deep-code-reasoning-mcp: A Model Context Protocol server that provides advanced code analysis and reasoning capabilities powered

by haasonsaas · MCP Server · ★ 102

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

How to install deep-code-reasoning-mcp

git clone https://github.com/Haasonsaas/deep-code-reasoning-mcp.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 79/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

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.

aiai-toolsclaudecode-analysiscode-intelligencecode-reasoningdebuggingdeveloper-toolsdistributed-systemsgemini

Quick Facts

Stars102
Forks15
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score79/100
Open Issues5
Last Updated2026-03-06
Created2025-06-11
Platformsclaude-code, gemini, mcp, node
Est. Tokens~16k

About deep-code-reasoning-mcp

Deep Code Reasoning MCP Server An MCP server that pairs Claude Code with Google's Gemini AI for complementary code analysis. This server enables a multi-model workflow where Claude Code handles tight terminal integration and multi-file refactoring, while Gemini leverages its massive context window (1M tokens) and code execution capabilities for distributed system debugging and long-trace...

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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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