# Build SQL and vector retrieval context layers with TiDB

> Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.

- Skill: `agentskillexchange/build-sql-and-vector-retrieval-context-layers-with-tidb` (Agent Skill)
- Install (CLI): `npx skillmds@latest add agentskillexchange/build-sql-and-vector-retrieval-context-layers-with-tidb`
- Raw SKILL.md: https://api.skillmd.com/api/skills/agentskillexchange/build-sql-and-vector-retrieval-context-layers-with-tidb/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: agentskillexchange (https://skillmd.com/u/agentskillexchange)
- Updated: 2026-09-08
- Page: https://skillmd.com/skills/agentskillexchange/build-sql-and-vector-retrieval-context-layers-with-tidb

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# Build SQL and vector retrieval context layers with TiDB

Use TiDB when an agent needs one transactional SQL store that can also hold embeddings and serve vector retrieval for RAG, memory, or app-context workflows.

## Prerequisites

TiDB or TiDB Cloud, an embedding model, SQL client or application connector, source documents or application records

## Installation

No source-backed install or usage instructions could be extracted automatically. Review the upstream project before running this skill in a sensitive workflow.

- Source: https://github.com/pingcap/tidb

## Documentation

- https://docs.pingcap.com/tidb/stable/vector-search-overview/

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/build-sql-and-vector-retrieval-context-layers-with-tidb/)