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Integration templates, evaluation paths, and reference material.

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Core context and project basics

  • Introduction3

    Platform context and entry points

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PROVNAI Ecosystem#

The PROVNAI initiative provides the trust layer for the agentic future. Below is the unified Nexus for all core repositories, protocols, and forensic tools in the ecosystem.

Integration-Ready Templates#

Pre-configured deployment and evaluation paths for testing core PROVNAI ecosystem components with minimal overhead.

Deploy on Railway

Bring up an evaluation instance with the right port mapping, health checks, and deployment caveats.

McpVanguard on Railway

Deploy the current McpVanguard gateway on Railway and attach a remote MCP client with the right auth headers.

Agent Execution Queue

Create an agent, queue work, and poll the resulting job with exact request and response examples.

Verifiable Pipeline Audit Trail

Generate valid and tampered audit exports, then verify them with the public CLI.


Repositories#

McpVanguard

McpVanguard

An open-source security proxy and active firewall for the Model Context Protocol (MCP).

SecurityPython

provn-sdk

provn-sdk

Client-side SDK for privacy-preserving cryptographic signing. Hash and sign claims locally.

CryptoSDK

Links#

  • GitHub Organization
  • Official Website
NextAPI Reference
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PROVN.AI

Security infrastructure for autonomous AI agents. MCP tool-call protection, governed execution, and cryptographic evidence for production AI systems.

Documentation

  • Introduction
  • Getting Started
  • Architecture
  • Ecosystem Overview

Ecosystem

  • Provnai Homepage
  • Open Source code
  • Release Notes
  • GitHub

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