DeepWideResearch

by puppyone-ai · MCP 服务器 · ★ 296

About DeepWideResearch

Open Deep Wide Research Agentic RAG for any scenarioCustomize sources, depth, and width Why Do You Need Open Deep Wide Research? In 2025, we observed 2 critical trends reshaping the Retrieval-Augmented Generation (RAG) tech stacks: Traditional, Rigid, pipeline-driven RAG is giving way to more dynamic agentic RAG systems. The emergence of MCP is dramatica

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Quick Facts

Stars296
Forks5
LanguageTypeScript
CategoryMCP 服务器
LicenseApache-2.0
Quality Score40.25/100
Last Updated2025-12-17
Created2025-09-30
Platformsmcp, node
Est. Tokens~1537k

Compatible Skills

These tools work well together with DeepWideResearch for enhanced workflows:

  • agentic — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • lucid-memory — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
  • obsidian-gemini-helper — semantic(0.17)+complementary+same_lang+similar_pop+shared_platform (51%)
  • sim — semantic(0.16)+complementary+same_lang+shared_platform (46%)

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Frequently Asked Questions

What is DeepWideResearch?

DeepWideResearch is Agentic RAG for any scenario. Customize sources, depth, and width. It is categorized as a MCP 服务器 with 296 GitHub stars.

What programming language is DeepWideResearch written in?

DeepWideResearch is primarily written in TypeScript. It covers topics such as agent, agentic-workflow, mcp.

How do I install or use DeepWideResearch?

You can find installation instructions and usage details in the DeepWideResearch GitHub repository at github.com/puppyone-ai/DeepWideResearch. The project has 296 stars and 5 forks, indicating an active community.

What license does DeepWideResearch use?

DeepWideResearch is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

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