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Open Deep Research

An open-source deep research agent framework that integrates multi-model providers, search tools and MCP for reproducible research pipelines.

Overview

Open Deep Research is an open-source deep research agent framework designed to automate reproducible research pipelines. It integrates multiple model providers, search tools, and Model Context Protocol (MCP) servers, and provides LangGraph Studio and configurable agent components to orchestrate tasks from retrieval and summarization to final report generation.

Key features

  • Support for multiple LLM providers and local models, enabling flexible trade-offs between cost and capability.
  • Integrations with search APIs, LangGraph platform, and Open Agent Platform for end-to-end research workflows.
  • Evaluation tooling (Deep Research Bench) and LangSmith compatibility for benchmarking and reproducible experiments.
  • Modular, configuration-driven architecture with quickstart examples and educational resources.

Use cases

  • Automated academic or industry research workflows (literature search, synthesis, report writing).
  • Teaching and training: a reference codebase for deep research courses and demos.
  • Research assistant deployment for organizations to accelerate draft generation and model evaluation.

Technical highlights

  • Built on the LangGraph architecture with visual configuration and runtime management capabilities.
  • Strong evaluation and benchmarking toolchain that integrates with LangSmith and the Deep Research Bench.
  • Plugin-friendly and configurable adapters for retrieval backends, MCP services, and model layers.

Comments

Open Deep Research
Resource Info
🤖 Agent Framework 🌱 Open Source