Can the agent monitor a long-running relevance AI agent task?

Yes. You can trigger an agent using `trigger_agent`, and because it provides a `run_id`, you can explicitly prompt your local Assistant to periodically "check in on the status using `get_agent_run` every minute until finished" or ask it to summarize the step-by-step agent logs after completion.

What is the differences between tasks, tools, and agents in Relevance AI?

Agents are autonomous workers capable of making step-by-step reasoning choices based on instructions and tools. Tasks are linear, pre-chained sets of commands and prompts. Tools (`list_tools`) are the individual capabilities, like a custom API integration or web scraper, that tasks and agents utilize to perform their actions.

How do I find my specific Region and Project ID?

These details are typically nested within the URL string when you are logged into your workspace or found globally in your developer API keys configuration pane inside your Relevance AI team dashboard. The Region is usually something like 'us-east-1' or 'v2'.

Relevance AI MCP Server for Cursor 10 tools — connect in under 2 minutes

Name: Relevance AI
Availability: InStock
Author: Vinkius

docs.cursor.com/context/model-context-protocol

Built by Vinkius GDPR 10 Tools IDE

Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

RecommendedModern Approach — Zero Configuration

Vinkius Desktop App

The modern way to manage MCP Servers — no config files, no terminal commands. Install Relevance AI and 2,500+ MCP Servers from a single visual interface.

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Classic Setup·json

{
  "mcpServers": {
    "relevance-ai": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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

About Relevance AI MCP Server

Connect your conversational AI to your Relevance AI workspace. By wrapping your custom agents, datasets, and API tools into this MCP extension, you transform your chat interface into a command center for orchestrating complex, autonomous AI operations and large-scale data workflows.

Cursor's Agent mode turns Relevance AI into an in-editor superpower. Ask Cursor to generate code using live data from Relevance AI and it fetches, processes, and writes. all in a single agentic loop. 10 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.

What you can do

Orchestrate Agents — Command your pre-built autonomous agents to execute tasks (trigger_agent). Monitor their progress and read their exact reasoning steps dynamically (get_agent_run). Use list_agents to discover all available AI worker configurations.
Execute Tasks & Workflows — Trigger predefined chained prompts or specific micro-tasks without leaving your chat (trigger_task), scaling repetitive workflows reliably.
Manage Knowledge Datasets — Take full control of your vector databases and tables. Insert new rows of knowledge directly from conversational context (insert_documents), retrieve raw unstructured data entries (get_documents), or surgically delete obsolete knowledge base items (delete_documents).

The Relevance AI MCP Server exposes 10 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Relevance AI to Cursor via MCP

Follow these steps to integrate the Relevance AI MCP Server with Cursor.

Open MCP Settings

Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"

Add the server config

Paste the JSON configuration above into the mcp.json file that opens

Save the file

Cursor will automatically detect the new MCP server

Start using Relevance AI

Open Agent mode in chat and ask: "Using Relevance AI, help me...". 10 tools available

Why Use Cursor with the Relevance AI MCP Server

Cursor AI Code Editor provides unique advantages when paired with Relevance AI through the Model Context Protocol.

Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context

Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards

MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment

VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools

Relevance AI + Cursor Use Cases

Practical scenarios where Cursor combined with the Relevance AI MCP Server delivers measurable value.

Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP

Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically

Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates

Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data

Relevance AI MCP Tools for Cursor (10)

These 10 tools become available when you connect Relevance AI to Cursor via MCP:

delete_documents

This action is irreversible. Deletes documents from a dataset by their IDs

get_agent_run

Retrieves the status and logs of a specific agent run

get_documents

Retrieves documents from a dataset

insert_documents

Provide documents as a JSON array of objects. Inserts documents into a dataset

list_agents

Lists all AI agents in the Relevance AI studio

list_datasets

Lists all datasets (knowledge tables) in the project

list_tasks

Lists all tasks (chained prompts) in the studio

list_tools

Lists all custom tools registered in the studio

trigger_agent

Provide inputs as a JSON object. Triggers an AI agent execution

trigger_task

Triggers a specific task execution

Example Prompts for Relevance AI in Cursor

Ready-to-use prompts you can give your Cursor agent to start working with Relevance AI immediately.

"List all available agents in my Relevance AI Studio and their IDs."

"Start a run for the 'Market Analysis' agent passing `{"company": "OpenAI"}` as the payload, then tell me the Run ID."

"Insert this JSON array of top competitor articles into the 'competitor_docs' dataset."

Troubleshooting Relevance AI MCP Server with Cursor

Common issues when connecting Relevance AI to Cursor through the Vinkius, and how to resolve them.

Tools not appearing in Cursor

Ensure you are in Agent mode (not Ask mode). MCP tools only work in Agent mode.

Server shows as disconnected

Check Settings → Features → MCP and verify the server status. Try clicking the refresh button.

Relevance AI + Cursor FAQ

Common questions about integrating Relevance AI MCP Server with Cursor.

What is Agent mode and why does it matter for MCP?

Agent mode is Cursor's autonomous execution mode where the AI can perform multi-step tasks: reading files, editing code, running terminal commands, and calling MCP tools. Without Agent mode, Cursor operates in a simpler ask-and-answer mode that doesn't support tool calling. Always ensure you're in Agent mode when working with MCP servers.

Where does Cursor store MCP configuration?

Cursor looks for MCP server configurations in a mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.

Can Cursor use MCP tools in inline edits?

No. MCP tools are only available in Agent mode through the chat panel. Inline completions and Tab suggestions do not trigger MCP tool calls. This is by design. tool calls require user visibility and approval.

How do I verify MCP tools are loaded?

Open Settings → Features → MCP and look for your server name. A green indicator means the server is connected. You can also check Agent mode's available tools by clicking the tools dropdown in the chat panel.