About PostgreSQL CVE & Release Intelligence
An MCP server that gives AI assistants PostgreSQL security intelligence, including CVEs, yanked releases, known exploits, and upgrade paths. It uses the manually curated PG_CVE dataset and returns structured results.
Key features
- 01Retrieve version CVEs and status
- 02Compare vulnerabilities across versions
- 03Recommend upgrades and list fixes
- 04List CVEs with public exploits
- 05View database overview
Use cases
- 01Check whether a PostgreSQL version has known issues
- 02Compare security findings before and after an upgrade
- 03Plan upgrades for branches near EOL
- 04Identify CVEs with known public exploits
MCP support
Exposes PostgreSQL security reports, version comparisons, upgrade recommendations, exploit listings, and dataset summaries as MCP tools. Supports stdio and Streamable HTTP.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
uvx pg-cve-mcpPG_CVE_MCP_TTLCache TTL in seconds for CVE data refresh (default: 86400)PG_CVE_MCP_DATA_URLURL of the PostgreSQL CVE JSON data (default: PG_CVE GitHub Pages)Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
5Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| version | string | Yes |
Details
From the project READMEpg-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
| Prompt to your agent | Tool used | Result |
|---|---|---|
| "Is PostgreSQL 15.8 safe?" | get_cves("15.8") | EOL/yanked flags, release date, full CVE list sorted by CVSS |
| "Compare 16.3 vs 16.4" | compare_versions("16.3", "16.4") | fixed / new / still-present CVEs with release dates |
| "Should I upgrade from 14.10?" | get_upgrade_path("14.10") | recommended target + the CVEs it fixes + release dates |
| "Any known exploits right now?" | get_exploits() | all exploitable CVEs, sorted by CVSS, with release dates |
| "What does this database track?" | get_summary() | stats, EOL and yanked-release overview |
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 include release dates for every version. 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
| Tool | Description |
|---|---|
get_cves(version) | Complete security report for a version: EOL/yanked status, release date, stats, CVEs sorted by CVSS (a synthetic CVE-EOL-WARNING at 10.0 is prepended for unsupported releases) |
compare_versions(v1, v2) | Side-by-side CVE comparison (fixed/new/still present) with yanked & EOL flags and release dates |
get_upgrade_path(from_version) | Recommended upgrade (minor by default; major when EOL or next-to-EOL) with fixed CVEs and release dates |
get_exploits() | All CVEs with known public exploits, sorted by CVSS, with release dates |
get_summary() | Overview of the tracked CVE database incl. yanked releases |
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
| Env Var | Default | Description |
|---|---|---|
PG_CVE_MCP_TTL | 86400 | Cache TTL in seconds for CVE data |
PG_CVE_MCP_DATA_URL | https://meob.github.io/PG_CVE/postgresql_cves.json | CVE data source URL |
PORT | 8000 | HTTP port for the Streamable HTTP server (run_server.py) |
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
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.