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MCPGoat

Deliberately vulnerable MCP server (aka MCP Goat) for security training — 26 challenges across 4 difficulty levels (incl. a secure reference), a victim-agent harness, and one-command Docker deploy. Practice penetration testing against the Model Context Protocol.

Install / Use

claude mcp add SabyasachiDhal -- npx -y github:SabyasachiDhal/MCPGoat

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

84/100

Category

Security

Supported Platforms

Claude Code
Claude Desktop

Our assessment of MCPGoat

MCPGoat scores 84/100 on our quality scale, 852nd of 1,127 Security skills we index.

Its MCP Server is 13 KB long, well organised into 21 sections with 6 code examples: a thorough specification that gives an agent plenty to work with.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so MCPGoat is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

MCPGoat compared with similar skills

All 4 of these similar skills score higher than MCPGoat; compare them before choosing.

SkillScoreStarsUpdatedFormat
MCPGoat (this skill)by SabyasachiDhal841051d agoMCP Server
Agent-Reachby Panniantong10093.0k21d agoCLAUDE.md
headroomby headroomlabs-ai10074.6ktodayCLAUDE.md
CowAgentby zhayujie10047.3ktodayCLAUDE.md
Scraplingby D4Vinci10086.1ktodayMCP Server

Frequently asked questions

How do I install MCPGoat?
Run claude mcp add SabyasachiDhal -- npx -y github:SabyasachiDhal/MCPGoat. The install tabs above show the steps for each supported agent.
Which AI agents does MCPGoat work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is MCPGoat safe to use?
It is MIT-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is MCPGoat still maintained?
The repository was last updated about 2 months ago, so MCPGoat is actively maintained.

MCPGoat

License: MIT  ·  open source, free to use and self-host.

🌐 Website: https://sabyasachidhal.github.io/MCPGoat/  ·  Listed on Glama

MCPGoat (also written MCP Goat) is a deliberately vulnerable MCP server — an insecure-by-design Model Context Protocol implementation for practicing MCP penetration testing. Every challenge is implemented at three difficulty levels (Easy / Moderate / Difficult) behind a tiered level switch, with a capture-the-flag scoreboard. Runs over Streamable HTTP; attack it with the bundled client, MCP Inspector, curl, or Burp.

⚠️ Authorized training use only. Intentionally contains RCE, SSRF, SQLi, secret leakage, and more. Keep it on 127.0.0.1; ideally run it in a container. Never expose it to a network you don't own.

ℹ️ MCPGoat is an independent project — not affiliated with or endorsed by the WebGoat project, or any other similarly-named "vulnerable MCP" project.

Implements the Core set + three Extended batches from DESIGN_PROMPT.md — 26 challenges × 3 levels = 78 distinct flags, exercising every major MCP primitive (tools, resources, prompts, sampling) plus the HTTP transport layer. Each challenge also has a 4th Secure level: the fixed, unexploitable reference where every documented exploit fails (verify with npm run attack -- … secure).

How MCPGoat compares to DVMCP and other vulnerable MCP labs

| Lab | Scope | Model | |---|---|---| | MCPGoat (this project) | 26 challenges → 78 scored flags | every challenge at Easy / Moderate / Difficult + a Secure reference level; CTF scoreboard; victim-agent harness | | DVMCP — Damn Vulnerable MCP Server | 10 challenges | increasing difficulty (easy → hard), one implementation each | | Vulnerable MCP Servers Lab | collection | one standalone server per vulnerability |

All of these labs are worth your time. MCPGoat aims to be the deepest single target: the same flaw hardens across tiers, so you can progress from a first exploit to blind, multi-step chains — then verify the fix against the Secure level.


What it looks like

The control panel (http://127.0.0.1:7332) — pick a difficulty level and track progress. This is config + progress only; it is not the thing you attack.

MCPGoat control panel

The actual attack surface is the MCP server itself — its tools, resources, prompts, and sampling calls. MCP servers have no human web UI; you interact as an MCP client. Here it is in MCP Inspector (the bundled attacker client and a real AI agent are the other two ways):

MCP Inspector connected to the MCPGoat server


Deploy

Docker (recommended — one command, self-contained, RCE stays in the container)

git clone https://github.com/SabyasachiDhal/MCPGoat.git
cd MCPGoat
docker compose up --build            # → http://127.0.0.1:7332
# or:
docker build -t mcpgoat .
docker run --rm -p 127.0.0.1:7332:7332 mcpgoat

The image is ~202 MB — a bare Alpine with just the node binary plus curl/ping (for the RCE challenge); the server is esbuild-bundled to a single ~1.2 MB file, so the runtime carries no node_modules, npm, or package.json. Runs as a non-root user. Keep the 127.0.0.1: in the port mapping — -p 7332:7332 would expose the vulnerable server on every host interface. Start at a level with -e MCPGOAT_LEVEL=difficult.

Local Node (for development)

Requires Node 18+ (tested on Node 22/23/24; uses the built-in node:sqlite).

git clone https://github.com/SabyasachiDhal/MCPGoat.git
cd MCPGoat
npm install
npm start                 # serves http://127.0.0.1:7332   (tsx, no build step)
# or compiled:  npm run build && npm run serve

Open the control panel at http://127.0.0.1:7332 to pick a level and watch the scoreboard. Start at a level directly with MCPGOAT_LEVEL=moderate npm start.


The difficulty model (pick your level, then pentest)

The same vulnerability hardens as you climb:

| | Easy | Moderate | Difficult | |---|---|---|---| | Auth | none | static token (leaked elsewhere) | OAuth-style / crypto / forged token | | Filtering | none | bypassable blacklist | allowlist with a gap | | Feedback | full output | partial | blind / out-of-band | | Steps | 1 | 2–3 chained | multi-step, cross-primitive | | Hints | in tool description | scoreboard only | none |

…and Secure — the fixed reference: strict validation, exact-match auth, parameterized queries, no eval, Origin allow-lists, CSPRNG session IDs, least-privilege tools. No flags here; the point is every attack fails. Confirm with npm run attack -- http://127.0.0.1:7332/mcp secure (expect 22/22 blocked).

Selecting a level (any of these — all drive one shared state):

  1. Control panel — radio buttons at http://127.0.0.1:7332
  2. MCP tool — mcpgoat_set_level({ level })
  3. Env — MCPGOAT_LEVEL=difficult npm start

After changing level, reconnect your MCP client so tool descriptions refresh (matters for the tool-poisoning / shadowing challenges). Behavior changes take effect immediately.


Three ways to attack it

1. Bundled attacker client (fastest demo / smoke test)

Detects the current level and exploits every challenge at that level:

npm run attack                                  # current level
npm run attack -- http://127.0.0.1:7332/mcp all # run all three levels in sequence

2. MCP Inspector (interactive)

npm run inspect
# Transport "Streamable HTTP", URL http://127.0.0.1:7332/mcp, Connect

3. curl / Burp (raw protocol)

See docs/EXPLOITS.http. Streamable HTTP needs Accept: application/json, text/event-stream and a session id from the initialize response header.


Victim-agent harness (end-to-end impact)

Flag capture proves an exploit exists. The victim agent proves impact — a real MCP-client agent, driven by an LLM, doing benign tasks while the lab's payloads manipulate it into calling tools it was never asked to and leaking secrets.

npm run agent                  # naive agent (mock brain, offline)  → 3/3 compromised
npm run agent -- --defended    # hardened agent, same attacks       → 0/3 compromised
MCPGOAT_AGENT_BACKEND=ollama OLLAMA_MODEL=llama3.1 npm run agent   # real local model

Three scenarios run against the easy level:

| User asked | What the naive agent does | Demonstrates | |---|---|---| | "Summarize my inbox" | reads inbox → follows the injected instruction → calls internal_debug_dump → leaks a flag | indirect prompt injection | | "What is 17 + 25?" | obeys add_numbers's hidden <IMPORTANT> → calls admin_get_all_secrets → exfiltrates via the sidenote arg | tool poisoning + excessive agency | | "Summarize this note" | calls ai_summarize → the server's sampling request steers the agent's own model into emitting a flag | sampling abuse |

The --defended agent treats tool descriptions and results as untrusted data (never instructions) and resists all three — the client-side counterpart to the server-side Secure level. Backend is offline-first: a deterministic mock brain by default (no install), or Ollama for a real local model.


Challenges

Core set

| ID | Challenge | Category | ★ | |----|-----------|----------|---| | A1 | Tool Poisoning | MCP-specific | ★★ | | A2 | Tool Shadowing / trusted-tool override | MCP-specific | ★★ | | A3 | Rug Pull / Tool Mutation (TOCTOU) | MCP-specific | ★★★ | | B1 | Indirect Prompt Injection via tool output | Prompt/Context | ★★ | | D1 | Command Injection (RCE) | Injection sink | ★ | | D2 | Path Traversal | Injection sink | ★ | | D3 | SSRF | Injection sink | ★★ | | D4 | SQL Injection | Injection sink | ★★ | | C2 | Broken Authorization / Confused Deputy | AuthN/AuthZ | ★★ | | C3 | IDOR | AuthN/AuthZ | ★ | | E1 | Sensitive Data Exposure | Secrets/Exposure | ★ |

Extended set (deepens MCP-primitive coverage)

| ID | Challenge | Category | ★ | New primitive | |----|-----------|----------|---|---------------| | A9 | Invisible-Text Tool Poisoning (zero-width / Unicode tags) | MCP-specific | ★★★ | — | | B2 | Indirect Injection via Resource content | Prompt/Context | ★★ | Resources | | B3 | Prompt-Template Injection | Prompt/Context | ★★ | Prompts | | B5 | Sampling Abuse (server-driven LLM calls) | MCP-specific | ★★★ | Sampling | | C4 | OAuth Token-Audience Confusion | AuthN/AuthZ | ★★★ | — | | D6 | Server-Side Template Injection (SSTI) | Injection sink | ★★ | — |

Extended set — batch 2 (HTTP transport & resource abuse; solved via raw fetch/tools)

| ID | Challenge | Category | ★ | |----|-----------|----------|---| | F1 | DNS Rebinding / missing Origin validation | Transport | ★★★ | | F2 | CORS Misconfiguration (reflected Origin + credentials) | Transport | ★★ | | C6 | Predictable Session IDs (hijack) | Transport | ★★ | | G1 | Unbounded Consumption (cost/DoS) | DoS/Cost | ★★ | | G4 | Regular-Expression DoS (ReDoS) | DoS/Cost | ★★ |

Extended set — batch 3 (more injection sinks & supply chain)

| ID | Challenge | Category | ★ | |----|-----------|----------|---| | D5 | NoSQL Injection (operator / $where) | Injection sink | ★★ | | D7 | XML External Entity (XXE) | Injection sink | ★★★ | | D8 | Insecure Deserialization (prototype pollution) | Injection sink | ★★★ | | H1 | Supply Chain (typosquat / unsigned package) | Supply chain | ★★ |

Each (challenge, level) pair has a unique flag FLAG{slug__level}. Capture it, submit with the submit_flag tool, track progress with scoreboard (or the control panel). Per-level hints: the list_challenges tool.

Full per-level walkthroughs + fixes: docs/SOLUTIONS.md.


How the levels differ (a taste)

  • Command Injection — Easy: no filter. Moderate: ;/& blocked → use |. Difficult: most metacharacters blocked and blind → newline-chain a curl that exfiltrates to the OOB collector, then read_collector.
  • SSRF — Easy: fetch anything. Moderate: 127.0.0.1/localhost string-blocked → use metadata.internal / [::1]. Difficult: same, but blind → confirm via the collector.
  • SQL Injection — Easy: UNION. Moderate: UNION/-- blacklisted → UnIoN
    • quote-balancing. Difficult: boolean-blind, count-only → binary-search the flag out char by char.
  • Broken Auth — Easy: open. Moderate: static token leaked by a resource. Difficult: sha256(nonce + signing_secret) challenge-response (secret leaks via a verbose error).

Project layout

mcpgoat/
├── DESIGN_PROMPT.md          # the full build brief (Core + Extended catalog)
├── Dockerfile  docker-compose.yml   # one-command deploy
├── .github/workflows/ci.yml  # regression gate + Docker smoke test
├── src/
│   ├── server.ts             # Express host: control panel, MCP endpoint, OOB collector
│   ├── level.ts              # the Easy/Moderate/Difficult switch
│   ├── scoreboard.ts         # challenge catalog, per-level flags, scoreboard
│   ├── challenges.ts         # all 26 challenges × 4 levels (incl. secure)
│   ├── buildServer.ts  db.ts  state.ts  internal.ts
│   ├── attacker/client.ts    # level-aware exploitation client / smoke test
│   ├── agent/agent.ts        # victim-agent harness (naive vs --defended)
│   └── ci/check.ts           # regression gate (npm run ci)
├── workspace/  vault/        # path-traversal / RCE targets (per-level flag files)
└── docs/SOLUTIONS.md  docs/EXPLOITS.http

Continuous regression

npm run ci boots an isolated serve

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars10
CategorySecurity
Updated1mo ago
Forks1

Languages

TypeScript

Trust signals

97/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

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