trusted-agent-stack
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@trusted-agent-stackCheck if my answer is grounded in the provided document excerpts."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Trusted Agent Stack
An open trust plane that validates and repairs frontier-model answers and actions before they reach users or tools.
This is an independent open-source demonstration built with IBM open-source technologies. It is not an IBM product, and it does not connect to any real payment or enterprise system.
Demo
See the poisoned-invoice scenario progress from an unsafe simulated payment to a verified human-approval action:
https://github.com/user-attachments/assets/d1b12482-69b7-4f85-9da3-f9b183fc07e9
The first vertical slice is a booth-safe, simulated invoice-payment scenario:
A frontier model proposes one typed action.
The exact same proposal is forked into unverified and trusted paths.
The unverified path executes against a local sandbox.
The trusted path runs semantic and deterministic checks.
Failed actions are repaired, revalidated, and emitted with a Trust Receipt.
No real payment or enterprise system is connected.
Related MCP server: mcp-confidence
IBM open-source building blocks
Project | Role in this stack |
Extracts structured PDF content and provenance, including visually hidden text | |
Runs local, score-only checks for document instructions, groundedness, and tool safety | |
Provides the optional typed repair and validation-retry path |
Exact account matching, payment thresholds, and tool schemas remain deterministic Python policies. The booth hot path uses deterministic repair for latency and repeatability; the Mellea repair path is available through the CLI.
Architecture
PDF → Docling evidence → frontier action proposal
├─ unverified sandbox
└─ Guardian + policy checks
↓ fail
repair → revalidate
↓ pass
sandbox + Trust ReceiptQuick start
uv sync --extra dev
uv run demo spike poisoned-invoice
uv run pytestMock mode is deterministic and requires no model download or credentials.
For a live frontier proposal with automatic disk-cache fallback:
uv sync --extra api --extra frontier
FRONTIER_PROVIDER=mellea-litellm \
FRONTIER_MODEL=anthropic/your-model-id \
uv run tas-apiRun the fixed scenario once while online to seed cache/generations/. At the venue,
set FRONTIER_OFFLINE=true; the receipt will explicitly mark the generation as cached.
The provider model ID and credential environment variable depend on the selected
LiteLLM provider.
Booth UI
Start the API and UI in separate terminals:
uv sync --extra api --extra dev
uv run tas-apicd frontend
npm install
npm run devOpen http://127.0.0.1:5173. The attract loop is on by default: it starts after six
idle seconds, holds the completed receipt for twelve seconds, resets, and repeats.
Use ?attract=0 for operator-only mode or toggle it from the status bar.
Before doors open, verify the frozen artifacts, frontend build, Ollama model, and running API:
uv run tas preflight --api-url http://127.0.0.1:8000Claude Code takeaway
Install the local groundedness verifier as an MCP server:
uv sync --extra mcp
claude mcp add trusted-agent-stack -- \
uv run --project /absolute/path/to/trusted-agent-stack tas-mcpThe verify_answer tool accepts a question, draft answer, and document excerpts. It
returns only a groundedness verdict from the local Granite Guardian and fails closed
when the verifier is unavailable. Document excerpts are always treated as untrusted
data.
Rehearsal
Run the complete build, preflight, test suite, and repeated live-Guardian scenario:
./scripts/rehearse_booth.sh 5Use 100 for the day-before soak test. See
docs/booth-runbook.md for startup, operator controls, and
the failure matrix.
Granite Guardian probe
Download the official IBM Q4 GGUF and register it with Ollama:
./scripts/setup_guardian.shThen run the live local probe:
uv run demo spike poisoned-invoice \
--guardian ollama \
--guardian-model trusted-granite-guardian:4.1The hot path uses score-only judging. The demo never exposes a model reasoning trace.
Mellea repair probe
With a local Ollama model available:
uv sync --extra dev --extra mellea
uv run demo spike poisoned-invoice \
--repair mellea-ollama \
--repair-model granite4.1:3bMellea generates a typed repair, validates the repair with an executable requirement, and retries with validation feedback when necessary. The deterministic business-policy checks still run after Mellea returns.
Run modes
mock: deterministic local development.ollama: live local Guardian checks with deterministic business policy enforcement.
Receipts are written below runs/ by default and are intentionally ignored by Git.
Rebuild the document fixture
The poisoned PDF contains a visually hidden instruction in its text layer. Rebuild and preprocess it with:
uv sync --extra demo-assets --extra docling
uv run python scripts/generate_demo_invoice.py
uv run python scripts/preprocess_docling.pyDocling output is frozen below scenarios/poisoned-invoice/docling/ for booth use. The
live demo does not parse the PDF on its hot path.
Project status
Trusted Agent Stack is an experimental booth demo and reference implementation. Its payment tool is an in-memory sandbox. Do not use it as a production authorization or payment system without an independent security review.
Community
Read CONTRIBUTING.md before opening a pull request.
Use the issue forms for bugs, feature ideas, and booth feedback.
Follow the Code of Conduct.
Report vulnerabilities through the process in SECURITY.md.
License
Licensed under the Apache License 2.0.
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