dominion-observatory

dominion-observatory

vdineshk

Trust layer for AI agents - check MCP server reliability scores before calling, report outcomes to strengthen the collec

A behavioral trust layer for the AI agent economy that provides trust scores and reliability metrics for MCP servers. Check server reliability before calling and report outcomes to strengthen the trust network.

314 viewsLocal (stdio)

About dominion-observatory

dominion-observatory is a community-built MCP server published by vdineshk that provides AI assistants with tools and capabilities via the Model Context Protocol. Trust layer for AI agents - check MCP server reliability scores before calling, report outcomes to strengthen the collec It is categorized under search web, other. This server exposes 8 tools that AI clients can invoke during conversations and coding sessions.

How to install

You can install dominion-observatory in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

License

dominion-observatory is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

Tools (8)

check_trust

Get trust score and reliability metrics for any MCP server

report_interaction

Report success/failure after calling an MCP server

get_leaderboard

Top-rated MCP servers by category

get_baselines

Behavioral baselines for a tool category

check_anomaly

Is this server behavior normal or anomalous?

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://dominion-observatory.sgdata.workers.dev 📡 MCP Endpoint: https://dominion-observatory.sgdata.workers.dev/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 (8)

ToolDescription
check_trustGet trust score and reliability metrics for any MCP server
report_interactionReport success/failure after calling an MCP server
get_leaderboardTop-rated MCP servers by category
get_baselinesBehavioral baselines for a tool category
check_anomalyIs this server behavior normal or anomalous?
register_serverRegister a new MCP server (free)
get_server_history30-day trust score trend for a server
observatory_statsOverall network statistics

Quick Start

For agents (MCP)

Connect to: https://dominion-observatory.sgdata.workers.dev/mcp

For developers (REST API)

# Check trust score
curl "https://dominion-observatory.sgdata.workers.dev/api/trust?url=https://example.workers.dev/mcp"

# View leaderboard
curl "https://dominion-observatory.sgdata.workers.dev/api/leaderboard"

# Network stats
curl "https://dominion-observatory.sgdata.workers.dev/api/stats"

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

Alternatives

Related Skills

Browse all skills
archon

Interactive Archon integration for knowledge base and project management via REST API. On first use, asks for Archon host URL. Use when searching documentation, managing projects/tasks, or querying indexed knowledge. Provides RAG-powered semantic search, website crawling, document upload, hierarchical project/task management, and document versioning. Always try Archon first for external documentation and knowledge retrieval before using other sources.

6
pr-review-check-suggestion

Pre-output validation for PR review subagents. When web search is available, verifies findings against current best practices. Otherwise, calibrates confidence based on knowledge dependencies.

1
google-official-seo-guide

Official Google SEO guide covering search optimization, best practices, Search Console, crawling, indexing, and improving website search visibility based on official Google documentation

101
ux-writing

Create user-centered, accessible interface copy (microcopy) for digital products including buttons, labels, error messages, notifications, forms, onboarding, empty states, success messages, and help text. Use when writing or editing any text that appears in apps, websites, or software interfaces, designing conversational flows, establishing voice and tone guidelines, auditing product content for consistency and usability, reviewing UI strings, or improving existing interface copy. Applies UX writing best practices based on four quality standards — purposeful, concise, conversational, and clear. Includes accessibility guidelines, research-backed benchmarks (sentence length, comprehension rates, reading levels), expanded error patterns, tone adaptation frameworks, and comprehensive reference materials.

24
browser-automation

Automate web browser interactions using natural language via CLI commands. Use when the user asks to browse websites, navigate web pages, extract data from websites, take screenshots, fill forms, click buttons, or interact with web applications. Triggers include "browse", "navigate to", "go to website", "extract data from webpage", "screenshot", "web scraping", "fill out form", "click on", "search for on the web". When taking actions be as specific as possible.

21
last30days

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

20