Dominion Observatory

MCP serverDev tools

Your AI can check how trustworthy an unfamiliar tool is before it uses that tool. dominion-observatory watches how tools behave while they run and turns that behavior into a trust score, so reliability is judged on what tools actually do. It is community-built, and its code is available on GitHub.

Use Dominion Observatory in Claude, ChatGPT or Ahel Desktop

Free. Sign in, add Dominion Observatory and connect your AI. About a minute.

Also: Claude Code · Cursor · Codex

Then ask your AI: use Dominion Observatory to check trust

Details

Available today. Use it from your connected AI after setup.

After adding it, have your AI check a tool's trust score before using that tool for the first time. More detail is in the GitHub repository at github.com/vdineshk/dominion-observatory.

Dominion ObservatoryStart free

What your AI can do with it

  • Check a tool's trust score before your AI calls it for the first time
  • Score tools on how they actually behave when used
  • Spot unreliable tools before your AI depends on them
  • Decide whether an unknown tool is worth calling based on its score

Install Dominion 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 dominion-observatory 'https://dominion-observatory.sgdata.workers.dev/mcp'

    Run it once in your project, then open /mcp to approve any sign-in the server asks for.

  • Claude Desktop

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

    Add a custom connector in Settings, paste this address, and approve the sign-in.

  • Cursor

    cursor://anysphere.cursor-deeplink/mcp/install?name=dominion-observatory&config=eyJ1cmwiOiJodHRwczovL2RvbWluaW9uLW9ic2VydmF0b3J5LnNnZGF0YS53b3JrZXJzLmRldi9tY3AifQ==

    Open the link and Cursor adds the server at that address.

  • ChatGPT

    https://dominion-observatory.sgdata.workers.dev/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 dominion-observatory --url 'https://dominion-observatory.sgdata.workers.dev/mcp'

    Run it once, then sign in with codex mcp login dominion-observatory if the server asks for an account.

From the project's README

As published by vdineshk/dominion-observatory in README.md.

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)

ToolDescription
check_trustGet the trust score and reliability metrics for any MCP server. Use this BEFORE calling an unknown MCP server to assess if it's reliable. Returns trust_score (0-100), latency stats, uptime, success rate, and how many agents have used it. Scores above 70 indicate reliable servers. Scores below 30 indicate risky servers.
clawhub_skill_trustCheck the supply-chain trust of a ClawHub (OpenClaw) skill BEFORE installing or invoking it. After the Feb-2026 ClawHavoc supply-chain attack, third-party skills can carry malware. Returns a PASS/UNCERTAIN/FAIL badge and 0-100 score aggregating ClawHub's published security scan (VirusTotal + model), moderation verdict, and provenance. Malicious/suspicious/blocked => FAIL; unscanned => UNCERTAIN.
verify_before_callRun a signed pre-invocation verification immediately before an agent sends money, credentials, private data, or write access to an MCP server. The first 3 verifications per agent are free. After that, authenticate the MCP HTTP request with Authorization: Bearer do_<api_key> for Stripe metering ($0.01/call), or call once without payment to receive x402 instructions and retry with payment_tx. Returns PASS/UNCERTAIN/FAIL/UNRATED, evidence freshness, recommendation, and a signed diligence receipt.
paid_trust_verdictGet the PREMIUM behavioral trust verdict for an MCP server, with a signed, citable, tamper-evident attestation receipt. This is a paid x402 service: call WITHOUT payment_tx to receive payment instructions (0.001 USDC on Base), pay, then call again WITH the payment_tx (transaction hash, single-use) to receive the full verdict + receipt. The free check_trust tool remains available for basic scores.
verify_attestationCryptographically verify a Dominion signed attestation (JWS) — e.g. a trust-verdict receipt, gateway attestation, or MCP Verified badge. Stateless: checks the Ed25519 signature against Dominion's published public key (no trust in this server required). Use this to confirm a receipt another party gave you is authentic and untampered.
preflight_checkRun a PRE-FLIGHT due-diligence check on an MCP server BEFORE your agent invokes it. Returns a verdict (PASS/UNCERTAIN/FAIL/UNRATED) plus a SIGNED, timestamped diligence receipt you keep as proof you performed a trust check — the standard of care after the ClawHavoc/Miasma supply-chain attacks. Call this before connecting to or invoking any unfamiliar MCP server.
report_interactionReport the outcome of calling an MCP server. Call this AFTER you use any MCP server to contribute to the trust network. Your report helps other agents make better decisions. This is free and takes <1ms.
get_leaderboardGet the top-rated MCP servers, optionally filtered by category. Use this to discover the most reliable MCP servers in the ecosystem. Categories include: weather, finance, code, data, search, compliance, transport, productivity, communication.
get_baselinesGet behavioral baselines for a tool category. Shows what 'normal' looks like — average latency, success rates, typical call patterns. Use this to evaluate whether a specific server's performance is within normal range for its category.
check_anomalyCheck if observed behavior from an MCP server is anomalous compared to baselines. Use this when a server seems slow, unreliable, or returns unexpected results. Returns whether the behavior deviates significantly from normal patterns.
register_serverRegister a new MCP server in the observatory. Server owners can register their servers to start building a trust score. Registration is free.
get_server_historyGet daily trust score and performance history for a server over the last 30 days. Use this to see trends — is the server improving or degrading?
observatory_statsGet overall statistics about the Dominion Observatory — total servers tracked, total interactions recorded, coverage by category, and data freshness. Use this to understand the scope of the trust network.
get_compliance_reportExport a compliance-ready audit trail of all recorded interactions. Formatted for EU AI Act Article 12 and Singapore IMDA Agentic AI Governance Framework. Filter by server, agent, or date range. Essential for enterprises that need to prove their AI agents are behaving correctly.

Quick Start

For agents (MCP)

Connect to: https://dominionobservatory.com/mcp

For developers (REST API)

# Check trust score
curl "https://dominionobservatory.com/api/trust?url=https://example.workers.dev/mcp"

# View leaderboard
curl "https://dominionobservatory.com/api/leaderboard"

# Network stats
curl "https://dominionobservatory.com/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

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
1
Forks
3
Last commit
Sep 2026
Advanced
Delivery
dominion-observatory MCP server → your Ahel connector (mcp.ahel.ai) → your AI.
Item type
mcp-server
Key
io-github-vdineshk-dominion-observatory
Source
github.com/vdineshk/dominion-observatory
Hosted endpoint
https://dominion-observatory.sgdata.workers.dev/mcp