shadow-monitor-mcp

shadow-monitor-mcp

Enables AI agents to inspect Shadow Monitor capture files locally, with tools to load bundles, find errors, search network requests, and replay user actions.

Category
Visit Server

README

shadow-monitor-mcp

Open-source MCP server that lets any AI agent inspect Shadow Monitor capture files (uat-report-*.json.gz) — locally, with no upload.

Works with any client that speaks MCP over stdio: Cursor, Claude Desktop, Claude Code, Windsurf, VS Code Copilot Chat, Continue, Cline, Zed, and others.

Shadow Monitor (Chrome) records a UAT session
              ↓
     you download uat-report-….json.gz
              ↓
   this MCP server loads it for your AI
npm shadow-monitor-mcp · npx -y shadow-monitor-mcp
GitHub yurii-mandzii/shadow-monitor-mcp
Claude one-click shadow-monitor-mcp.mcpb (all releases)
Agent Skill SKILL.md (optional — teaches the agent when to call the tools)
License MIT
Needs Node.js 20+ for the MCP (Chrome extension is separate)

Companion: Shadow Monitor (Chrome extension)

This MCP does not record the browser. Capture comes from the extension:

Chrome Web Store Shadow Monitor
User guide Guide
Homepage Docs site
Source github.com/yurii-mandzii/shadow-monitor
Support / Privacy Support · Privacy
  1. Install the extension → add your UAT domain in Settings.
  2. Hard-reload the tab (Cmd/Ctrl+Shift+R).
  3. Reproduce the bug → Download → get uat-report-*.json.gz (often under Downloads/uat-capture).

MCP vs Skill (what you need)

Piece What it is Required?
MCP server The actual tools (load_bundle, find_errors, …) Yes — without it the agent cannot inspect the file
Agent Skill A short playbook (SKILL.md) that says “when the user pastes a uat-report-*.json.gz, call load_bundle — don’t raw-read the file” No — but strongly recommended so the agent behaves correctly

You can install them together (Option A) or separately (MCP via UI / .mcpb, skill via init or copy).


Install the MCP

You need Node.js 20+ once (download the LTS installer — click through; no coding required).

Option A — One command (MCP + skill together)

Open Terminal / PowerShell, paste, Enter:

npx -y shadow-monitor-mcp init --client all

Registers the server for Claude Desktop + Cursor + Claude Code and installs the Agent Skill. Then restart your AI app (Claude Desktop: fully quit with Cmd+Q).

Only one app? Use --client cursor, --client desktop, or --client claude-code.

Option B — UI / click (MCP only)

Claude Desktop — one-click .mcpb

  1. Download shadow-monitor-mcp.mcpb
  2. Double-click it, or Claude Desktop → Settings → Extensions → Install Extension…

Any MCP client — paste JSON

{
  "mcpServers": {
    "shadow-monitor": {
      "command": "npx",
      "args": ["-y", "shadow-monitor-mcp"]
    }
  }
}
App Where
Cursor Settings → Tools & MCP → add / edit MCP config
Claude Desktop Settings → Developer, or claude_desktop_config.json
Others Their MCP / custom-tools settings — same JSON

Option C — From a git clone

cd shadow-monitor-mcp
npm install && npm run build && npm run init:all

Install the skill (optional, separate is fine)

The skill teaches Claude/Cursor to call load_bundle instead of raw-reading the report.

Claude Desktop (what you use in Customize → Skills)

~/.claude/skills/ is Claude Code only — Desktop does not list those files.

  1. Run npx -y shadow-monitor-mcp init --client desktop (or all) — it writes
    ~/Downloads/shadow-monitor-bundles.zip
  2. Claude Desktop → Customize → Skills → Add → Upload a skill
  3. Upload that ZIP → enable the skill
  4. Ensure Settings → Capabilities → Code execution and file creation is on

Or zip manually: folder shadow-monitor-bundles/ containing SKILL.md.

Cursor / Claude Code (filesystem)

init also copies SKILL.md into:

  • Cursor → ~/.cursor/skills/shadow-monitor-bundles/
  • Claude Code → ~/.claude/skills/shadow-monitor-bundles/

Use it

In any connected agent chat, paste an absolute path:

Investigate /Users/you/Downloads/uat-capture/uat-report-2026-07-27T07-34-55-912Z.json.gz and show me what failed.

Expected flow: load_bundlebundle_overviewfind_errors → drill into network / console / actions.

  • Path must be absolute (/Users/… or C:\Users\…).
  • Don’t treat the .json.gz name as a skill / slash-command.
  • Encrypted exports: pass passphrase to load_bundle.

Tools

Tool What it does
check_bundle Cheap probe: is this path a workable Shadow Monitor .json / .json.gz?
load_bundle Load .json / .json.gz / encrypted report
bundle_overview Errors, slow requests, actions, navigation
bundle_metadata Schema, page, window, counts
find_errors Network + console failures
search_network Filter requests
get_network_request Full request by id
get_console_event Full console event by id
get_user_actions Click / navigate story timeline
get_action_replay rrweb slice for one action
get_semantics Pre-computed semantics (schema 2/3)

bundleId is optional when only one bundle is loaded.


Optional settings

Env Effect
SHADOW_MONITOR_FORMAT=toon Smaller list responses (TOON)
SHADOW_MONITOR_REDACT=false Keep signed-URL params / auth headers raw

Commands (developers)

Command Purpose
npm run build Compile → dist/
npm run init / init:cursor / init:all Register MCP + skill
npm run init:print Preview config, write nothing
npm start Run MCP server (stdio)
npm test Format / token tests
npm run test:smoke -- <bundle> End-to-end against a report
npm run pack:mcpb Build shadow-monitor-mcp.mcpb locally
npx -y shadow-monitor-mcp init --client all
npx -y shadow-monitor-mcp init --launch npx      # client uses npx (default after npm install)
npx -y shadow-monitor-mcp init --launch local    # client uses absolute dist/cli.js
npx -y shadow-monitor-mcp init --no-skill        # MCP only
npx -y shadow-monitor-mcp init --print

Troubleshooting

Problem Fix
404 shadow-monitor-mcp Package not on npm yet — use Option C from a clone, or the .mcpb release asset.
Server disconnected Node 20+, restart the app, check MCP config / .mcpb install.
Claude Desktop ignores config Fully quit (Cmd+Q) and reopen.
Agent raw-reads the .json.gz Install the skill (init, or copy SKILL.md).
No report file Install the Chrome extension first.

Development

npm install
npm run build
npm start
npm test

Capture format: shadow-monitor README · BUNDLE_FORMAT.md.

MIT — see LICENSE.

Recommended Servers

playwright-mcp

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
Audiense Insights MCP Server

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.

Official
Featured
Local
TypeScript
Magic Component Platform (MCP)

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.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

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

Official
Featured
Local
graphlit-mcp-server

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

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
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

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

Qdrant Server

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

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured