What is SWT3 AI Witness?
SWT3 AI Witness is an MCP server that provides cryptographic accountability for every AI inference, tool call, and resource access. It hashes prompts and responses locally, records them as Merkle-accumulated anchors, and enables independent verification without exposing any data. It is built for developers and compliance teams who need to prove their AI followed rules—especially under regulations like the EU AI Act.
How to use SWT3 AI Witness?
Install the MCP server via npm (@tenova/swt3-mcp) and add it to your MCP host’s configuration with the command npx @tenova/swt3-mcp. This enables zero-config compliance governance for Claude Code, Cursor, Windsurf, and any MCP-compatible host. Alternatively, use the Python SDK (pip install swt3-ai) to wrap any OpenAI‑compatible client or tool functions and begin witnessing in three lines of code.
Key features of SWT3 AI Witness
- Witnesses every AI inference, tool call, and resource access
- Hashes all prompts/responses locally; raw text never leaves your infrastructure
- Detects instruction drift by hashing system prompts automatically
- Witnesses RAG context retrieval and relevance (AI‑RAG.1 and AI‑RAG.2)
- Verifies model weight integrity and adapter stacks
- Supports TPM platform attestation for hardware root of trust
- Offline verification of any anchor without network calls
- Trust Mesh for secure agent‑to‑agent cryptographic verification
Use cases of SWT3 AI Witness
- Generate audit‑ready evidence for EU AI Act compliance (e.g., Art. 12 logging)
- Prove that an AI agent only accessed allowed resources within its declared scope
- Maintain a tamper‑proof chain of custody for model weights and quantization
- Enable mutual trust between AI agents from different organizations via the Trust Mesh
- Demonstrate host firmware integrity in sovereign/air‑gapped deployments
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