
Dominion Observatory
io.github.vdineshkPublished by GitHub account vdineshkv1.1.0Updated Oct 25, 2026
Runtime behavioral trust scoring for MCP servers. Check reliability before calling unknown tools.
The publisher's own server: Observatory
Overview
A remote trust-scoring service that lets an assistant check an MCP server's reliability, verify signed attestations, and report call outcomes.
- What you can do
- Check trust scores, baselines, anomalies, leaderboards and 30-day history for MCP servers and tool categories, plus observatory-wide statistics and compliance audit exports for recorded interactions. Run pre-flight and pre-invocation verification with signed diligence receipts, and cryptographically verify Dominion attestations. Check supply-chain trust of ClawHub skills before installing them. Report interaction outcomes and register new servers in the observatory.
- When to use it
- Useful when an assistant is about to call an unfamiliar MCP server or install a third-party skill and wants a reliability signal first, or when an operator needs signed proof that a due-diligence check was performed or an audit trail of agent interactions.
- Requirements
- A remote SSE endpoint; no local runtime, account or key is needed for the free tools. Paid verification and premium verdicts require an Authorization: Bearer do_ header for Stripe metering or an x402 payment transaction hash in USDC on Base. Network access to the hosted service.
Installation
In SourceWeft
- Open Dominion Observatory in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Web executable via SSE. Remote servers run from the web runtime once configured in a workspace.
Use with an agent
Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.
Read https://sourceweft.com/mcp/io.github.vdineshk%2Fdominion-observatory/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.Other MCP clients
Add this to your client's mcpServers config.
{
"mcpServers": {
"dominion-observatory": {
"type": "sse",
"url": "https://dominion-observatory.sgdata.workers.dev/mcp"
}
}
}README
Dominion Observatory
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_trusttells you if it's reliable - After calling any MCP server →
report_interactioncontributes to the trust network - Every report makes scores better for everyone — this is a collective intelligence system
Tools (14)
Quick Start
For agents (MCP)
Connect to: https://dominionobservatory.com/mcp
For developers (REST API)
How Trust Scores Work
Trust scores range from 0-100 and combine two signals:
- Static score (30%): GitHub presence, documentation quality, authentication support
- Runtime score (70%): Real success rates, latency, error patterns from agent interactions
Scores above 70 = reliable. Below 30 = risky. The more agents report interactions, the more accurate scores become.
Architecture
- Runtime: Cloudflare Workers (330+ global edge locations, <1ms cold start)
- Database: Cloudflare D1 (SQLite at the edge)
- Protocol: MCP (Model Context Protocol) + REST API
- Cost: Runs on free tier
Data Collection
Started: April 8, 2026
Every interaction reported to the observatory strengthens the trust network for all agents. The behavioral dataset compounds daily — it cannot be replicated by competitors who start later.
Categories
weather · finance · code · data · search · compliance · transport · productivity · communication
Operator
Built by Dinesh Kumar in Singapore. Part of the Dominion Agent Economy Engine (DAEE).
License
MIT
Source: README.md at commit afb4ab3
Tools
0Version history
1- v1.1.0LatestSep 16, 2026
Score
75% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 daysRequired25 pts
- Auth declaredRequired10 pts
- Tools listedRequired15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts
Declare a license in the repository or the registry entry.
Other Dominionobservatory integrations

Observatory
com.dominionobservatoryOfficial publisher
Remote MCP service that scores the behavioral trust of other MCP servers and skills, so an assistant can check reliability before calling unknown tools.

Ai Compliance Monitor
Published by GitHub account vdineshk
Regulatory intelligence for AI agents across jurisdictions, letting an assistant look up compliance obligations, articles, deadlines and cross-border comparison