MCP Observatory

Name: MCP Observatory
Author: KryptosAI

by KryptosAIversion 1.36.1i★ –iRuns on your computer

Registry nameio.github.KryptosAI/mcp-observatory

Install

Overview

Description from the maker (original English)

MCP security scanner. CI-native testing, attack simulation, health scoring, and SARIF.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Clinics & health

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "observatory": {
      "command": "npx",
      "args": [
        "-y",
        "@kryptosai/mcp-observatory"
      ]
    }
  }
}

Run this in your terminal

claude mcp add observatory -- npx -y @kryptosai/mcp-observatory

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "observatory": {
      "command": "npx",
      "args": [
        "-y",
        "@kryptosai/mcp-observatory"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "observatory": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@kryptosai/mcp-observatory"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account KryptosAI, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Clinics & healthi

More stars than 0% of the other 871 servers in this category
Published to the registry more recently than 26% of the other 871 servers in this category
Basic checks equal to or better than 100% of the other 871 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is MCP Observatory safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.36.1) reached the registry 3 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Mirobody, FHIR MCP Server, Google Health MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Mirobody

by thetahealth

Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.

Runs on your computer★ 1,408Apache-2.0Updated 6 days ago

Install

FHIR MCP Server

by wso2

MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications

Runs on your computer★ 137Apache-2.0Updated 9 days ago

Install

Google Health MCP

by davidmosiah

Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents

Runs on your computer★ 79MITUpdated 4 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

MCP Observatory

More badges

Free, open-source MCP security testing from ClearFrame. MCP Observatory is the CI-native security tool for teams shipping custom MCP servers. Test during development, catch schema drift, simulate attacks, and generate compliance evidence — before agents depend on your servers.

Also available in Simplified Chinese.

Runtime enforcement: Use mcp-seatbelt to block dangerous MCP tool calls at runtime based on observatory scan results.

Get Started

[Step-by-step setup guide](https://mcp-observatory.com/start/) · macOS, Windows, Linux · Node.js 20+ and npm (install Node.js LTS).

1. Run your first scan

Open Terminal or PowerShell in your project folder and paste:

npx -y @kryptosai/mcp-observatory@latest

This downloads Observatory and checks your first configured MCP server. With no configured server, it uses an included example. To try only that example, run npx -y @kryptosai/mcp-observatory@latest demo --example.

2. Read the result

The terminal shows the target, grade, findings, and saved receipt path. Failed checks are findings to review, not a request to pay. If connection failed, fix the startup command or credentials and rerun. A demo grade describes the example, not your own server.

3. Review locally, then continue in ClearFrame

npx -y @kryptosai/mcp-observatory@latest dashboard

npx -y @kryptosai/mcp-observatory@latest clearframe

The dashboard shows your local scan history, HTML reports, and JSON downloads. No account, upload, subscription, or time-based retention limit. Stop it with Ctrl+C.

The clearframe command writes a private instruction file and prints a read-only CLI command. Review the file, then run that command or paste it into a new ClearFrame Mac chat with your project open. It does not launch ClearFrame or upload evidence automatically.

[Get ClearFrame CLI or the Mac app](https://clearframecode.com/download/?utm_source=mcp-observatory&utm_medium=readme&utm_campaign=opensource) · Currently Apple Silicon Mac. ClearFrame has its own account and usage terms; all Observatory features work without it.

MCP Observatory is free and MIT licensed. Product telemetry is off by default and makes no telemetry network request before explicit opt-in. Use telemetry preview to inspect fields or telemetry enable to opt in. Privacy details.

npx -y @kryptosai/mcp-observatory@latest test npx -y @modelcontextprotocol/server-everything

- uses: KryptosAI/mcp-observatory/action@v1

If this repo is an MCP package, that tests npx -y . Otherwise set command:.

Or generate a full workflow: npx -y @kryptosai/mcp-observatory@latest setup-ci --all --command "npx -y my-mcp-server" --sarif

Install: npx -y @kryptosai/mcp-observatory@latest · brew tap kryptosai/mcp-observatory https://github.com/KryptosAI/mcp-observatory && brew install mcp-observatory · docker pull ghcr.io/kryptosai/mcp-observatory:latest · curl -fsSL https://raw.githubusercontent.com/KryptosAI/mcp-observatory/main/scripts/install.sh | sh

docker run --rm ghcr.io/kryptosai/mcp-observatory:latest demo

docker run --rm ghcr.io/kryptosai/mcp-observatory:latest test npx -y @modelcontextprotocol/server-everything

Scanning a server on the host needs network and, for local files, a volume mount (-v "$PWD:$PWD" -w "$PWD").

Agents: npx -y @kryptosai/mcp-observatory@latest serve

Default-deny connect: npx -y @kryptosai/mcp-observatory@latest protect rewrites every discovered client config (Cursor, Claude, VS Code, .mcp.json, …). Undo: protect --undo. HTTP/SSE servers are left alone.

Runtime deny-default: npx -y @kryptosai/mcp-observatory@latest enforce --start-proxy writes a Seatbelt policy from the scan and starts the proxy. Local scan stays free.

Proof: Safety Index. Local history, evidence export, CI, and remediation task preparation are free.

Learn from production usage

Connect real tool calls to user intent with the usage-learning SDK and CLI: sanitized invocation evidence, opted-in “asked / expected / got” reports, selected conversation excerpts, one-click dissatisfaction flags, intent grouping across captured requests, and regression-case export. Run mcp-observatory usage review --dir private-usage to inspect linked evidence in a loopback-only browser screen. Server logs cannot reveal unshared conversations; observed execution and inferred breakdown signals stay separate. Collection is local and requires explicit integration.

Why MCP Observatory

MCP servers are becoming production dependencies. If agents rely on them, teams need a way to catch broken tools, unsafe schemas, schema drift, slow responses, and security footguns before those failures reach users.

Observatory gives maintainers and teams:

One-command CI setup with setup-ci --all
Profile-mapped audits with audit --profile nsa-mcp
MCP receipts that package target, evidence, verdict, action, and reproduction commands
MCP risk graphs that group servers by capability boundary, receipt state, CI posture, and recommended action
Action receipts that say allow, gate, rerun, quarantine, or escalate
GitHub PR comments for compatibility, drift, and security findings
GitHub Code Scanning SARIF for normalized MCP findings
Health score badges for public trust signals
Record/replay/verify workflows for regression testing
MCP server mode so agents can inspect other MCP servers directly
Review and remediation with free local history, CI, and optional ClearFrame CLI or Mac tasks

See GitHub Code Scanning for MCP servers, MCP Receipts, Troubleshooting, Safety Methodology, MCP Server Safety Index, MCP Observatory Contributors, hosted client contract, repository boundary, open-source policy, and free project policy.

Self-Assessment

We scan ourselves with mcp-observatory on every release. See results →

Self-hosted evidence

The MIT-licensed hosting source includes private receipt storage, GitHub sign-in, multi-target history, downloads, hosted HTTP checks and retention cleanup. Deploy it with your own configuration; no Observatory subscription is required. The account-free local dashboard is the fastest start.

Free tools for maintainers and teams

All scanner features, source audits, skill scans, package-name review, cross-server capability review, receipts, record/replay, local dashboards, and CI integrations are open source under MIT. No hosted account or private API is needed.

# Inspect local code without executing it

npx -y @kryptosai/mcp-observatory@latest source-audit ./src

Review a launch package name without running it

npx -y @kryptosai/mcp-observatory@latest package-check -- npx -y your-mcp-package

Review capability combinations across saved receipts

npx -y @kryptosai/mcp-observatory@latest toxic-flow first-receipt.json second-receipt.json

These checks identify review candidates; they do not prove a server is safe. See coverage and competitor feature evidence, ClearFrame workflow, and project policy.

How It Compares

Feature	mcp-observatory	Snyk agent-scan	Cisco mcp-scanner	agent-shield
MCP-native	✓	✓	✓	✓
Attack simulation	✓	✗	✗	✗
Schema drift detection	✓	✗	✗	✗
Record/replay/verify	✓	✗	✗	✗
Health scoring (0-100)	✓	✗	✗	✗
SARIF output	✓	✓	✓	✓
CI/CD native (setup-ci)	✓	✓	✓	✓
Public Safety Index	✓	✗	✗	✗
Runtime enforcement via mcp-seatbelt	✓	✗	✗	✗

Quick Start

Run a first check. No arguments starts demo (your servers, or the packaged local demo):

npx @kryptosai/mcp-observatory

Go deeper — also invoke safe tools to verify they actually run:

npx @kryptosai/mcp-observatory scan deep

Test a specific server:

npx @kryptosai/mcp-observatory test npx -y @modelcontextprotocol/server-everything

Add it to Claude Code as an MCP server:

claude mcp add mcp-observatory -- npx -y @kryptosai/mcp-observatory serve

Or add it manually to your config:

"mcpServers": { "mcp-observatory": { "command": "npx", "args": ["-y", "@kryptosai/mcp-observatory", "serve"] } } }

Commands

Command	What it does

| scan | Auto-discover servers, check them, and run safe a

Only the beginning is shown; read the rest in the repo

MCP Observatory

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Clinics & healthi

Common questions

Alternatives

Mirobody

FHIR MCP Server

Google Health MCP

README from the maker

Get Started

1. Run your first scan

2. Read the result

3. Review locally, then continue in ClearFrame

Learn from production usage

Why MCP Observatory

Self-Assessment

Self-hosted evidence

Free tools for maintainers and teams

Review a launch package name without running it

Review capability combinations across saved receipts

How It Compares

Quick Start

Commands