---
name: mastra-libsql
description: Documentation for @mastra/libsql. Use when working with @mastra/libsql APIs, configuration, or implementation.
metadata:
  package: "@mastra/libsql"
  version: "1.9.0"
---

## When to use

Use this skill whenever you are working with @mastra/libsql to obtain the domain-specific knowledge.

## How to use

Read the individual reference documents for detailed explanations and code examples.

### Docs

- [Agent approval](references/docs-agents-agent-approval.md) - Learn how to require approvals, suspend tool execution, and automatically resume suspended tools while keeping humans in control of agent workflows.
- [Agent networks](references/docs-agents-networks.md) - Coordinate multiple agents, workflows, and tools using agent networks for complex, non-deterministic task execution.
- [Memory processors](references/docs-memory-memory-processors.md) - Learn how to use memory processors in Mastra to filter, trim, and transform messages before they're sent to the language model to manage context window limits.
- [Message history](references/docs-memory-message-history.md) - Learn how to configure message history in Mastra to store recent messages from the current conversation.
- [Memory overview](references/docs-memory-overview.md) - Learn how Mastra's memory system works with working memory, message history, semantic recall, and observational memory.
- [Semantic recall](references/docs-memory-semantic-recall.md) - Learn how to use semantic recall in Mastra to retrieve relevant messages from past conversations using vector search and embeddings.
- [Storage](references/docs-memory-storage.md) - Configure storage for Mastra to persist conversations and other runtime state.
- [Working memory](references/docs-memory-working-memory.md) - Learn how to configure working memory in Mastra to store persistent user data, preferences.
- [Retrieval, semantic search, reranking](references/docs-rag-retrieval.md) - Guide on retrieval processes in Mastra's RAG systems, including semantic search, filtering, and re-ranking.
- [Snapshots](references/docs-workflows-snapshots.md) - Learn how to save and resume workflow execution state with snapshots in Mastra

### Guides

- [AI SDK](references/guides-agent-frameworks-ai-sdk.md) - Use Mastra processors and memory with the Vercel AI SDK

### Reference

- [Reference: Mastra.getMemory()](references/reference-core-getMemory.md) - Documentation for the `Mastra.getMemory()` method in Mastra, which retrieves a registered memory instance by its registry key.
- [Reference: Mastra.listMemory()](references/reference-core-listMemory.md) - Documentation for the `Mastra.listMemory()` method in Mastra, which returns all registered memory instances.
- [Reference: Mastra class](references/reference-core-mastra-class.md) - Documentation for the `Mastra` class in Mastra, the core entry point for managing agents, workflows, MCP servers, and server endpoints.
- [Reference: Memory class](references/reference-memory-memory-class.md) - Documentation for the `Memory` class in Mastra, which provides a robust system for managing conversation history and thread-based message storage.
- [Reference: Composite storage](references/reference-storage-composite.md) - Documentation for combining multiple storage backends in Mastra.
- [Reference: DynamoDB storage](references/reference-storage-dynamodb.md) - Documentation for the DynamoDB storage implementation in Mastra, using a single-table design with ElectroDB.
- [Reference: libSQL storage](references/reference-storage-libsql.md) - Documentation for the libSQL storage implementation in Mastra.
- [Reference: libSQL vector store](references/reference-vectors-libsql.md) - Documentation for the LibSQLVector class in Mastra, which provides vector search using libSQL with vector extensions.


Read [assets/SOURCE_MAP.json](assets/SOURCE_MAP.json) for source code references.