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  1. Home
  2. ๐Ÿ—„๏ธ Databases
  3. Pg Mnemosyne MCP
Pg Mnemosyne MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 6:48:07 PM

Pg Mnemosyne MCP

User RatingsBe the first to rate and review this MCP server!
View Repository3 GitHub StarsTotal stargazers on GitHub for the source repository (3 stars).Visit Website
postgresqldatabasememorytask-trackingmulti-agent

PostgreSQL MCP server providing persistent super memory, task tracking, and multi-agent coordination for AI assistants.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "janadasroor-pg-mnemosyne-mcp": {
      "command": "uvx",
      "args": [
        "pg-mnemosyne-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (3) Directory Badge Claim listing Alternatives๐Ÿ—„๏ธ More in Databases

Overview

This MCP server uses PostgreSQL to offer AI assistants a persistent super memory, dynamic task management, and multi-agent coordination. It supports dynamic creation of databases and schemas, allowing AI agents to adapt memory structures on the fly. Use it when you need a robust, scalable backend for AI memory, task tracking, and preventing conflicts in multi-agent workflows.

Use cases

โ€ขStore and retrieve persistent AI memory with tagging
โ€ขTrack and manage tasks with status, priority, and deadlines
โ€ขCoordinate multiple AI agents to avoid duplicate work
โ€ขDynamically create and modify project-specific databases and schemas
โ€ขExecute raw SQL queries for advanced data operations

Key features

โ€ขCached connection pooling with asyncpg for sub-millisecond queries
โ€ขDynamic database and schema creation/modification by AI
โ€ขStandard memory item tracking with tags
โ€ขAdvanced task management schema supporting status transitions and deadlines
โ€ขMulti-agent session tracking to prevent conflicts
โ€ขRaw SQL execution capability for complex queries and DDL

Capabilities & Tool Schemas (3) ~7 tokensApproximate context cost of this serverโ€™s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Self-reported Self-reportedParsed from the repository README, not verified against a live server โ€” may be incomplete or out of date.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Pg Mnemosyne MCP.

records

Callable MCP tool function

tasks

Callable MCP tool function

agent_sessions

Callable MCP tool function

Documentation Overview

Pg-Mnemosyne MCP

PyPI version License: MIT Python Version MCP Protocol Platform Support

Pg-Mnemosyne MCP Power Banner

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

โšก Quick Start

  1. Install the package globally:

    • Windows:
      Terminal
      pip install pg-mnemosyne-mcp
      
    • macOS / Linux:
      bash
      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:

    bash
    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:
    bash
    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:
    Terminal
    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:
    bash
    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:
    config.json
    {
      "name": "pg-mnemosyne",
      "source": "manual",
      "components": ["mcpServers"]
    }
    

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

config.json
{
  "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):

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

Running the Server (Standalone)

bash
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:

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

Manual Record Management

You can add and list records directly from your terminal:

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

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

๐Ÿค 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:

๐Ÿ“‹ 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:

bash
pg-mnemosyne init-todo my_project_db

๐Ÿ›ฐ๏ธ Agent Coordination Hub

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

bash
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.).

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
3
Stargazers on the source repository.
Last commit
3mo ago
Most recent push to the default branch.
Tools exposed
3
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Pg Mnemosyne MCP

Set the PG_BASE_DSN environment variable with your PostgreSQL connection string in the format postgresql://<USERNAME>:<PASSWORD>@<HOST>:<PORT>/<DEFAULT_DB>.

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Technical Specs & Signals

Category๐Ÿ—„๏ธDatabases
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsClaude Desktop, Cursor, Windsurf, Cline / VS Code
Last updatedAug 9, 2026
11/11 checks healthy over the last 33d
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars3
GitHub Star CountTotal stargazers on GitHub representing community popularity (3 stars).
Last commit3mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on May 26, 2026
52Quality signal: Good ยท 52/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools27/30
Adoption & activity2/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 23d ago via OSV.dev ยท pg-mnemosyne-mcp (PyPI)

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