
DR-Tulu is AI2's open-source research agent—an 8B model that autonomously plans research strategies, searches the web, reads pages, and synthesizes comprehensive answers with citations. Unlike typical LLMs with tools bolted on, DR-Tulu was trained end-to-end with its MCP tools, making it a compelling open alternative to proprietary research APIs. This guide walks through deploying DR-Tulu on Vast.ai, where you can run the full agent stack on affordable GPU instances and integrate it into your own agentic applications.

## What Makes DR-Tulu Special?

Key features include:
- **Native MCP Integration**: Trained with web search and page reading tools from the start
- **Autonomous Research**: Plans strategies, gathers sources, and synthesizes cited answers
- **Efficient Architecture**: 8B parameters with strong research capabilities

## What's in the New Guide

Our latest documentation walks you through deploying DR-Tulu on Vast.ai with a split architecture: vLLM for GPU inference on Vast.ai, MCP backend running locally for tool execution.

**Complete Deployment Instructions**
- Instance selection with the Vast.ai CLI
- vLLM configuration with the correct version (critical for compatibility)
- MCP backend setup with required API keys
- Workflow configuration to connect the components

**Three Ways to Use DR-Tulu**
- Interactive chat for exploratory research
- Batch evaluation against built-in datasets
- Python API for programmatic integration

## Why This Architecture?

The split deployment keeps GPU-intensive inference on Vast.ai while running tool orchestration locally. This means:

- Your API keys (Serper, Jina) stay on your machine (or wherever you deploy the MCP backend)
- Model inference doesn't require sending data to third-party APIs
- You can modify the MCP backend without redeploying the model
- Lower Vast.ai costs since you only need GPU for inference

## Who Should Use This Guide?

This deployment guide is perfect for:
- **Researchers** who need cited, source-backed answers at scale
- **Developers** building applications that require web research capabilities
- **Teams** evaluating open alternatives to proprietary research APIs

## Get Started

The complete guide is now available in our documentation:

**[Read: Running DR-Tulu on Vast.ai →](https://docs.vast.ai/examples/mcp/dr-tulu)**

Whether you're exploring agentic AI architectures or ready to deploy your own research assistant, this guide provides everything you need to get DR-Tulu running on Vast.ai infrastructure.

Ready to try it? [Sign up for Vast.ai](https://vast.ai) and follow the guide to deploy your first instance.


Learn how to deploy DR-Tulu, AI2's open-source research agent, on Vast.ai for autonomous web research with citations.

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