ProofFlow

Local-first audit layer for Codex-compatible AI coding agent workflows.

Vibe coding is fast. Blind trust is not enough.

ProofFlow makes AI coding agents reviewable, traceable, and reversible through evidence-backed claims, policy gates, undo metadata, and human maintainer review.

▶ Watch the 72s demo: From AI agent claims to verifiable Proof Packets

📦 Example Proof Packet: docs/examples/proof_packet_codex_review.md

Problem

AI coding agents (Claude Code, Codex, Copilot Workspace) can modify files, run commands, and make decisions autonomously. But there's no standard way to:

• Audit what an agent did and why
• Gate high-risk actions before they execute
• Prove that a code review actually checked what it claims
• Undo agent-initiated changes with confidence

ProofFlow solves this by sitting between the agent and the filesystem, creating an evidence graph that links every action to its justification.

Quickstart

Docker (recommended)

git clone https://github.com/Hyperion-GPU/ProofFlow-v0.1.git
cd ProofFlow-v0.1
docker compose up

Backend: http://localhost:8787 | Frontend: http://localhost:5173

Manual

# Backend
cd backend && pip install -r requirements.txt
python -m uvicorn proofflow.main:app --port 8787

# Frontend
cd frontend && npm ci && npm run dev

MCP Integration (Claude Code / Codex)

pip install proofflow-mcp

Add to your project's .mcp.json:

{
  "mcpServers": {
    "proofflow": {
      "command": "proofflow-mcp",
      "env": { "PROOFFLOW_BASE_URL": "http://127.0.0.1:8787" }
    }
  }
}

Now your AI agent can scan files, review code, suggest actions, and export audit reports — all with enforced safety gates.

Architecture

AI Agent (Claude Code / Codex / Custom)
    |
    | MCP Protocol (stdio)
    v
ProofFlow MCP Server (12 tools)
    |
    | HTTP REST API
    v
ProofFlow Backend (FastAPI + SQLite)
    |
    |--- Evidence Graph: Cases > Artifacts > Claims > Evidence
    |--- Action Pipeline: Preview > Approve > Execute > Undo
    |--- Policy Gates: Risk classification > Owner decision
    |--- Proof Packets: Exportable markdown audit reports
    v
Local Filesystem (scanned files, git repos)

Core Capabilities

Evidence-Backed Code Review (AgentGuard)

Analyzes git diffs, generates risk-scored claims, and links each claim to specific evidence (changed lines, test results). No claim exists without supporting evidence.

File Audit & Organization (LocalProof)

Scans directories, indexes files with SHA-256 hashes, extracts text for full-text search, and suggests organization actions — all tracked in an auditable Case.

Policy Gate Enforcement

High-risk filesystem actions (moves to system paths, bulk operations) are automatically paused at pending_decision status. Requires explicit owner approval before execution.

Safety Invariants

• No Preview, no Action — destructive operations require two-phase confirmation
• No Evidence, no Claim — every assertion links to verifiable data
• No Undo, no Destructive Action — executed actions carry rollback metadata
• No Case, no Workflow — all work is tracked in auditable containers

MCP Tool Suite (12 tools)

health · scan · suggest · review · status · approve_execute · export_packet · search · list_cases · list_actions · undo · decide

Technical Stack

Security Features

• Optional API key authentication (PROOFFLOW_API_KEY)
• Rate limiting (PROOFFLOW_RATE_LIMIT)
• MCP concurrency guards (PROOFFLOW_MCP_MAX_CONCURRENT)
• Filesystem action scope restrictions (allowed_roots)
• CORS locked to localhost origins

Project Status

v0.1.0 — Stable release. All core workflows functional, tested, and documented.

Roadmap

• Multi-agent coordination (shared Cases across agents)
• Vector RAG for semantic evidence retrieval
• GitHub Actions integration (CI-triggered reviews)
• VS Code extension for inline audit visualization
• Cloud sync option for team workflows
• Webhook notifications for policy gate decisions

Development

# Run all tests
cd backend && python -m pytest          # 274 tests
cd frontend && npm run test             # 24 tests
cd mcp-server && pip install -e ".[dev]" && python -m pytest  # 24 tests

# End-to-end smoke test
python scripts/mcp_smoke.py --cleanup

# Demo workflow
python scripts/demo_workflow.py

License

MIT

Built by Hyperion-GPU — making AI agent workflows auditable, safe, and provable.