deepseek-claude-code-worker-mcp: DeepSeek V4 code worker MCP for Codex Desktop, powered by Claude Code

by louchi1984-coder · MCP Server · ★ 97

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

How to install deepseek-claude-code-worker-mcp

git clone https://github.com/louchi1984-coder/deepseek-claude-code-worker-mcp.git
npx github:louchi1984-coder/deepseek-claude-code-worker-mcp#v0.3.20-beta.38 --doctor

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 70/100

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.

Quick Facts

Stars97
Forks13
LanguageJavaScript
CategoryMCP Server
LicenseMIT
Quality Score70/100
Open Issues1
Last Updated2026-05-29
Created2026-05-07
Platformsclaude-code, codex, mcp, node
Est. Tokens~15k

About deepseek-claude-code-worker-mcp

DeepSeek Code Worker MCP Languages: English | 简体中文 Coding-worker MCP for Codex Desktop. Codex plans, delegates, and reviews; DeepSeek V4 does the expensive code reading, editing, and checking through Claude Code. Goal: save Codex main-thread tokens, not DeepSeek tokens. For suitable coding tasks, the intended workflow can reduce Codex main-thread token usage by about 40-60%.

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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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