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.
Install
$ agentstack add skill-agentskillexchange-skills-add-postgres-native-vector-retrieval-to-agent-and-rag-workflows-with-pgvector ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-agentskillexchange-skills-add-postgres-native-vector-retrieval-to-agent-and-rag-workflows-with-pgvector) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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)
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
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: agentskillexchange
- Source: agentskillexchange/skills
- License: MIT
- Homepage: https://agentskillexchange.com
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.