deadends.dev
About
Structured failure knowledge infrastructure for AI agents — dead ends, workarounds, and error transition graphs.
Details
- Author
- dbwls99706
- Downloads
- 229
- Categories
- Other, Developer Tools, AI
Jump to
- 90% Precision@1 and 0.935 MRR benchmark
- 2,204 canon entries across 54 domains and 39+ countries
- 11 MCP tools: lookup_error, get_error_detail, batch_lookup, etc.
- Deterministic, sub-millisecond local regex matching (no API roundtrip)
- Community-validated success rates that feed back into data
- Primary-sourced country canons citing government sites and embassies
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
deadends.devCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install via pip (pip install deadends-dev) and run deadends "error message" from the command line. Alternatively, integrate as an MCP server for Claude Desktop, Cursor, or Antigravity (remote HTTP) via configuration files or Smithery. Use the Python SDK with lookup, batch_lookup, and search functions for programmatic access.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"deadends.dev": {
"deadend": {
"command": "npx",
"args": [
"-y",
"@smithery/cli@latest",
"run",
"deadend/deadends-dev"
]
}
}
}
}
McpServers
{
"deadend": {
"command": "npx",
"args": [
"-y",
"@smithery/cli@latest",
"run",
"deadend/deadends-dev"
]
}
}
deadends.dev
<!-- mcp-name: dev.deadends/deadends-dev -->
Stop AI agents from repeating known failures - in code AND in the real world.
AI assistants reliably fumble two kinds of problems: known-failed code fixes, and
country-specific real-world rules they've never been exposed to in training.
deadends.dev now covers both:
- Code errors (2,089 entries, 51 domains): what NOT to try when an agent
hits ModuleNotFoundError, CUDA OOM, CrashLoopBackOff, etc.
- Country-scoped dead ends (250+ entries across 52 countries): visa rules
(ETA/eVisitor, NZeTA, e-visas, arrival cards), banking requirements, legal red
lines (lèse-majesté, §86a, Article 301), cultural taboos (chopsticks in rice,
clock gifts in China, red-ink names in Korea), food safety (tap-water safety by
country), emergency numbers, driving norms (left-hand traffic), housing
contracts - all the friction where a plausible-sounding global answer is wrong
locally.
> Why the expansion? Coding dead ends are largely solved by a good LLM.
> Country-specific friction - Japanese hanko requirements, Schengen 90/180
> math, Ramadan business hours, Saudi alcohol ban, Indian beef taboos - is
> where generic AI advice breaks hardest. The codebase and schema are
> identical; the env segment just carries a country code.
> 90% Precision@1 · 0.935 MRR · Data Quality Dashboard
> Website: deadends.dev · MCP Server: Smithery · PyPI: deadends-dev · API: /api/v1/index.json
> Repository: https://github.com/dbwls99706/deadends.dev
Why Use This?
| Without deadends.dev | With deadends.dev |
|---------------------|-------------------|
| Agent tries sudo pip install → breaks system Python → wastes 3 retries | Agent sees "dead end: sudo pip - fails 70%" → skips it immediately |
| Agent tells user to tip 15% at a Tokyo restaurant | Agent knows tipping is refused in Japan (culture/tipping-refused/jp) |
| Agent drafts a Thai social post referencing King Rama X | Agent stops: Article 112 lèse-majesté risk (legal/lese-majeste-article-112/th) |
| Agent fixes error A, gets confused by error B | Agent knows "A leads to B 78% of the time" → handles both |
| Agent tells unmarried couple to kiss publicly in Dubai | Agent flags UAE public decency law (legal/unmarried-public-affection/ae) |
What makes this different from asking an LLM?
- Deterministic: Same query → same answer, every time. No hallucination.
- Country-scoped: ID format {domain}/{slug}/{env} - env holds the country
code (kr, jp, us, de...) so the same taboo can be answered
differently for different jurisdictions.
- Primary-sourced: Every country canon cites government sites, embassies,
or verifiable reporting. No "based on general knowledge" answers.
- Community-validated: Fix success rates updated from real outcome reports.
- Sub-millisecond: Local regex matching, no API roundtrip.
현실적인 한계 (운영 관점)
- 모든 에러를 다 커버하지는 못합니다. 없는 케이스는 이슈/PR/report_outcome로 빠르게 보완합니다.
- 설명의 깊이보다 실전 해결 우선(dead end/workaround 중심)으로 설계되어 있습니다.
- 신뢰성은 도메인/케이스마다 다를 수 있으므로, 고위험 변경은 공식 문서/벤더 가이드와 교차 검증을 권장합니다.
Quick Start (30 seconds)
pip install deadends-dev
deadends "CUDA error: out of memory"
MCP Server (Claude Desktop / Cursor)
Add to ~/.claude/claude_desktop_config.json:
{
"mcpServers": {
"deadend": {
"command": "python",
"args": ["-m", "mcp.server"],
"cwd": "/path/to/deadends.dev"
}
}
}
Or install via Smithery (no local setup):
npx -y @smithery/cli@latest install deadend/deadends-dev --client claude
MCP Unauthorized 빠른 해결 가이드 (사람용)
deadend: calling "initialize": sending "initialize": Unauthorized 에러가 보이면 아래를 순서대로 그대로 실행/확인하세요.
1) 로컬 서버 모드인지, 원격(Smithery) 모드인지 하나만 사용
```bash
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.





