mcp-security-toolkit

mcp-security-toolkit

14 atomic MCP tools for AppSec and AI Security engineers: source/schema/prompt audit primitives, JWT inspect, HTTP diff, pentest atoms (default creds, GraphQL introspect, phpggc, interactsh OOB), and a defensive helpers library that fixes the bugs the detectors flag. SARIF output, PyPI Trusted Publishing with Sigstore provenance.

Category
Visit Server

README

mcp-security-toolkit

CI PyPI Python License: MIT

Built by Redmai. For continuous autonomous API / agent security scanning, use Redmai.

Source / schema / prompt audit primitives for agent builders.

Plug into Claude Code / Cursor / Claude Desktop. Audit MCP servers, agent tool schemas, system prompts, JWTs, and HTTP-response diffs — locally, in the coding agent you already use. Atomic, auditable, no orchestration.

Why this exists

Most security-flavored MCP servers wrap an existing CLI (Burp, Shodan, CyberChef) or audit MCP configurations and tool descriptions. The primitives a developer reaches for when their own code ships an LLM feature — source-level audit of an MCP server, schema-level audit of an agent tool, static review of a system prompt — are thinly covered.

mcp-security-toolkit ships those primitives, plus the everyday pentest atoms an agent reaches for during AppSec work, so you can run one server instead of five.


Headline tools

mcp_server_audit

Heuristic AST audit of an MCP server's Python source. Enumerates @tool-decorated and imperatively-registered tools, then runs 13 detectors:

Detector Category Sev
Shell execution shell-exec high
Filesystem write/delete fs-write / fs-destructive med–high
Network egress network-egress medium
Code injection code-injection high
Over-broad params over-broad-param medium
Ambiguous/missing docstring ambiguous-description low–med
Secret read from env secret-in-env info
Path traversal path-traversal high
Prompt injection in docstring tool-description-injection medium
SSRF via URL param ssrf high
Resource URI → SQL injection mcp-resource-uri-sqli high
Tool shadowing (cross-tool) tool-shadowing medium

Tracks from X import Y [as Z] aliases so renamed dangerous imports don't slip through. Reports include a coverage.detectors_run list and limitations — absence of finding is NOT proof of safety.

Complements Snyk / Invariant Labs mcp-scan, which audits MCP configs and tool descriptions — this audits the source code of the server.

agent_tool_risk_audit

Takes a single agent tool's JSON schema and reports schema-level risks: over-broad params, ambiguous descriptions, missing constraints, exfil potential, dangerous defaults.

prompt_injection_audit

Static review of a system prompt / template for injection surface. Flags untrusted placeholders, missing delimiters, trust-boundary violations, dangerous-instruction patterns.

owasp_llm_classify

Map a finding or observation to OWASP LLM Top 10 (2025) with reasoning and severity. Useful in reports and ticket creation.

http_diff

Appsec-focused diff of two HTTP responses. For manual auth-bypass / IDOR triage. Highlights set/added/removed headers, status changes, body diffs, and security-relevant cookies.

jwt_inspect

Decode + audit a JWT. Flags alg:none, weak HS-secrets (small dictionary check), expiry, missing standard claims, suspicious kid (path traversal), external key URLs (jku, x5u).


Pentest pack (atomic primitives)

Bundled so an agent has the basics without needing five MCP installs. Each tool is one input → one output, no chaining.

  • default_creds_lookup — known default credentials by vendor / product (50+ products, aliases like fortigate, idrac, wp)
  • sensitive_files_list — curated sensitive paths per tech stack (common, php, wordpress, dotnet, java, node, python, k8s, docker, ci); returns paths only, does not probe
  • wordlist_gen — OSINT-driven wordlist generator (passwords / usernames / subdomains modes)
  • graphql_introspect — single introspection POST → schema summary + security observations
  • phpggc_generate — wraps phpggc CLI for PHP-deserialization gadget chains (graceful if binary missing)
  • interactsh_register / interactsh_poll / interactsh_stop — wraps interactsh-client CLI for OOB callback URL capture (blind SSRF / XXE / RCE confirmation). _stop terminates and cleans up the session; TTL gc runs on every register

Example output

Real output from three of the headline tools. Click to expand.

<details> <summary><b><code>mcp_server_audit</code></b> on a deliberately-bad fixture — finds <code>subprocess.run</code> shell-exec, over-broad <code>path: str</code> params, missing docstring, fs-write, and a secret read from env.</summary>

{
  "file": "sample_mcp_server.py",
  "tools_found": 4,
  "summary": {"high": 1, "medium": 5, "low": 1, "info": 1},
  "tools": [
    { "name": "safe_echo", "findings": [] },
    {
      "name": "run_cmd",
      "findings": [
        {"category": "ambiguous-description", "severity": "low",
         "message": "docstring is very short (4 chars) — risk of LLM misuse"},
        {"category": "over-broad-param", "severity": "medium",
         "message": "parameter `cmd`: command-like parameter typed as bare `str`"},
        {"category": "shell-exec", "severity": "high",
         "message": "calls `subprocess.run`"}
      ]
    },
    {
      "name": "read_anything",
      "findings": [
        {"category": "ambiguous-description", "severity": "medium",
         "message": "tool has no docstring — the LLM cannot reason about when to use it"},
        {"category": "over-broad-param", "severity": "medium",
         "message": "parameter `path`: path-like parameter typed as bare `str` (no allow-list)"}
      ]
    },
    {
      "name": "write_log",
      "findings": [
        {"category": "over-broad-param", "severity": "medium",
         "message": "parameter `path`: path-like parameter typed as bare `str` (no allow-list)"},
        {"category": "fs-write", "severity": "medium",
         "message": "opens file for writing (mode='a')"}
      ]
    }
  ],
  "file_level_findings": [
    {"category": "secret-in-env", "severity": "info",
     "message": "reads secret from env `SECRET_API_KEY` — ensure it is documented in README and never logged"}
  ]
}

</details>

<details> <summary><b><code>agent_tool_risk_audit</code></b> on a tool schema with bare-string <code>cmd</code> / <code>url</code>, a URL+data exfil shape, and <code>verify_ssl: false</code>.</summary>

{
  "tool_name": "shell_exec",
  "detected_format": "mcp",
  "findings": [
    {"category": "ambiguous-description", "severity": "medium", "path": "<tool>",
     "message": "description is very short (5 chars) — high risk of LLM misuse"},
    {"category": "risky-name-vague-desc", "severity": "medium", "path": "<tool>",
     "message": "tool name suggests it executes ('exec') but description is brief — agent may misuse"},
    {"category": "over-broad-param", "severity": "high", "path": "cmd",
     "message": "command-like param `cmd` is bare string — agent can execute arbitrary commands"},
    {"category": "over-broad-param", "severity": "high", "path": "url",
     "message": "url-like param `url` is bare string with no `pattern` — agent can reach arbitrary hosts (SSRF / exfil)"},
    {"category": "dangerous-default", "severity": "medium", "path": "verify_ssl",
     "message": "safety-related param `verify_ssl` defaults to `False` — disables a safeguard by default"},
    {"category": "exfil-shape", "severity": "medium", "path": "<tool>",
     "message": "tool accepts both a URL-like destination and a data-like payload — classic exfil shape"}
  ]
}

</details>

<details> <summary><b><code>jwt_inspect</code></b> on the well-known <code>jwt.io</code> default token — verifies signature against a small weak-secret dictionary, finds missing claims.</summary>

{
  "valid_structure": true,
  "header": {"alg": "HS256", "typ": "JWT"},
  "payload": {"sub": "1234567890", "name": "John Doe", "iat": 1516239022},
  "weak_secret": "your-256-bit-secret",
  "findings": [
    {"category": "missing-claim", "severity": "medium",
     "message": "no `exp` claim — token never expires"},
    {"category": "missing-claim", "severity": "low", "message": "no `iss` claim"},
    {"category": "missing-claim", "severity": "low", "message": "no `aud` claim"},
    {"category": "weak-secret", "severity": "high",
     "message": "signature verifies with common weak secret: 'your-256-bit-secret'"}
  ]
}

</details>

Recommended companion MCP servers

For deeper coverage in adjacent areas we explicitly recommend (and do not duplicate):


Install

pip install mcp-security-toolkit
{
  "mcpServers": {
    "sec": { "command": "mcp-security-toolkit" }
  }
}

Developing locally

python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev]"
pytest
ruff check .

End-to-end MCP smoke test (boots the server over stdio, lists tools, calls two of them):

python scripts/smoke_mcp.py

Defensive helpers — fix what we detect

The tools above find unsafe patterns in MCP servers. The mcp_security_toolkit.helpers package is the inverse: drop-in primitives an MCP author imports to make their tools safe by construction.

from mcp_security_toolkit.helpers import (
    safe_path, safe_filename, safe_url, safe_sql_identifier, evaluate_expression,
)

@mcp.tool()
def read_log(name: str) -> str:
    p = safe_path(name, root="/var/log/myapp", must_exist=True)
    return p.read_text()

@mcp.tool()
def save_upload(filename: str, data: bytes) -> str:
    name = safe_filename(filename)                          # basename-only
    (Path("/var/uploads") / name).write_bytes(data)
    return name

@mcp.tool()
def fetch_url(url: str) -> str:
    url = safe_url(url)                                     # blocks SSRF
    return httpx.get(url, timeout=5).text

ALLOWED_TABLES = {"users", "orders", "events"}

@mcp.tool()
def count_rows(table: str) -> int:
    table = safe_sql_identifier(table, allow=ALLOWED_TABLES)
    return db.execute(f"SELECT COUNT(*) FROM {table}").scalar()

@mcp.tool()
def evaluate_formula(expr: str, price: float, qty: int) -> float:
    return evaluate_expression(expr, variables={"price": price, "qty": qty})

Pure functions, no I/O, no globals. Each fixes the corresponding mcp_server_audit finding category in one line.

GitHub Action

Drop into any repo to run mcp_server_audit in CI, upload SARIF to the Security tab, and fail the build on configured severity:

# .github/workflows/mcp-audit.yml
on: [push, pull_request]
jobs:
  audit:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      security-events: write
    steps:
      - uses: actions/checkout@v5
      - uses: x0base/mcp-security-toolkit@v0.3
        with:
          path: src/my_mcp_server.py
          fail-on-severity: high

CLI

# Default (no args): start the MCP stdio server — what your client config invokes
mcp-security-toolkit

# Audit every MCP server your local Claude / Cursor / Claude Desktop is configured to launch
mcp-security-toolkit scan-installed
mcp-security-toolkit scan-installed --sarif > findings.sarif

# Zero-install run, via uv
uvx mcp-security-toolkit scan-installed

Treat tool outputs as untrusted data

Some tools return content from attacker-controlled sources: http_diff quotes target response bodies, interactsh_poll returns raw OOB requests, graphql_introspect returns target-controlled schema names. If such a string contains "ignore previous instructions...", an LLM agent reading it may follow the embedded instruction — classic indirect prompt injection. MCP clients should render tool outputs inside delimiters (<tool_output>...) and not flow them silently into the next prompt. See THREAT_MODEL.md.

Non-goals

  • No orchestration, chaining, or decision logic across tools — primitives only.
  • No reimplementation of full-featured offensive CLIs (sqlmap, ghauri, dalfox); where wrapping a small, focused CLI is a natural fit (phpggc, interactsh-client), we wrap it directly with a graceful "binary not found" path.
  • No novel offensive research — all referenced techniques cite public sources.

License

MIT.

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
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
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
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
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
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