Relevance AI MCP Server for Windsurf 10 tools — connect in under 2 minutes
Windsurf brings agentic AI coding to a purpose-built IDE. Connect Relevance AI through Vinkius and Cascade will auto-discover every tool. ask questions, generate code, and act on live data without leaving your editor.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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.
{
"mcpServers": {
"relevance-ai": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
* 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.
Windsurf's Cascade agent chains multiple Relevance AI tool calls autonomously. query data, analyze results, and generate code in a single agentic session. Paste Vinkius Edge URL, reload, and all 10 tools are immediately available. Real-time tool feedback appears inline, so you see API responses directly in your editor.
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).
The Relevance AI MCP Server exposes 10 tools through the Vinkius. Connect it to Windsurf 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 Windsurf via MCP
Follow these steps to integrate the Relevance AI MCP Server with Windsurf.
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
Add the server
Paste the JSON configuration above into mcp_config.json
Save and reload
Windsurf will detect the new server automatically
Start using Relevance AI
Open Cascade and ask: "Using Relevance AI, help me...". 10 tools available
Why Use Windsurf with the Relevance AI MCP Server
Windsurf provides unique advantages when paired with Relevance AI through the Model Context Protocol.
Windsurf's Cascade agent autonomously chains multiple tool calls in sequence, solving complex multi-step tasks without manual intervention
Purpose-built for agentic workflows. Cascade understands context across your entire codebase and integrates MCP tools natively
JSON-based configuration means zero code changes: paste a URL, reload, and all 10 tools are immediately available
Real-time tool feedback is displayed inline, so you see API responses directly in your editor without switching contexts
Relevance AI + Windsurf Use Cases
Practical scenarios where Windsurf combined with the Relevance AI MCP Server delivers measurable value.
Automated code generation: ask Cascade to fetch data from Relevance AI and generate models, types, or handlers based on real API responses
Live debugging: query Relevance AI tools mid-session to inspect production data while debugging without leaving the editor
Documentation generation: pull schema information from Relevance AI and have Cascade generate comprehensive API docs automatically
Rapid prototyping: combine Relevance AI data with Cascade's code generation to scaffold entire features in minutes
Relevance AI MCP Tools for Windsurf (10)
These 10 tools become available when you connect Relevance AI to Windsurf 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 Windsurf
Ready-to-use prompts you can give your Windsurf 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 Windsurf
Common issues when connecting Relevance AI to Windsurf through the Vinkius, and how to resolve them.
Server not connecting
Relevance AI + Windsurf FAQ
Common questions about integrating Relevance AI MCP Server with Windsurf.
How does Windsurf discover MCP tools?
mcp_config.json file on startup and connects to each configured server via Streamable HTTP. Tools are listed in the MCP panel and available to Cascade automatically.Can Cascade chain multiple MCP tool calls?
Does Windsurf support multiple MCP servers?
mcp_config.json. Each server's tools appear in the MCP panel and Cascade can use tools from different servers in a single flow.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.
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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.
Connect Relevance AI to Windsurf
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.