observatory

MCP serverDev tools

Lets your agent check how reliable an unfamiliar tool is before using it.

No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.

Connect your AI Use it in a pipeline

Then ask your AI: use observatory to check trust

Details

Available today. Use it as a step in a pipeline you build, or from your connected AI.

No key or account is asked for. Not verified by us yet: Ahel has not run a call through it.

Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.

About this server

Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.

Install observatory

The server’s own address, for the clients that take one directly. Or connect Ahel once and every client you use reads it from one address, with the account kept on Ahel rather than in each client’s config.

Claude Code
claude mcp add --transport http --scope user observatory 'https://dominionobservatory.com/mcp'
Run it once in your project, then open /mcp to approve any sign-in the server asks for.
Claude Desktop
https://dominionobservatory.com/mcp
Add a custom connector in Settings, paste this address, and approve the sign-in.
Cursor
cursor://anysphere.cursor-deeplink/mcp/install?name=observatory&config=eyJ1cmwiOiJodHRwczovL2RvbWluaW9ub2JzZXJ2YXRvcnkuY29tL21jcCJ9
Open the link and Cursor adds the server at that address.
ChatGPT
https://dominionobservatory.com/mcp
In Settings, enable Developer mode, create an MCP app, and paste this address. Your plan and workspace must allow custom apps.
Codex
codex mcp add observatory --url 'https://dominionobservatory.com/mcp'
Run it once, then sign in with codex mcp login observatory if the server asks for an account.

From the project's README

As published by vdineshk/dominion-observatory in README.md. This repository publishes several servers, so only the opening is shown here.

The behavioral trust layer for the AI agent economy.

Check MCP server reliability before you call. Report outcomes to strengthen the trust network.

🌐 Live: https://dominionobservatory.com 📡 MCP Endpoint: https://dominionobservatory.com/mcp

What is this?

Every AI agent needs to know: "Can I trust this MCP server?" The Dominion Observatory answers that question with real runtime data — not GitHub stars, not static scans, but actual performance metrics from real agent interactions.

Before calling an unknown MCP server → check_trust tells you if it's reliable
After calling any MCP server → report_interaction contributes to the trust network
Every report makes scores better for everyone — this is a collective intelligence system

Tools (14)

Shortened here. Read the whole README on GitHub.

Tools it offers (15)

What this server listed when Ahel dialed its public endpoint in Oct 2026, with no key and no account of yours. The names are the server’s own.

check_trust
clawhub_skill_trust
verify_before_call
paid_trust_verdict
verify_attestation
preflight_check
report_interaction
get_leaderboard
get_baselines
check_anomaly
register_server
get_server_history
observatory_stats
get_compliance_report
get_mica_attestation

Signals

GitHub stars: 2
Forks: 3
Last commit: Sep 2026

Advanced

Delivery: observatory MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type: mcp-server
Key: com-dominionobservatory-observatory
Source: github.com/vdineshk/dominion-observatory
Hosted endpoint: https://dominionobservatory.com/mcp

github.com/vdineshk/dominion-observatory

More in Dev tools

airtreks-mcp
MCP server · airtreks
More in Dev tools world-data-statistics
MCP server · adarsh4052
More in Dev tools draw.io
MCP server · jgraph
More in Dev tools 0nMCP
MCP server · 0nork
More in Dev tools sportwizzard
MCP server · adamruehle
More in Dev tools korean-law-mcp
MCP server · chrisryugj
More in Dev tools