TechDebtMCP v2.0.0: MCP server for technical debt analysis across 14 languages

TechDebtMCP v2.0.0 is an MCP server that connects Claude to your codebase to analyze technical debt. Once connected, you can ask Claude questions about technical debt, security issues, and code quality.
Key Features
- Analyzes code quality issues, security vulnerabilities, and maintainability problems across 14 programming languages: JS/TS, Python, Java, Swift, Kotlin, Go, Rust, C/C++, C#, Ruby, PHP, and more
- Provides SQALE metrics including A–E debt ratings, remediation time estimates, and debt ratios
- Includes 14 specialized SwiftUI checks for state management, retain cycles, deprecated patterns, etc.
- Performs dependency analysis across 10 package ecosystems
- Supports custom rules via
.techdebtrc.jsonfor defining regex-based checks
Example Queries
Once connected, you can ask Claude:
- "What's the worst technical debt in this project?"
- "Give me a SQALE rating for this repo"
- "What are my top 5 security issues?"
- "Scan this file and tell me what needs fixing first"
Setup
Add to Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"tech-debt-mcp": {
"command": "npx",
"args": ["-y", "tech-debt-mcp@latest"]
}
}
}Or use Claude Code:
claude mcp add tech-debt-mcp -- npx -y tech-debt-mcp@latestThe tool scans itself regularly and currently holds an A rating with a 2.9% debt ratio.
📖 Read the full source: r/ClaudeAI
👀 See Also

Signet: An Open-Source Local-First Memory Substrate for AI Agents
Signet is an open-source memory substrate for AI agents that moves memory handling outside the agent loop. It preserves transcripts, distills sessions into structured memory, links entities into a graph, and injects context before prompts start.

Local Book Translation Pipeline Uses Qwen 32B and Mistral 24B with Contextual RAG
A developer built a fully automated PDF-to-ePub book translation pipeline using eight Python scripts, Marker for PDF extraction, Qwen 32B for translation with a global glossary, and Mistral 24B for style editing.

Persistent AI Advisor with Cross-Platform Memory: Tracks Decision History for 3 Months
A Reddit user built a persistent AI advisor that remembers every product decision across Claude Code, Cursor, and a web interface, catching contradictions and improving over months.

mycrab.space introduces SKILL.md and Prompt Autocomposer for standardized app deployment
mycrab.space has released SKILL.md, a Markdown blueprint for defining app dependencies and configuration, and a Prompt Autocomposer that generates ready-to-use deployment commands from these files. The system enables zero-config deployment of applications like VS Code in browser, personal music clouds, and AI agent interfaces.