PG CVE MCP Server

pg-cve-mcp — PostgreSQL CVE & Release Intelligence for AI Agents

Give your AI assistant direct access to PostgreSQL security intelligence: CVEs, yanked releases, known exploits, and upgrade paths for any version — queried, not browsed.

---

Why pg-cve-mcp?

Browsing a CVE dashboard is a human habit. Agents need answers, not pages.

pg-cve-mcp turns the curated dataset of the PG_CVE project — the same one powering the PostgreSQL CVE Dashboard — into MCP tools that any AI assistant (opencode, Claude Desktop, etc.) can call directly. What was a static page becomes a first-class, programmatic part of your AI workflow.

Unlike raw NVD feeds, the PG_CVE dataset is manually curated to carry the same judgment a careful DBA would apply:

• Yanked releases flagged with the real reason (e.g. "Data corruption using CONCURRENTLY")
• Known exploits confirmed to exist in the wild
• EOL branches marked, with a synthetic CVE-EOL-WARNING (CVSS 10.0) prepended to unsupported reports
• Verified CVEs — no false positives from automated scraping

What your agent can now do

Agent-first design

Every tool returns structured JSON, sorted by CVSS (highest first). Tools flag yanked and EOL state explicitly on the version metadata, and get_upgrade_path distinguishes a safe minor upgrade from a forced major one when a branch is at or near end-of-life — so the agent can give advice, not just data.

See real tool outputs in the live demo.

---

Quick Start

pip install pg-cve-mcp
pg-cve-mcp

Or with npx (no install):

npx -y pg-cve-mcp

MCP Tools

Transports

stdio (default)

Run locally over stdio for opencode, Claude Desktop, and other stdio MCP clients:

pip install -e .
pg-cve-mcp

Streamable HTTP (self-hosted)

For remote or enterprise deployments, serve the same tools over HTTP. Run python run_server.py (or build the Dockerfile); the server listens on $PORT (default 8000) at path /mcp:

python run_server.py
# MCP endpoint: http://127.0.0.1:8000/mcp

Configure any MCP client with the URL, e.g. in opencode.json:

{
  "mcp": {
    "pg-cve-mcp": {
      "type": "remote",
      "url": "http://127.0.0.1:8000/mcp"
    }
  }
}

Configuration

Development

Run the test suite and linters:

python -m pytest
ruff check src tests
mypy src

Data Source

Data is fetched from the PG_CVE project's GitHub Pages with local caching. Falls back to a bundled copy if the network is unavailable.

Example Prompts

"What CVEs affect PostgreSQL 16.4?"

"Is PostgreSQL 15.8 safe to use?"

"Compare CVEs in 16.3 vs 16.4"

"What's the upgrade path from PostgreSQL 14.10?"

License

Apache 2.0