CoexistAI: Modular, developer-friendly research assistant framework

by SPThole · MCP Server · ★ 528

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

How to install CoexistAI

git clone https://github.com/SPThole/CoexistAI.git coexistai

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 60/100

Flagged: environment access. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

agentic-aifastapigithublangchainlanggraphmapmcp-serverredditsearxngtools

Quick Facts

Stars528
Forks34
LanguageJupyter Notebook
CategoryMCP Server
Quality Score60/100
Open Issues4
Last Updated2026-03-10
Created2025-06-06
Platformsbrowser, mcp
Est. Tokens~2921k

About CoexistAI

CoexistAI CoexistAI is a modular, developer-friendly research assistant framework. It enables you to build, search, summarize, and automate research workflows using LLMs, web search, Reddit, YouTube, git and mapping tools—all with simple API calls or Python functions. 🎙️ New Features & Updates 🔥 Docker Installation available (Thanks for all the feedback, hope this makes installations easy).

Compatible Skills

These tools work well together with CoexistAI for enhanced workflows:

  • last30days-skill — semantic(0.31)+complementary+rare_topics+similar_pop+shared_platform (60%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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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