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Give AI agents long-term memory with semantic graph and consolidation.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "SMRITI Memory" MCP server from askskill: Run: claude mcp add 'io-github-smriti-memcore-smriti-memory' -- npx -y smriti-memcore
Use SMRITI Memory to store long-term memory for my AI support agent: the user prefers concise replies, and common topics are subscriptions and refunds. Create relevant semantic links.
Stored memory entries plus a description of semantic links between preferences and topics.
Retrieve from SMRITI Memory the memories most relevant to “refund policy” and “the user prefers concise replies” for this response.
A summary of relevant memories to keep the conversation consistent and personalized.
Consolidate this agent’s recently accumulated memories, merge duplicates, and strengthen semantic graph links related to product feedback.
An updated memory structure with fewer duplicates and improved future retrieval quality.
Developers building chat agents can use it to preserve important information across turns and sessions. This helps the agent produce more consistent responses from long-term memory.
Researchers can store key information in an agent’s memory as a semantic graph. This helps later retrieval of related concepts and preserves contextual connections.
In automation flows that need long-term tracking of state or preferences, it can provide persistent memory and consolidation for agents. It is useful for reducing duplicate records and improving continuity in later tasks.
It is a long-term memory tool for AI agents. Based on the description, it focuses on neuro-inspired memory, semantic graphs, and memory consolidation.
It suits projects where AI agents need to remember past information, build semantic links, and reuse memories in later tasks. Examples include conversational, research, or automation agents.
The provided material does not include installation steps, runtime requirements, or key requirements. For prerequisites and deployment details, see the source repository.
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