Relevance AI MCP Server
Equip your AI to trigger custom autonomous agents, execute chained prompts, and manage unstructured knowledge datasets directly within your Relevance AI studio.
Ask AI about this MCP Server
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What is the Relevance AI MCP Server?
The Relevance AI MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Relevance AI via 10 tools. Equip your AI to trigger custom autonomous agents, execute chained prompts, and manage unstructured knowledge datasets directly within your Relevance AI studio. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.
Built-in capabilities (10)
Tools for your AI Agents to operate Relevance AI
Ask your AI agent "List all available agents in my Relevance AI Studio and their IDs." and get the answer without opening a single dashboard. With 10 tools connected to real Relevance AI data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.
Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.
Why teams choose Vinkius
One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents 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 and security, zero maintenance.
Build your own MCP Server with our secure development framework →Vinkius works with every AI agent you already use
…and any MCP-compatible client
Relevance AI MCP Server capabilities
10 toolsThis action is irreversible. Deletes documents from a dataset by their IDs
Retrieves the status and logs of a specific agent run
Retrieves documents from a dataset
Provide documents as a JSON array of objects. Inserts documents into a dataset
Lists all AI agents in the Relevance AI studio
Lists all datasets (knowledge tables) in the project
Lists all tasks (chained prompts) in the studio
Lists all custom tools registered in the studio
Provide inputs as a JSON object. Triggers an AI agent execution
Triggers a specific task execution
What the Relevance AI MCP Server unlocks
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.
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). Uselist_agentsto 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).
How it works
1. Add the Relevance AI extension to your MCP hub.
2. Supply your Project ID, API Key, and your assigned Region (e.g., "us-east-1" or "v2") from your Relevance AI settings.
3. Prompt your assistant: "Trigger the 'Lead Research' agent with the company name 'Google' and monitor the run until completion. Then, insert the output directly into our 'competitors' dataset."
Who is this for?
- AI Engineers & Builders — Run end-to-end tests on your chained logic and customized agents directly from your terminal or chat without touching the studio GUI.
- Data Analysts — Move processed insights, raw texts, and structured metadata into Relevance AI datasets using natural language.
- Operations Teams — Combine the output of your everyday AI chat intimately with your specialized Relevance AI autonomous agents for highly productive compounding workflows.
Frequently asked questions about the Relevance AI MCP Server
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'.
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Connect Relevance AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Give your AI agents the power of Relevance AI MCP Server
Production-grade Relevance AI MCP Server. Verified, monitored, and maintained by Vinkius. Ready for your AI agents — connect and start using immediately.