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Give agents local memory, recall, search, context, and graph traversal tools.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.gowtham0992/link" MCP server from askskill: Run: claude mcp add 'io-github-gowtham0992-link' -- npx -y link-mcp
Please store “I prefer concise answers and Chinese by default” in local memory and prioritize these preferences in future conversations.
The tool stores a local memory entry and can recall these preferences in later conversations.
Search the remembered content related to “API authentication strategy” and summarize the most relevant points.
It returns relevant memory results with a brief summary or useful pointers.
Starting from “Project Alpha,” traverse the related memory graph and find nodes about the owner, deadline, and risks.
It outputs connected memory nodes and their relationship paths for the target topic.
Developers can use it to preserve user preferences, task background, and past conclusions for agents, reducing repeated context sharing. It fits scenarios where memory must persist across sessions.
In research or product work, an agent can search local memory before answering based on matched context. This helps recover previously recorded information faster.
When information has topic or entity relationships, graph traversal can expand from one memory node to related ones. It is useful for mapping context relationships and tracing connected clues.
It is an MCP tool for agents that provides local personal memory. It supports remembering, recalling, searching context, and graph traversal.
Based on the description, it is suited for storing and retrieving agent-related context such as preferences, past conclusions, and linked clues. For specific data structures and limits, see the source repository.
The provided material does not include installation steps, runtime requirements, or API key details. Please see the source repository for prerequisites.
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