pg-mnemosyne-mcp

pg-mnemosyne-mcp

🧠 A high-performance PostgreSQL-backed MCP server acting as a super memory, task tracker, and dynamic database manager for AI agents. Features built-in connection pooling, a professional tasks schema, and a unique shared multi-agent coordination hub to prevent coding conflicts in real-time.

Category
Visit Server

README

Pg-Mnemosyne MCP

PyPI version License: MIT Python Version MCP Protocol Platform Support

<p align="center"> <img src="https://raw.githubusercontent.com/Janadasroor/pg-mnemosyne-mcp/main/assets/mcp_power_banner.png" alt="Pg-Mnemosyne MCP Power Banner" width="100%"> </p>

A Model Context Protocol (MCP) server that provides AI assistants with a robust "super memory", task tracker, and dynamic PostgreSQL database management capabilities.

⚡ Quick Start

  1. Install the package globally:

    • Windows:
      pip install pg-mnemosyne-mcp
      
    • macOS / Linux:
      pipx install pg-mnemosyne-mcp
      
      (If you prefer standard pip or don't have pipx, run: pip install pg-mnemosyne-mcp --break-system-packages)
  2. Auto-configure all your AI agents (Claude, Gemini, Qwen, Cursor, etc.) at once:

    pg-mnemosyne init --dsn "postgresql://user:password@localhost:5432/postgres"
    

    (Be sure to replace user and password with your actual PostgreSQL username and database password!)

  3. Restart your AI agents. You're done!


Features

  • High-Performance: Uses cached connection pooling (asyncpg.create_pool) for instant sub-millisecond database queries.
  • Dynamic Projects: The AI can create new databases for different projects on the fly.
  • Dynamic Schema: The AI can modify table schemas dynamically to adapt to changing memory needs.
  • Standard Memory Tracker: Built-in support for tracking, updating, and deleting memory items with tags.
  • Advanced Task Management: Dedicated tasks schema with fields for status transitions, priority, and deadlines.
  • Multi-Agent Coordination: Centralized session tracking preventing duplicate coding and file-editing conflicts.
  • Raw SQL Execution: Gives AI ultimate flexibility for complex queries and DDL operations.

Setup

Users will need to provide their PostgreSQL credentials using the PG_BASE_DSN environment variable. This is a standard connection string: postgresql://<USERNAME>:<PASSWORD>@<HOST>:<PORT>/<DEFAULT_DB>

Where to configure this (Client Setup)

The exact location depends on which AI client you are using. You need to add the server configuration to your client's MCP settings file.

For Claude Desktop:

  • Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json

For Cursor:

  • Go to Settings > Features > MCP and add a new MCP server, or edit your project's .cursor/mcp.json.

For Roo Code / Cline (VS Code):

  • Edit the MCP settings file located at ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json (Mac) or the equivalent Windows path.

For Gemini CLI & Qwen CLI:

  • Open your global configuration file (usually located at ~/.gemini/settings.json or ~/.qwen/settings.json).
  • Alternatively, use the CLI:
    gemini mcp add pg-mnemosyne "/path/to/pg-mnemosyne" -e PG_BASE_DSN="postgresql://user:pass@localhost:5432/postgres" -s user
    # OR
    qwen mcp add pg-mnemosyne "/path/to/pg-mnemosyne" -e PG_BASE_DSN="postgresql://user:pass@localhost:5432/postgres" -s user
    

For Claude Code CLI:

  • The easiest way is to add it via the CLI:
    claude mcp add pg-mnemosyne "/path/to/pg-mnemosyne" -e PG_BASE_DSN="postgresql://user:pass@localhost:5432/postgres" -s user
    
  • Manually, it lives in your global config at ~/.claude.json.

For Codex CLI:

  • The easiest way is to add it via the CLI:
    codex mcp add pg-mnemosyne --env PG_BASE_DSN="postgresql://user:pass@localhost:5432/postgres" -- pg-mnemosyne
    
  • Manually, it lives in your global config at ~/.codex/config.toml (TOML format).

For Windsurf IDE:

  • Edit your global config at ~/.codeium/windsurf/mcp_config.json.
  • Alternatively, click the Hammer (MCP) icon in the Cascade panel and select Configure.

For Antigravity CLI (agy): Antigravity uses a plugin-based system. To add the server:

  1. Create a plugin directory: mkdir -p ~/.gemini/config/plugins/pg-mnemosyne
  2. Create ~/.gemini/config/plugins/pg-mnemosyne/mcp_config.json with the Standard Template below.
  3. Add an entry to your ~/.gemini/config/import_manifest.json under the "imports" array:
    {
      "name": "pg-mnemosyne",
      "source": "manual",
      "components": ["mcpServers"]
    }
    

Configuration Template (Claude Desktop, Cursor, Roo Code, Gemini CLI, Claude Code, Antigravity, Windsurf):

{
  "mcpServers": {
    "pg-mnemosyne": {
      "command": "pg-mnemosyne",
      "env": {
        "PG_BASE_DSN": "postgresql://postgres:my_password@localhost:5432/postgres"
      }
    }
  }
}

For OpenCode:

  • Edit your OpenCode configuration file located at ~/.config/opencode/opencode.jsonc.

Configuration Template (OpenCode):

{
  "mcp": {
    "pg-mnemosyne": {
      "type": "local",
      "command": ["pg-mnemosyne"],
      "environment": {
        "PG_BASE_DSN": "postgresql://postgres:my_password@localhost:5432/postgres"
      }
    }
  }
}

Running the Server (Standalone)

pg-mnemosyne run

This starts the MCP server using standard input/output.

CLI Usage

The pg-mnemosyne command also acts as a standalone CLI for managing your data and configuring agents.

Auto-Initialization

You can automatically configure all supported AI agents (Claude, Gemini, Qwen, Cursor, etc.) with a single command:

pg-mnemosyne init --dsn "postgresql://user:pass@localhost:5432/postgres"

Manual Record Management

You can add and list records directly from your terminal:

# Add a record
pg-mnemosyne add my_project_db todo "Finish the documentation"

# List records
pg-mnemosyne list my_project_db --type todo

🤝 Multi-Agent Coordination & Advanced Tasks

Pg-Mnemosyne includes specialized schemas to help complex multi-agent setups (e.g. Gemini CLI, Codex CLI, Roo Code, Claude Desktop) coordinate on the same project:

📋 Professional Tasks Schema

Spin up a dedicated tasks table with fields for statuses (backlog, todo, in_progress, blocked, done), priority levels (low, medium, high, critical), tags, and deadlines:

pg-mnemosyne init-todo my_project_db

🛰️ Agent Coordination Hub

Avoid merge conflicts, double-coding, and redundant compiler troubleshooting by initializing the shared agent_sessions coordination table:

pg-mnemosyne init-coordination my_project_db

When active, agents use the update_agent_session and get_active_sessions MCP tools to register their current editing files and active subtasks, creating a real-time bulletin board for mutual visibility!

Available MCP Tools

  • create_project_db(db_name: str): Creates a new isolated PostgreSQL database.
  • init_schema(db_name: str): Initializes the base records table.
  • init_todo_schema(db_name: str): Initializes a professional tasks table.
  • init_coordination_schema(db_name: str): Initializes the multi-agent agent_sessions table.
  • add_column(db_name: str, table: str, column_name: str, data_type: str): Dynamically adds a column to any table.
  • add_record(db_name: str, type: str, content: str, tags: list[str]): Adds a memory/todo record.
  • get_records(db_name: str, type: str = None, limit: int = 50): Retrieves recent records.
  • update_record(db_name: str, record_id: int, content: str = None, tags: list[str] = None, status: str = None): Partially updates a record.
  • delete_record(db_name: str, record_id: int): Deletes a record by ID.
  • update_agent_session(db_name: str, agent_name: str, active_task: str, active_file: str = None, status: str = "active"): Registers/updates active agent state.
  • get_active_sessions(db_name: str): Lists active agent coordination sessions.
  • run_sql(db_name: str, query: str): Runs arbitrary SQL (SELECT, INSERT, DDL, etc.).

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured