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Add Postgres-native vector retrieval to agent and RAG workflows with pgvector

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

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agentskillexchange/skills 45 57 forks MIT Updated 2d ago

Part of agentskillexchange/skills — 249 skills

Install

skills CLI

npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/add-postgres-native-vector-retrieval-to-agent-and-rag-workflows-with-pgvector

Claude Code

claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install agentskillexchange-skills@llmmart

Git git clone https://github.com/agentskillexchange/skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole agentskillexchange/skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

Add Postgres-native vector retrieval to agent and RAG workflows with pgvector

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Prerequisites

Postgres 13+, pgvector extension, SQL access to the target database, embeddings from the agent or RAG pipeline, and application code that can query Postgres

Installation

Use the upstream install or setup path that matches your environment:

git clone --branch v0.8.2 https://github.com/pgvector/pgvector.git
make
make install # may need sudo
Then re-run the installation instructions (run make clean before make if needed). If sudo is needed for make install, use:

Requirements and caveats from upstream:

You can also install it with Docker, Homebrew, PGXN, APT, Yum, pkg, APK, or conda-forge, and it comes preinstalled with [Postgres.app](#...
You can also install it with Docker or conda-forge.
Or load vectors in bulk using COPY (example)

Basic usage or getting-started notes:

Compile and install the extension (supports Postgres 13+)
cd /tmp
cd pgvector
Source: https://github.com/pgvector/pgvector
Extracted from upstream docs: https://raw.githubusercontent.com/pgvector/pgvector/HEAD/README.md

Documentation

https://github.com/pgvector/pgvector#readme

Source

Agent Skill Exchange

Files (skills)

SKILL.md 2.3 KB

---
name: "Add Postgres-native vector retrieval to agent and RAG workflows with pgvector"
slug: "add-postgres-native-vector-retrieval-to-agent-and-rag-workflows-with-pgvector"
description: "Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval."
github_stars: 21709
verification: "security_reviewed"
source: "https://github.com/pgvector/pgvector"
author: "pgvector"
publisher_type: "organization"
category: "Data Extraction & Transformation"
framework: "Multi-Framework"
tool_ecosystem:
  github_repo: "pgvector/pgvector"
  github_stars: 21709
---

# Add Postgres-native vector retrieval to agent and RAG workflows with pgvector

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

## Prerequisites

Postgres 13+, pgvector extension, SQL access to the target database, embeddings from the agent or RAG pipeline, and application code that can query Postgres

## Installation

Use the upstream install or setup path that matches your environment:
- git clone --branch v0.8.2 https://github.com/pgvector/pgvector.git
- make
- make install # may need sudo
- Then re-run the installation instructions (run make clean before make if needed). If sudo is needed for make install, use:

Requirements and caveats from upstream:
- You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), [APK](#apk), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#...
- You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
- Or load vectors in bulk using COPY ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py))

Basic usage or getting-started notes:
- Compile and install the extension (supports Postgres 13+)
- cd /tmp
- cd pgvector

- Source: https://github.com/pgvector/pgvector
- Extracted from upstream docs: https://raw.githubusercontent.com/pgvector/pgvector/HEAD/README.md

## Documentation

- https://github.com/pgvector/pgvector#readme

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/add-postgres-native-vector-retrieval-to-agent-and-rag-workflows-with-pgvector/)