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hoklims/stacksfinder-mcp

by Various

MCP server for StacksFinder - deterministic tech stack recommendations for LLM clients

H

MCP

hoklims/stacksfinder-mcp

Added 1 June 2026

Overview

hoklims/stacksfinder-mcp is an MCP server that provides deterministic tech stack recommendations for LLM clients. It implements the Model Context Protocol to allow AI assistants to query stack suggestions programmatically.

Best for

Best for
Developers building LLM-based tooling that need consistent, deterministic tech stack suggestions

Use cases

  • Integrating stack recommendations into an LLM-powered coding assistant
  • Automating tech stack selection during project scaffolding
  • Evaluating consistent stack options across multiple LLM sessions

How to use

Install

bun install

Tools exposed

  • list_technologies
  • analyze_tech
  • compare_techs
  • recommend_stack
  • estimate_project
  • get_estimate_quota
  • get_blueprint
  • create_blueprint
  • setup_api_key
  • list_api_keys
  • revoke_api_key
  • create_audit
  • get_audit
  • list_audits
  • compare_audits
  • get_audit_quota
  • get_migration_recommendation
  • generate_mcp_kit
  • analyze_repo_mcps
  • prepare_mcp_installation

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, VS Code, ChatGPT

Notes

hoklims/stacksfinder-mcp is an MCP server that provides deterministic tech stack recommendations for LLM clients. It implements the Model Context Protocol to allow AI assistants to query stack suggestions programmatically.

8 stars on GitHub. Last updated 2026-01-29. Licensed MIT.

Use cases

  • Integrating stack recommendations into an LLM-powered coding assistant
  • Automating tech stack selection during project scaffolding
  • Evaluating consistent stack options across multiple LLM sessions

Pros

  • Deterministic output ensures repeatable recommendations
  • Lightweight TypeScript implementation
  • Integrates directly with LLM clients via MCP

Cons

  • Low GitHub stars indicate limited community adoption
  • Dependent on external StackFinder service availability
  • Only supports MCP protocol, limiting integration options

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

Pros

  • Deterministic output ensures repeatable recommendations
  • Lightweight TypeScript implementation
  • Integrates directly with LLM clients via MCP

Cons

  • Low GitHub stars indicate limited community adoption
  • Dependent on external StackFinder service availability
  • Only supports MCP protocol, limiting integration options
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