Deadends Dev

@dbwls99706

About Deadends Dev

Structured failure knowledge infrastructure for AI agents — dead ends, workarounds, and error transition graphs.

#error-handling #debugging #mcp #ai-agent #python #docker #kubernetes #troubleshooting

Config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "deadend": {
      "command": "npx",
      "args": [
        "-y",
        "@smithery/cli@latest",
        "run",
        "deadend/deadends-dev"
      ]
    }
  }
}

Tools

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Overview

What is Deadends Dev?

Deadends Dev is an MCP server that provides a database of known errors and dead ends for AI agents, covering both code failures and country-specific real-world rules. It helps agents avoid repeating known failures by offering deterministic, community-validated advice.

How to use Deadends Dev?

Install via pip with pip install deadends-dev, then invoke commands like deadends "error message". For MCP integration, add the server configuration to ~/.claude/claude_desktop_config.json or install via Smithery. The server provides 11 tools accessible via MCP clients.

Key features of Deadends Dev

Deterministic answers with no hallucination
Country-scoped data using ISO alpha-2 codes
Primary-sourced from government and verifiable sources
Community-validated fix success rates
Sub-millisecond local regex matching
Over 2,200 canon entries across 54 domains

Use cases of Deadends Dev

Prevent agents from trying sudo pip install that fails 70% of the time
Avoid AI advice to tip in Japan where tipping is culturally refused
Flag legal risks like Article 112 lèse-majesté in Thailand
Handle error transitions where one fix triggers another error
Stop agents from suggesting public displays of affection in UAE

FAQ from Deadends Dev

What makes Deadends Dev different from asking an LLM?

Deadends Dev provides deterministic answers (same query, same result) with no hallucination, country-scoped data, primary-sourced references, community-validated success rates, and sub-millisecond local response.

What are the practical limitations of Deadends Dev?

The dataset does not cover every error; missing cases can be added via issues, PRs, or the report_outcome tool. It prioritizes practical dead ends and workarounds over deep explanations. Reliability varies by domain and case; high-risk changes should be cross-verified with official sources.

How can I resolve "Unauthorized" errors when using the MCP server?

Common causes include wrong cwd path, running both local and remote (Smithery) modes simultaneously, or expired authentication. Ensure only one mode is active, verify the configuration file, and

Frequently asked questions

What makes Deadends Dev different from asking an LLM?

What are the practical limitations of Deadends Dev?

The dataset does not cover every error; missing cases can be added via issues, PRs, or the `report_outcome` tool. It prioritizes practical dead ends and workarounds over deep explanations. Reliability varies by domain and case; high-risk changes should be cross-verified with official sources.

How can I resolve "Unauthorized" errors when using the MCP server?

Common causes include wrong `cwd` path, running both local and remote (Smithery) modes simultaneously, or expired authentication. Ensure only one mode is active, verify the configuration file, and

Comments

Basic information

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