MCP Servers

MCP Observatory

Finds problems in your MCP servers before your users do. Scans your Claude config, checks every server's capabilities, actually calls tools to make sure they work, and catches breaking changes between versions.

README

MCP Observatory

  ███╗   ███╗ ██████╗██████╗
  ████╗ ████║██╔════╝██╔══██╗
  ██╔████╔██║██║     ██████╔╝
  ██║╚██╔╝██║██║     ██╔═══╝
  ██║ ╚═╝ ██║╚██████╗██║
  ╚═╝     ╚═╝ ╚═════╝╚═╝
     O B S E R V A T O R Y

Find problems in your MCP servers before your users do.

You update a server, a tool silently breaks, and your agent starts failing. MCP Observatory catches that. It connects to your servers, checks every capability, actually calls tools to make sure they work, and diffs runs to catch what changed.

Quick Start

Scan every MCP server in your Claude config:

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 from config files and check them all (default)
`scan deep`	Scan and also invoke safe tools to verify they execute
`test <cmd>`	Test a specific server by command
`diff <base> <head>`	Compare two run artifacts for regressions and schema drift
`watch <config>`	Watch a server for changes, alert on regressions
`serve`	Start as an MCP server for AI agents

What It Does

Check capabilities — connects to a server and verifies tools, prompts, and resources respond correctly.

Invoke tools — goes beyond listing. Actually calls safe tools (no required params / readOnlyHint) and reports which ones work and which ones crash.

npx @kryptosai/mcp-observatory scan deep

Detect schema drift — diffs two runs and surfaces added/removed fields, type changes, and breaking parameter changes.

npx @kryptosai/mcp-observatory diff run-a.json run-b.json

Recommend servers — scans your project for languages, frameworks, databases, and cloud providers, then cross-references the MCP registry to suggest servers you're missing. Ask your agent "what MCP servers should I add?" and it figures out the rest.

Watch for regressions — re-runs checks on an interval and alerts when something changes.

npx @kryptosai/mcp-observatory watch target.json

Scan locations

When you run scan, it looks for MCP configs in:

~/.claude.json (Claude Code)
~/Library/Application Support/Claude/claude_desktop_config.json (Claude Desktop, macOS)
%APPDATA%/Claude/claude_desktop_config.json (Claude Desktop, Windows)
.claude.json and .mcp.json (current directory)

MCP Server Mode

When running as an MCP server (serve), your AI agent gets five tools:

Tool	What it does
`scan`	Discover and check all configured servers
`check_server`	Check a specific server by command
`diff_runs`	Compare two saved run artifacts
`get_last_run`	Return the most recent run for a target
`suggest_servers`	Scan your environment and recommend servers you're missing

An AI tool that checks other AI tools. It's a tool testing tools that serve tools.*

<sub>* I'm a dude playing a dude disguised as another dude.</sub>

Compatibility

Works with any MCP server that uses standard transports:

Transport	Examples	Adapter
stdio (most servers)	filesystem, memory, context7, brave-search, sentry, notion, stripe	`local-process`
HTTP/SSE (remote)	Cloudflare, Exa, Tavily	`http`
Docker	All `@modelcontextprotocol/server-*` images	`local-process` via `docker run -i`

Servers needing API keys work via env in the target config. Python servers work via uvx. See the full compatibility matrix for tested servers and known issues.

Target config files

For more control (env vars, metadata, custom timeout):

{
  "targetId": "filesystem-server",
  "adapter": "local-process",
  "command": "npx",
  "args": ["-y", "@modelcontextprotocol/server-filesystem", "."],
  "timeoutMs": 15000
}

npx @kryptosai/mcp-observatory run --target ./target.json

HTTP / SSE targets

{
  "targetId": "my-remote-server",
  "adapter": "http",
  "url": "http://localhost:3000/mcp",
  "authToken": "optional-bearer-token",
  "timeoutMs": 15000
}

Limitations

Servers requiring interactive OAuth (e.g., Google Drive) need pre-authentication before Observatory can connect
Custom WebSocket transports (e.g., BrowserTools MCP) are not supported
A few servers time out or close before init — see known issues and compatibility

Contributing

See CONTRIBUTING.md for guidelines. The fastest way to contribute is to add a real passing target with a distinct capability shape, a clearer report surface, or a cleaner startup diagnosis.

Recommended Servers

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official

Featured

TypeScript

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official

Featured

Local

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official

Featured

TypeScript

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official

Featured

Python

E2B

Using MCP to run code via e2b.

Official

Featured

Neon Database

MCP server for interacting with Neon Management API and databases

Official

Featured

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official

Featured

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official

Featured