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tosin2013/mcp-adr-analysis-server

by Various

A sophisticated Model Context Protocol (MCP) server for analyzing Architectural Decision Records (ADRs) and providing deep architectural insights to AI agents.

T

MCP

tosin2013/mcp-adr-analysis-server

Added 1 June 2026

#adr #ai-agents #architectural-decision-records #architecture #claude #cursor #mcp-server #typescript

Overview

An open-source Model Context Protocol (MCP) server that analyzes Architectural Decision Records (ADRs) and surfaces architectural insights to AI agents. Built in TypeScript, it enables AI tools to query and reason over ADR content.

Best for

Best for
Developers and architects who want to integrate ADR analysis into AI-assisted workflows

Use cases

  • Feed ADRs into an AI coding assistant to inform architecture decisions
  • Automate review of ADRs for consistency and completeness
  • Provide architectural context to AI agents during code generation or refactoring

Notes

An open-source Model Context Protocol (MCP) server that analyzes Architectural Decision Records (ADRs) and surfaces architectural insights to AI agents. Built in TypeScript, it enables AI tools to query and reason over ADR content.

28 stars on GitHub. Last updated 2026-05-26. Licensed MIT.

Use cases

  • Feed ADRs into an AI coding assistant to inform architecture decisions
  • Automate review of ADRs for consistency and completeness
  • Provide architectural context to AI agents during code generation or refactoring

Pros

  • Specialized for ADR analysis, a niche but valuable use case
  • Leverages the MCP standard for interoperability with AI agents
  • Open source with a clear focus and TypeScript codebase

Cons

  • Small community (28 stars) limits support and contributions
  • Requires an MCP-compatible AI agent to be useful
  • Early-stage project with potentially limited documentation and stability

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

Pros

  • Specialized for ADR analysis, a niche but valuable use case
  • Leverages the MCP standard for interoperability with AI agents
  • Open source with a clear focus and TypeScript codebase

Cons

  • Small community (28 stars) limits support and contributions
  • Requires an MCP-compatible AI agent to be useful
  • Early-stage project with potentially limited documentation and stability