MCP tool poisoning, rug pulls, and shadow servers are attacking production AI systems right now — with no detection in your security stack. SentinelMCP stops them at the gateway, with <5ms overhead.
Traditional security tools inspect bytes and headers. MCP tool poisoning lives in natural language — inside tool descriptions the LLM reads as instructions. SentinelMCP intercepts and inspects every tool schema before it reaches your agent.
No code changes required. Deploy as a sidecar or reverse proxy. Works with Claude, GPT-4, Gemini, and any MCP-compatible agent.
Every one of these has been demonstrated in production environments in 2025–2026. None are caught by SIEM, WAF, or EDR.
Hidden instructions embedded in tool descriptions. The agent follows them. The user never sees them. Demonstrated by Trail of Bits — exfiltrates entire chat history including credentials.
An MCP server you approved last week silently updates with malicious behavior this week. No re-approval, no alert. Your agent is now executing attacker instructions on every call.
Dev teams deploy unauthorized MCP instances to move fast. These unmanaged servers bypass all monitoring and policy enforcement, becoming invisible attack surfaces.
MCP servers aggregate credentials for dozens of enterprise services. One compromised server = keys to everything. Datadog audits found 12,000+ API keys exposed via MCP handling.
Typosquatted packages, fake "official" servers, and malicious dependency injection. The first malicious MCP package hit public registries September 2025. Many more have followed.
Malicious data injected into agent context propagates through entire workflows. Downstream agents make decisions on corrupted inputs, cascading compromise through multi-agent systems.
SentinelMCP sits between your agents and MCP servers. Five validation stages. Schema checks on discovery, lightweight flag lookups on invocation.
OAuth 2.1, TLS, domain allowlist validation before any schema is fetched
Hash every tool schema. Re-validate only on change. Detects rug pulls in real time
Local ML model inspects tool descriptions for injected instructions. No API round-trip
Intent-aware RBAC. Time-bound, context-aware permissions beyond static allow/deny
Every tool call logged with full context. Splunk, Datadog, or your SIEM of choice
| Product | Tool poisoning detection | Rug pull alerts | Shadow MCP discovery | Intent-aware policy | In-VPC deployment | LLM-agnostic |
|---|---|---|---|---|---|---|
| SentinelMCP | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
| MintMCP | ~ | ✗ | ~ | ✗ | ✗ | ✓ |
| Bifrost (OSS) | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ |
| Kong AI Proxy | ✗ | ✗ | ✗ | ✗ | ✓ | ✓ |
| Azure APIM | ✗ | ✗ | ✗ | ✗ | ~ | ✗ |
| Straiker | ~ | ✗ | ~ | ✗ | ~ | ✓ |
Annual contracts. In-VPC deployment included on Growth and Enterprise. SOC 2 Type II on request.
SentinelMCP is built by a founder with 19 years in payment infrastructure, PCI compliance, and high-volume transaction security — running systems that process millions of transactions with fraud detection baked in.
Most security founders understand either AI or enterprise security. We understand both — and we've shipped production systems under both constraints.
We're working with 5 enterprise teams to deploy SentinelMCP in production before general availability. No cost. Full access. Real security.
Or email us directly: hello@sentinelmcp.io