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corebasehq/coremcp

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CoreMCP: Connect Legacy Databases to AI Agents via Model Context Protocol. Open-source bridge for LLM data analysis.

C

MCP

corebasehq/coremcp

Added 1 June 2026

#database-bridge #golang #legacy-systems #llm-ops #mcp #mcp-server #mssql

Overview

CoreMCP is an open-source bridge written in Go that connects legacy databases to AI agents using the Model Context Protocol. It enables LLMs to perform data analysis on existing database systems without migration. The tool acts as a middleware translating database queries into MCP-compatible interactions.

Best for

Best for
Developers needing to connect legacy databases to AI agents via MCP

Use cases

  • Query legacy databases from AI agents via MCP
  • Enable LLM-driven data analysis on existing SQL databases
  • Integrate older database systems into modern AI workflows

Notes

CoreMCP is an open-source bridge written in Go that connects legacy databases to AI agents using the Model Context Protocol. It enables LLMs to perform data analysis on existing database systems without migration. The tool acts as a middleware translating database queries into MCP-compatible interactions.

3 stars on GitHub. Last updated 2026-05-27. Licensed Apache-2.0.

Use cases

  • Query legacy databases from AI agents via MCP
  • Enable LLM-driven data analysis on existing SQL databases
  • Integrate older database systems into modern AI workflows

Pros

  • Open-source and free to use
  • Written in Go, offering good performance and concurrency
  • Provides a standardized MCP interface for database access

Cons

  • Very early stage with only 3 GitHub stars, limited community and support
  • Requires understanding of both MCP and legacy database specifics
  • May lack comprehensive documentation and production readiness

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

Pros

  • Open-source and free to use
  • Written in Go, offering good performance and concurrency
  • Provides a standardized MCP interface for database access

Cons

  • Very early stage with only 3 GitHub stars, limited community and support
  • Requires understanding of both MCP and legacy database specifics
  • May lack comprehensive documentation and production readiness