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orionbelt-analytics

MCP server · PyPI · graded 2026-10-24Source linked

Ontology-based MCP server for database schema analysis and RDF/OWL ontology generation

No outside reports on file

orionbelt-analytics connects to external service APIs; restrict its folder reach, network access, and credentials before installing.

Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee.

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What it can access

  • Local filesNo local folder access notedLOW
  • Command executionNo shell command runner notedLOW
  • Network reachConnects to outside service APINOTED
  • CredentialsNo API token requiredLOW
  • Package sourcePyPI (orionbelt-analytics)PUBLIC

Inferred from this listing’s public package details and description. Check the project’s source before installing.

Install

uvx orionbelt-analytics

All setup options ↓

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Everything known

We found nothing about this project in the sources we read (last checked 2026-10-31). That does not mean it has no problems.

0 incidents · 0 advisories · 0 news articles · 0 community threads · checked 2026-10-31

Popularity grade: D (from public signals such as stars and downloads, not a code review). Graded 2026-10-24.

Sources we read: OSV, GitHub Advisory Database, CISA Known Exploited Vulnerabilities, 44 security news feeds and our incident library. Last checked 2026-10-31.

Check a specific version →

About Orionbelt Analytics

Orionbelt Analytics is an MCP server focused on Data & databases and Cloud & infrastructure: Ontology-based MCP server for database schema analysis and RDF/OWL ontology generation.

It is published on PyPI as orionbelt-analytics and hosted on GitHub at ralfbecher/orionbelt-analytics. Based on its public metadata, its operational scope includes: connects to outside service api.

Setup

These use the package this listing points to. Check the project’s own instructions before running anything.

PyPI command

uvx orionbelt-analytics

PyPI (pip) command

pip install orionbelt-analytics

MCP client config

For Claude Desktop (claude_desktop_config.json) or Cursor (.cursor/mcp.json).

json
{
  "mcpServers": {
    "orionbelt-analytics": {
      "command": "uvx",
      "args": [
        "orionbelt-analytics"
      ]
    }
  }
}

Why this grade

DD — High risk signals

Signal-based grade (1/7 points): public source code. This reflects adoption and transparency, not a code review.

Popularity and upkeep

4/100
Listing last refreshed
2026-10-30

These are public popularity signals, not a maintenance check. Look at the repository’s commit history and open issues.

Risks to watch for

  • External API & account scope: Connects to third-party service APIs. Use a dedicated, least-privilege token scoped only to the workspaces or repositories this tool needs.
  • Dependency & version pinning: Distributed via PyPI (orionbelt-analytics). Pin an exact release version or commit SHA rather than floating tags so upstream updates are reviewed first.

How to lower the risk

Least-privilege permissions

  • Give it access only to the specific folders, accounts or projects it needs, never your whole drive or admin account.
  • Use a separate, limited API key or login just for this tool so you can switch it off without affecting anything else.

Network isolation

  • Run it on a work computer or sandbox account, not one holding personal or company-sensitive data.
  • If your IT team can, limit which websites and services it is allowed to contact.

Monitoring

  • Check its activity history or logs weekly at first, and look at what it changed or sent.
  • Turn on alerts for new logins or unusual usage on any account it connects to.

Red flags to watch for

  • It asks for more access than its job requires, or prompts you to paste passwords.
  • It suddenly updates with new owners, or starts contacting unfamiliar websites.

Questions

How do I install Orionbelt Analytics?

Run uvx orionbelt-analytics (or pip install orionbelt-analytics) in your terminal, or add the server entry to your claude_desktop_config.json or .cursor/mcp.json as shown in the Setup section on this page. Full setup docs and environment variables are in github.com/ralfbecher/orionbelt-analytics.

Are there security reports about Orionbelt Analytics?

No reports found for this package in our research (last checked 2026-10-31). Orionbelt Analytics currently holds Grade D (High risk signals) based on public adoption and transparency signals. Review the permissions and source repository before granting access to local files, shell commands, or API keys.

Is Orionbelt Analytics actively maintained?

We do not have star or download counts on file for Orionbelt Analytics yet (listing refreshed 2026-10-30). Check the commit history and open issues at github.com/ralfbecher/orionbelt-analytics before relying on it.

What are alternatives to Orionbelt Analytics?

Compare Orionbelt Analytics side by side with similar MCP servers in the Related tools section on this page, or browse all MCP servers on AgentArmorHQ.

README badge and team notes

Maintain or use Orionbelt Analytics? Show its live grade in your GitHub README, docs site, or run a check from the terminal before you install.

AgentArmorHQ Risk Grade D for Orionbelt Analytics

GitHub README Markdown:

markdown
[![AgentArmorHQ Risk Grade for Orionbelt Analytics](https://agentarmorhq.com/api/badge/ralfbecher-orionbelt-analytics)](https://agentarmorhq.com/skills/ralfbecher-orionbelt-analytics)

HTML embed:

html
<a href="https://agentarmorhq.com/skills/ralfbecher-orionbelt-analytics"><img src="https://agentarmorhq.com/api/badge/ralfbecher-orionbelt-analytics" alt="AgentArmorHQ Risk Grade for Orionbelt Analytics" height="20" /></a>

Terminal check:

terminal
curl -fsSL https://agentarmorhq.com/api/cli | node --input-type=module - check "ralfbecher-orionbelt-analytics"

Share with your security lead

Need sign-off to use orionbelt-analytics? Copy this note for Slack, a ticket or a pull request.

### AgentArmorHQ Security Review Memo: orionbelt-analytics
- **Listing URL:** https://agentarmorhq.com/skills/ralfbecher-orionbelt-analytics
- **Type:** App connector
- **Risk Grade:** Grade D (High risk signals)
- **Outside Security Advisories on File:** 0

#### Permission & Blast-Radius Signals
- **Local files:** No local folder access noted
- **Command execution:** No shell command runner noted
- **Network reach:** Connects to outside service API
- **Credentials:** No API token required
- **Package source:** PyPI (orionbelt-analytics)

#### Recommended Hardened Setup
- **Command:** `uvx orionbelt-analytics`
- **Controls:** Pin an exact version in `.mcp.json`, scope access to a single workspace folder, and use a least-privilege read-only token where supported.

_Based on public adoption and transparency signals as of Oct 24, 2026. Our opinion, not a code audit or security guarantee._

Key facts

Type
App connector
Publisher
ralfbecher
Source code
github.com/ralfbecher/orionbelt-analytics
Install command
pip install orionbelt-analytics
Est. context load
~850 tokens / turn (~5 tool schemas, 0.43% of 200k context)
Last updated
2026-10-30
Last graded
2026-10-24

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