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open-memory-local-manager

Manage memories in an OpenMemory Local MCP server with semantic search.

Updated Aug 23, 2026

Search Tags:#search #mcp #memory #connectivity #local #storage

One-click install

npx skills add https://github.com/contextware/skills --skill open-memory-local-manager

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: open-memory-local-manager
Source: https://github.com/contextware/skills/tree/main/skills/open-memory-local-manager
Command: npx skills add https://github.com/contextware/skills --skill open-memory-local-manager

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and scenarios (resource) components.

What problem does it solve?

This Skill simplifies the process of interacting with the OpenMemory Local MCP server, ensuring reliable connectivity and efficient memory management for your AI agent.

Core Features & Use Cases

Automated Connectivity Checks: Verifies server accessibility and API key validity before operations.
Semantic Search: Enables powerful searching of stored memories.
Memory Storage & Listing: Provides straightforward methods to store new facts and retrieve existing ones.
Use Case: An agent needs to recall past conversations or facts about a specific topic. This Skill allows the agent to query the OpenMemory Local server to retrieve relevant information, ensuring contextually aware responses.

Quick Start

Use the open-memory-local-manager skill to search for memories related to 'project deadlines'.

Frequently Asked Questions about open-memory-local-manager

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I connect an AI agent to an OpenMemory Local MCP server?▼

To connect to an OpenMemory Local MCP server, use a Node.js script to verify server accessibility and validate the static x-api-key header before executing memory operations.

How does semantic search work for memories stored in OpenMemory Local?▼

Semantic search in OpenMemory Local works by using the openmemory_query tool to retrieve relevant stored facts based on topic context, enabling contextually aware agent responses.

What's the best way to store and list memories via an MCP server?▼

The best way to store and list memories via an MCP server is using the openmemory_store and openmemory_list tools, which provide structured storage patterns for new facts and retrieval of existing ones.

Do I need an API key to perform local memory storage and queries?▼

Yes, you need an API key to perform local memory storage and queries, as OpenMemory Local requires static header authentication via an x-api-key for all connectivity and operations.