PostgreSQL MCP server providing persistent super memory, task tracking, and multi-agent coordination for AI assistants.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
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๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Pg Mnemosyne MCP.
recordsCallable MCP tool function
tasksCallable MCP tool function
agent_sessionsCallable MCP tool function
A Model Context Protocol (MCP) server that provides AI assistants with a robust "super memory", task tracker, and dynamic PostgreSQL database management capabilities.
Install the package globally:
pipx, run: pip install pg-mnemosyne-mcp --break-system-packages)Auto-configure all your AI agents (Claude, Gemini, Qwen, Cursor, etc.) at once:
(Be sure to replace user and password with your actual PostgreSQL username and database password!)
Restart your AI agents. You're done!
asyncpg.create_pool) for instant sub-millisecond database queries.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>
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:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonFor Cursor:
Settings > Features > MCP and add a new MCP server, or edit your project's .cursor/mcp.json.For Roo Code / Cline (VS Code):
~/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:
~/.gemini/settings.json or ~/.qwen/settings.json).For Claude Code CLI:
~/.claude.json.For Codex CLI:
~/.codex/config.toml (TOML format).For Windsurf IDE:
~/.codeium/windsurf/mcp_config.json.For Antigravity CLI (agy): Antigravity uses a plugin-based system. To add the server:
mkdir -p ~/.gemini/config/plugins/pg-mnemosyne~/.gemini/config/plugins/pg-mnemosyne/mcp_config.json with the Standard Template below.~/.gemini/config/import_manifest.json under the "imports" array:
Configuration Template (Claude Desktop, Cursor, Roo Code, Gemini CLI, Claude Code, Antigravity, Windsurf):
For OpenCode:
~/.config/opencode/opencode.jsonc.Configuration Template (OpenCode):
This starts the MCP server using standard input/output.
The pg-mnemosyne command also acts as a standalone CLI for managing your data and configuring agents.
You can automatically configure all supported AI agents (Claude, Gemini, Qwen, Cursor, etc.) with a single command:
You can add and list records directly from your terminal:
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:
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:
Avoid merge conflicts, double-coding, and redundant compiler troubleshooting by initializing the shared agent_sessions coordination table:
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!
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.).Factual signals from GitHub, npm, and our automated checks โ not a rating.
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