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SurajKGoyal/amnesic

by Various

Persistent semantic memory for SQL databases (Postgres, MySQL, MSSQL, SQLite) — the MCP server with the most ironic name. One-line install for Claude Code, Cursor, and any MCP-comp

S

MCP

SurajKGoyal/amnesic

Added 23 June 2026

#ai-tools #claude #cursor #database #fastmcp #llm #mcp #model-context-protocol

Overview

Amnesic is an MCP server that provides persistent semantic memory for SQL databases including PostgreSQL, MySQL, MSSQL, and SQLite. It installs with a single line and works with Claude Code, Cursor, and other MCP-compatible clients.

Best for

Best for
Developers who need persistent memory for MCP-based agents using SQL databases

Use cases

  • Attach long-term memory to SQL-based tools
  • Enable Claude Code to retain context across sessions
  • Build memory-augmented workflows with MCP clients

Notes

Amnesic is an MCP server that provides persistent semantic memory for SQL databases including PostgreSQL, MySQL, MSSQL, and SQLite. It installs with a single line and works with Claude Code, Cursor, and other MCP-compatible clients.

0 stars on GitHub. Last updated 2026-06-23. Licensed MIT.

Use cases

  • Attach long-term memory to SQL-based tools
  • Enable Claude Code to retain context across sessions
  • Build memory-augmented workflows with MCP clients

Pros

  • Supports multiple SQL backends (Postgres, MySQL, MSSQL, SQLite)
  • One-line install simplifies integration with popular MCP clients
  • Open source (Python) for customization

Cons

  • GitHub stars at 0 indicates early stage
  • Requires a running SQL database server
  • Semantic memory performance depends on chosen database

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

Pros

  • Supports multiple SQL backends (Postgres, MySQL, MSSQL, SQLite)
  • One-line install simplifies integration with popular MCP clients
  • Open source (Python) for customization

Cons

  • GitHub stars at 0 indicates early stage
  • Requires a running SQL database server
  • Semantic memory performance depends on chosen database

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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