability
Get task status
Relevance AI MCP checks the current progress and final results of a background task. This lets you see if a long job is still running or already finished.
- 06 Capability
List agents
Relevance AI MCP sees a complete list of all autonomous agents in your workspace. It is the quickest way to see every persona you have built.
- 07 Capability
List knowledge items
Relevance AI MCP browses through all items in your agent's knowledge base. This helps you understand what data your agent has access to right now.
- 08 Capability
List agent tasks
Relevance AI MCP views a list of the most recent tasks performed by your agents. Use this to quickly see what your workforce has been doing lately.
09—11
3 capabilities in this set.
Part of 11 available through Relevance AI.
- 09 Capability
List capabilities
Relevance AI MCP sees all available studios and custom capabilities in your account. Use this to keep track of every custom operation you have built.
- 10 Capability
Trigger agent
Relevance AI MCP starts a new task for a specific autonomous agent. You can give it a goal and let it work in the background while you do other things.
- 11 Capability
Trigger capability
Relevance AI MCP executes a specific custom Studio or capability with provided parameters. This lets you run complex, multi-step operations with specific inputs.
Set up in minutes
One URL. Then ask Relevance AI to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Relevance AI 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_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable Relevance AI for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI URL.
- Step 03
Save and start
Save the connection and enable Relevance AI in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"relevance-ai-alternative": {
"url": "https://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI
Open Agent mode in chat and ask: "Using Relevance AI, help me...". 11 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"relevance-ai-alternative": {
"url": "https://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI
Ask Copilot: "Using Relevance AI, help me...". 11 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"relevance-ai-alternative": {
"url": "https://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI
Open Cascade and ask: "Using Relevance AI, help me...". 11 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"relevance-ai-alternative": {
"url": "https://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI
Ask Cline: "Using Relevance AI, help me...". 11 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add relevance-ai-alternative --transport http "https://edge.vinkius.com/vk_preview_iFwRUZhAj5suaTidWNZC08UUh2XO1rOjS6rvlZqI/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 Relevance AI
Ask Claude: "Using Relevance AI, show me...". 11 tools are ready
Where the request belongs
Work Relevance AI can move forward.
This is for the AI Ops manager who's tired of refreshing browser tabs to see if a batch job finished, or the automation engineer building complex multi-agent systems that need a hands-off way to trigger and monitor.
AI Operations Manager
Monitors agent performance and task summaries without switching tabs.
Automation Engineer
Triggers complex multi-agent workflows via natural language.
Developer
Integrates real-time task results into custom business logic.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse ConnectorsRelevance AI
Automate autonomous AI agents via Relevance AI. manage capabilities, trigger tasks, and monitor results directly.
Langflow (Visual Multi-agent Orchestrator)
Orchestrate multi-agent AI workflows visually. execute flows, manage projects, and trigger webhooks directly from any AI agent.
VectorShift (AI Workflow & RAG Automation)
Automate AI workflows and RAG via VectorShift. manage pipelines, query knowledge bases, and deploy chatbots directly from any AI agent.
Dify
Manage agentic workflows via Dify. send chat messages, track conversations, audit app parameters, and handle file uploads directly from any AI agent.
AutoGen
Orchestrate Microsoft AutoGen multi-agent workflows. manage sessions, agent roles, workflows, and monitor execution logs from any AI agent.
Lindy (Autonomous AI Employees)
Manage autonomous AI employees via Lindy. trigger task runs, monitor reasoning logs, and audit app integrations.
Bring your own AI
Change the model, client or framework. Keep Relevance AI 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 Relevance AI.
The practical details behind the request, access and result.
How does Relevance AI MCP help with multi-agent workflows?
It gives you a central way to trigger and monitor multiple agents at once. You can start a workflow with one agent and check the status of another, all within your chat interface.
Can I use Relevance AI MCP to see my task history?
Yes, you can view the full history of your agent executions. This helps you audit what your agents have done, how many tasks succeeded, and what the final outputs were.
Does Relevance AI MCP support custom studios?
It does. You can execute specific custom studios or capabilities with complex parameters using natural language commands, making it easier to run specialized operations.
How do I manage my knowledge base with Relevance AI MCP?
You can list and search through your agent's knowledge base items directly. This allows you to verify what data your agents have access to without leaving your AI client.
Is Relevance AI MCP good for scaling AI operations?
It is designed for scaling. By providing a direct command line to your Relevance AI infrastructure, it removes the friction of manual dashboard management for large fleets of agents.
Can I delete old tasks using Relevance AI MCP?
Yes, you can permanently remove specific task records. This helps you keep your workspace organized and your task history clean.
Can my AI automatically trigger another autonomous agent in Relevance AI?
Yes! Use the trigger_agent capability. Provide the agent_id and the user message/goal, and your agent will initiate the autonomous workflow in your Relevance account instantly.
How do I find my Region Code and API Key?
The Region Code is in your dashboard URL (e.g., bcbe5a). For the API Key, log in to Relevance AI, navigate to Settings > API Keys, and generate a new secret key.
One connection away
Give your agent a direct line to Relevance AI.
Connect Relevance AI once. Keep it beside 5,900+ managed Connectors when the next task needs more.
Explore every Connector No credit card required · Free tier available