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MCP Safety Warden

gautamvarmadatla/mcpsafetywarden
6STDIOregistry active
Summary

A proxy layer that sits between Claude and any MCP server to scan tool calls before they execute. It runs behavioral profiling on every tool (effect class, destructiveness, retry safety), checks arguments for 20+ injection patterns including SSRF and path traversal, scans outputs for prompt injection attempts, and gates risky calls with alternatives. The security audit mode pulls source from GitHub and runs entropy scanning, AST taint analysis, and Bandit checks without making live calls. Integrates with Cisco AI Defense, Snyk, Kali Linux MCP for network recon, and Burp Suite MCP for HTTP probing. Tracks drift by hashing server source on first scan and alerts on schema or implementation changes. Useful when wrapping third-party servers or hardening your own tools against composition attacks and credential leakage.

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MCP Safety Warden

MCP safety warden is a proxy server that wraps any MCP server and adds behavioral profiling, security scanning, risk gating, and safe execution to its tools.

PyPI Python PyPI Downloads License CI CodeQL MCP Registry Docker Pulls OpenSSF Scorecard OpenSSF Best Practices GitHub Stars

Contents

  • Overview
  • Prerequisites
  • Installation
  • Configuration
  • MCP Integration
  • CLI Reference
  • Auxiliary Integrations
  • Development
  • Testing
  • Further reading

[!IMPORTANT] MCP security is an active research area. Recent surveys catalog a lot of protocol-specific threat categories spanning tool poisoning, prompt injection, rug-pull attacks, supply chain compromise, credential exfiltration, and composition attacks across the full server lifecycle. See Securing the MCP (OpenReview), Landscape & Threats (arXiv), When MCP Servers Attack (arXiv), and MCP-38 Taxonomy (arXiv).

Overview

Use as a proxy to add safety gating to any MCP server, or point it at a server you don't own and run a full security audit without making a single tool call.

Two operating modes
Fig 1. Two operating modes: proxy and audit

Behavioral profiling: Effect class, retry safety, destructiveness. LLM-assisted (Anthropic, OpenAI, Gemini, Ollama) with rule-based fallback. Observed stats (latency p50/p95, failure rate, output size) updated after every proxied call.

Security scanning: mcpsafety+ five-stage pipeline (Recon, Planner, Hacker, Auditor, Supervisor). Cisco AI Defense (AST/YARA). Snyk (metadata analysis). Kali and Burp Suite integrations enrich the pipeline with real network data and HTTP-layer probes. Source code scanning from GitHub with entropy, AST, taint flow, and rug-pull detection.

3e457b83-6980-49fc-b812-350ab94f5633
Fig 2. mcpsafety+ five-stage pipeline, triggered when you run a full security audit on any MCP server

Safe execution: Argument scanning (20+ attack categories, LLM second-pass). Two-layer output injection scanning. Risk gating with alternatives and per-tool policies. Drift detection on every call and standalone check.

fb949e62-5a3e-4a5c-be14-3523ef92295e
Fig 3. Safe execution pipeline: the five checks every proxied tool call passes through

CLI: 24 subcommands, interactive risk menu, --json flag on every command, --yes for CI.

What it detects

  • Prompt injection: tool outputs trying to hijack the agent: role hijacking, jailbreaks, fake system prompts, instruction overrides. Detects 11 obfuscation techniques including Unicode lookalikes, zero-width characters, and base64-encoded payloads.
  • Malicious tool metadata: descriptions containing injection strings, hardcoded secrets, suspicious download URLs, tool impersonation (shadowing), direct financial execution, system service modification, and untrusted external dependencies. Backed by 19 Snyk checks.
  • Argument injection: 20+ attack categories checked on every tool call before the call is forwarded: SSRF to cloud metadata endpoints (AWS, GCP, Azure, Alibaba), path traversal, credential file access (.aws, .ssh, .kube, .env), command injection, SQL/NoSQL/LDAP/XPath injection, XXE, template injection (SSTI), CRLF, null byte, deserialization payloads (Java, Python pickle, PHP, .NET), Windows UNC/ADS attacks, and base64-obfuscated variants of all of the above.
  • Source code risks: fetches the server's GitHub source and runs 6 analysis layers: entropy scanning for hardcoded secrets, AST taint flow tracking (parameter to dangerous sink), description-vs-implementation mismatch, Bandit and Semgrep SAST, and LLM cross-function reasoning. Supports Python and TypeScript/JavaScript.
  • Rug-pull and drift: stores a SHA-256 hash of the server's source on first scan and alerts if it changes. Catches description swaps, schema changes, and tool removal live on every call via a per-call drift guard.
  • Behavior anomalies: classifies every tool by effect class, destructiveness, and 7 risk tags: credential exposure, arbitrary execution, data exfiltration, filesystem access, lateral movement, privilege escalation, and prompt injection surface.
  • Composition attacks: analyzes tool sets for chaining risks: IDOR chains, read-write pairs, auth flow exploitation, write-then-execute sequences, and data accumulation + exfiltration paths across multiple tools.
  • Network and host risks: when Kali Linux MCP is registered: open ports, running services, OS fingerprint via nmap. When Burp Suite MCP is registered: HTTP-layer active probing and blind SSRF via out-of-band callbacks.
  • Credential exposure in outputs: redacts secrets from tool responses before storage. Injection-flagged responses are quarantined and never returned to the calling agent - stored under a run ID for forensic review.
  • CVE research and Arxiv findings: the mcpsafety+ Auditor stage cross-references discovered capabilities against known vulnerabilities and recent security research.

Prerequisites

  • Python 3.10 or later
  • At least one wrapped MCP server to proxy (stdio, SSE, or streamable_http)
  • Recommended: an LLM API key (Anthropic, OpenAI, or Gemini)

Without a key the wrapper operates in rule-based-only mode: lower confidence tool classification, regex-only injection scanning, no alternatives in the risk gate, no mcpsafety+ pipeline. For a fully local setup, run Ollama, set OLLAMA_MODEL, and pass --provider ollama explicitly (Ollama is not auto-detected).

[!NOTE] stdio servers that require local setup (stdio servers that need local configuration before starting - missing config files, credentials, data directories, or OS-specific dependencies) cannot be inspected by the wrapper - tool discovery will fail and 0 tools will be stored. You can still run a full source-code security scan without spawning the server by passing --github-url to scan / onboard, or the github_url parameter to security_scan_server. The mcpsafety+ pipeline will fetch and analyze the source directly from GitHub. sse and streamable_http servers are not affected.

Installation

pip install mcpsafetywarden

With all optional extras:

pip install "mcpsafetywarden[all]"

Or specific extras:

pip install "mcpsafetywarden[anthropic,snyk]"

From source:

git clone https://github.com/gautamvarmadatla/mcpsafetywarden
cd mcpsafetywarden
pip install .

The SQLite database is created automatically on first run in the platform user data directory (~/.local/share/mcpsafetywarden/ on Linux, ~/Library/Application Support/mcpsafetywarden/ on macOS, %APPDATA%\mcpsafetywarden\ on Windows). Override with MCP_DB_PATH.

Credential protection (automatic, no action required)

Secret values passed to register_server or onboard_server (Bearer tokens, API keys in headers or env) are automatically detected and replaced with opaque cref_ identifiers before anything touches the model context. The real credential is stored encrypted in the database and resolved silently at connection time. The model, conversation history, and logs only ever see cref_<id>.

Optional: at-rest encryption for stored credentials

pip install cryptography
python -c "from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())"

Set the printed key as MCP_DB_ENCRYPTION_KEY before starting the server. This encrypts both server credentials and cref_ values at rest.

Configuration

All configuration is via environment variables.

VariableDefaultPurpose
MCP_TRANSPORTstdioTransport mode: stdio, sse, or streamable_http
MCP_HOST127.0.0.1Bind address for HTTP transports
MCP_PORT8000Bind port for HTTP transports
MCP_AUTH_TOKEN(unset)Bearer token for HTTP transport auth
MCP_DB_ENCRYPTION_KEY(unset)Fernet key to encrypt stored credentials at rest
ANTHROPIC_API_KEY(unset)Enables Anthropic as LLM provider
OPENAI_API_KEY(unset)Enables OpenAI as LLM provider
GEMINI_API_KEY or GOOGLE_API_KEY(unset)Enables Gemini as LLM provider (GEMINI_API_KEY preferred)
OLLAMA_MODEL(unset)Model name for Ollama (e.g. llama3.1)
OLLAMA_BASE_URLhttp://localhost:11434/v1Ollama API base URL
SNYK_TOKEN(unset)Enables Snyk E001 prompt-injection detection
MCP_SCANNER_API_KEY(unset)Cisco AI Defense cloud ML engine key
MCP_SCANNER_LLM_API_KEY(unset)LLM key for Cisco internal AST analysis
MCP_DB_PATH(unset)Override the SQLite database file path
MCP_GRAPH_POLICYwarnGraph enforcement in safe_tool_call: off (disabled), warn (attach risk context to response), block (hard-block critical/high blast-radius tools unless approved=True)
GITHUB_TOKEN(unset)GitHub personal access token for source-code scanning (raises rate limit from 60 to 5,000 req/hour)

Security note: Never commit API keys or the encryption key. The wrapper strips its own secrets from child process environments before spawning stdio servers.

MCP Integration

Connecting with Claude Desktop

Add the wrapper to claude_desktop_config.json:

{
  "mcpServers": {
    "mcpsafetywarden": {
      "command": "mcpsafetywarden-server",
      "args": [],
      "env": {
        "ANTHROPIC_API_KEY": "sk-ant-...",
        "MCP_DB_ENCRYPTION_KEY": "<generated_fernet_key>"
      }
    },
    "filesystem": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-filesystem", "/Users/yourname/Documents"]
    }
  }
}

Register each server with the wrapper before use:

mcpsafetywarden register filesystem --transport stdio \
  --command npx \
  --args '["-y", "@modelcontextprotocol/server-filesystem", "/Users/yourname/Documents"]'

For a mandatory gateway setup where all tool calls must go through the wrapper, see docs/DEPLOYMENT.md.

Available MCP tools

See docs/TOOLS.md for the full tool reference.

ToolWhat it does
onboard_serverRegister + inspect + security scan in one call
register_serverRegister a server; optionally auto-inspect
inspect_serverRefresh tool list and profiles
check_server_driftDetect schema and tool-list drift against stored baseline
list_serversList all registered servers
list_server_toolsList tools on a server with summary profiles
preflight_tool_callRisk assessment without execution
safe_tool_callExecute with risk gating and alternatives
get_tool_profileFull behavior profile with observed stats
get_retry_policyRetry and timeout recommendations
suggest_safer_alternativeLLM-ranked safer substitutes
run_replay_testIdempotency test (calls tool twice)
security_scan_serverLive security audit (mcpsafety+, Cisco, Snyk)
scan_all_serversmcpsafety+ pipeline across all registered servers
get_security_scanLatest stored scan report
set_tool_policyPermanent allow/block policy for a tool
get_run_historyRecent execution history for a tool
ping_serverReachability check with latency
discover_serversScan filesystem for MCP client configs and extract server entries
onboard_discovered_serversRegister discovered servers in bulk
get_risk_graphBuild or query the inventory risk graph (servers, tools, findings, agent clients)
explain_tool_riskWalk risk paths for a tool: blast radius, composition risks, MITRE tags, recommended action
explain_client_riskAnalyze cross-server risks for all servers under one agent client
analyze_cve_blast_radiusReport CVEs affecting multiple servers under the same client
export_graphExport risk graph as JSON or Mermaid diagram

CLI Reference

24 subcommands covering all 25 MCP tools. Every command supports --json for machine-readable output and --yes / -y to skip confirmation prompts.

See docs/CLI.md for the full reference with flags and examples.

Auxiliary Security Tool Integrations

Kali Linux MCP, Burp Suite MCP, and Snyk each integrate automatically once registered. Kali enriches the Recon stage and ping_server with real nmap/traceroute data. Burp adds raw HTTP probing, out-of-band callbacks, and proxy evidence. Snyk analyses tool metadata for injection strings, tool shadowing, hardcoded secrets, and 16 other checks.

See docs/INTEGRATIONS.md for setup instructions.

Development

Install in editable mode:

pip install -e ".[all]"

Run the server and observe logs:

mcpsafetywarden-server 2>server.log

Every module uses logging.getLogger(__name__). The server does not call logging.basicConfig itself - configure logging in your entry point before importing.

Testing

pytest tests/ -v

Set an LLM API key to include LLM-assisted tests; without one they are skipped automatically. See docs/TESTING.md for step-by-step verification of classification, injection scanning, risk gating, and policy enforcement.

Further reading

DocContents
docs/TOOLS.mdFull reference for all 25 MCP tools
docs/CLI.mdCLI subcommands, flags, and examples
docs/INTEGRATIONS.mdKali, Burp Suite, and Snyk setup
docs/DEPLOYMENT.mdstdio, HTTP, container, and gateway deployment
docs/TROUBLESHOOTING.mdCommon errors and fixes
docs/SECURITY.mdSecrets, auth, isolation, and scanning details
docs/TESTING.mdVerification steps for each feature
docs/COMPARISON.mdComparison with related tools
docs/ROADMAP.mdPlanned features

Contributing

See CONTRIBUTING.md for code standards and pull request guidelines.

License

Apache License 2.0. See LICENSE for details.

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Categories
Security & Pentesting
Registryactive
Packagemcpsafetywarden
TransportSTDIO
UpdatedJun 10, 2026
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