Ragas MCP Server for Cursor 7 tools — connect in under 2 minutes
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.
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{
"mcpServers": {
"ragas": {
"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 Ragas MCP Server
Integrate Ragas with your AI agent to bring professional grade RAG (Retrieval-Augmented Generation) evaluation and tracking into your chat interface. By subscribing to this server, the AI can seamlessly manage datasets and measure LLM performance on demand.
Cursor's Agent mode turns Ragas into an in-editor superpower. Ask Cursor to generate code using live data from Ragas and it fetches, processes, and writes — all in a single agentic loop. 7 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
What you can do
- Dataset Management — Upload, list, and organize evaluation datasets directly inside your environment.
- Run Evaluations — Automatically trigger Ragas evaluations on your RAG pipelines and fetch detailed scoring.
- Track Experiments — Monitor and compare iterative improvements by viewing tracked metrics across different agent versions.
- Project Organization — Associate evaluations with specific projects within your Ragas dashboard.
The Ragas MCP Server exposes 7 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 Ragas to Cursor via MCP
Follow these steps to integrate the Ragas 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 Ragas
Open Agent mode in chat and ask: "Using Ragas, help me..." — 7 tools available
Why Use Cursor with the Ragas MCP Server
Cursor AI Code Editor provides unique advantages when paired with Ragas 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
Ragas + Cursor Use Cases
Practical scenarios where Cursor combined with the Ragas 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
Ragas MCP Tools for Cursor (7)
These 7 tools become available when you connect Ragas to Cursor via MCP:
get_dataset
Retrieves details for a specific evaluation dataset
get_experiment
Retrieves detailed information for a specific experiment
get_results
Retrieves the results of a completed experiment
list_datasets
Lists available evaluation datasets
list_experiments
Lists experiments associated with a specific dataset
list_metrics
Lists all available evaluation metrics
run_evaluation
g., faithfulness, answer_relevancy). Triggers a new evaluation run for a dataset
Example Prompts for Ragas in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with Ragas immediately.
"List all Ragas datasets available in my project."
"Fetch the metrics and results for the recent experiment 'Support Bot V3'."
"Create a new Ragas project named 'Financial_RAG_Testing'."
Troubleshooting Ragas MCP Server with Cursor
Common issues when connecting Ragas to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
Ragas + Cursor FAQ
Common questions about integrating Ragas MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
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?
How do I verify MCP tools are loaded?
Connect Ragas with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Python SDK for building production-grade OpenAI agent workflows.
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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 Ragas to Cursor
Get your token, paste the configuration, and start using 7 tools in under 2 minutes. No API key management needed.
