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TimurRakhmatullin86/mcp-drill

by Various

Fault injection and reliability scoring for MCP servers

MCP

TimurRakhmatullin86/mcp-drill

Added 13 Sept 2026

#ai-agents #chaos-engineering #fault-injection #llm #mcp #model-context-protocol #reliability #testing

Overview

mcp-drill is a Python tool for fault injection and reliability scoring of MCP servers. It lets developers simulate failures and assess how a server behaves under degraded conditions. The project is hosted on GitHub under the name TimurRakhmatullin86/mcp-drill.

Best for

Best for
Developers building or operating MCP servers who need lightweight fault injection and reliability checks

Use cases

  • Inject faults into MCP server responses
  • Run reliability scoring during development
  • Test server behavior under simulated failure conditions

How to use

Install

uvx mcp-drill wrap --faults timeout,corrupt -- npx -y @modelcontextprotocol/server-filesystem /tmp

Notes

mcp-drill is a Python tool for fault injection and reliability scoring of MCP servers. It lets developers simulate failures and assess how a server behaves under degraded conditions. The project is hosted on GitHub under the name TimurRakhmatullin86/mcp-drill.

1 stars on GitHub. Last updated 2026-09-09. Licensed Apache-2.0.

Use cases

  • Inject faults into MCP server responses
  • Run reliability scoring during development
  • Test server behavior under simulated failure conditions

Pros

  • Focused scope on MCP server reliability
  • Simple Python-based tooling
  • Open-source code available for inspection

Cons

  • Very early stage with limited community adoption
  • No release history or usage examples in the provided information
  • Limited to fault injection and scoring rather than a broader testing suite

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Focused scope on MCP server reliability
  • Simple Python-based tooling
  • Open-source code available for inspection

Cons

  • Very early stage with limited community adoption
  • No release history or usage examples in the provided information
  • Limited to fault injection and scoring rather than a broader testing suite
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