local-deep-research — security grade SAFE, quality 63/100

Security audit verdict: SAFE · quality 63/100

No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

by LearningCircuit · Agent Tool · ★ 9.1k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

🔒 Is local-deep-research safe to install? View the security audit →

About local-deep-research

Local Deep Research [![OpenSSF Scorecard](https://api.securityscorecards.dev/p

academiaanthropicarxivbravedeep-researchencryptionhome-automationhomeserverlocallocal-deep-research

Quick Facts

Stars9,123
Forks832
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score63.3147337301187/100
Open Issues973
Last Updated2026-09-23
Created2025-02-09
Platformspython
Est. Tokens~20k

Compatible Skills

These tools work well together with local-deep-research for enhanced workflows:

  • arxiv-mcp-server — semantic(0.18)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
  • deep-research-mcp — semantic(0.35)+complementary+shared_fw(ollama)+same_lang+shared_platform (60%)
  • gpt-researcher — semantic(0.26)+complementary+rare_topics+same_lang+similar_pop+shared_platform (59%)
  • paperbanana — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (58%)

local-deep-research alternative? Top 6 similar tools

Looking for a local-deep-research alternative? If you're comparing local-deep-research with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

  • agentops by AgentOps-AI · ⭐ 5.8k

    Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and a

  • deep-research by u14app · ⭐ 4.7k

    Use any LLMs (Large Language Models) for Deep Research. Support SSE API and MCP server.

  • maid by Mobile-Artificial-Intelligence · ⭐ 2.7k

    Maid is a free and open source application for interfacing with llama.cpp models locally, and with Anthropic,

  • hive by aden-hive · ⭐ 11.0k

    Multi-Agent Harness for Production AI

  • codecompanion.nvim by olimorris · ⭐ 6.9k

    ✨ AI Coding, Vim Style

  • sdk-python by strands-agents · ⭐ 6.0k

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Frequently Asked Questions

What is local-deep-research?

local-deep-research is ~95% on SimpleQA (e.g. Qwen3.6-27B on a 3090). Supports all local and cloud LLMs (llama.cpp, Ollama, Google, ...). 10+ search engines - arXiv, PubMed, your private documents. Everything Local & Encryp. It is categorized as a Agent Tool with 9.1k GitHub stars.

What programming language is local-deep-research written in?

local-deep-research is primarily written in Python. It covers topics such as academia, anthropic, arxiv.

How do I install or use local-deep-research?

You can find installation instructions and usage details in the local-deep-research GitHub repository at github.com/LearningCircuit/local-deep-research. The project has 9.1k stars and 832 forks, indicating an active community.

What license does local-deep-research use?

local-deep-research is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to local-deep-research?

The top alternatives to local-deep-research on Agent Skills Hub include agentops, deep-research, maid. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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