ai-governance
50 servers · 3,772★ total
The Enterprise Architecture Governance Harness — strategy, architecture, delivery, and assurance using AI coding assistants
The action firewall for AI agents. Enforce policy and human approval before risky tool calls, shell commands, workflows, and production changes, with auditable evidence.
🛡️ The approval and policy layer for AI agents. Intercept risky actions before they run, block them, or approve them remotely.
Forge Orchestrator: Multi-AI task orchestration. File locking, knowledge capture, drift detection. Rust.
Agent orchestration & security template featuring MCP tool building, agent2agent workflows, mechanistic interpretability on sleeper agents, and agent integration via CLI wrappers
Governance gateway for AI agents — bounded, auditable, session-aware control with MCP proxy, shell proxy & HTTP API. Works with Cursor, Claude Code, Codex, and any MCP-compatible agent.
[L0 CONSTITUTION] arifOS — constitutional MCP kernel. Law, identity, F1–F13, VAULT999. Judges but never executes. DITEMPA BUKAN DIBERI.
Make AI coding agents safe to scale autonomously: assign work, cap spend, enforce policy, verify output, roll back failures, learn from loops, and prove ROI across every repo.
AI Governance Infrastructure — local evaluation. The governance layer for AI agents: a single compiled Rust binary that authenticates, authorises, rate-limits, logs, and costs every AI interaction. Self-hosted, air-gap capable, provider-agnostic.
Discover, govern and control access to MCP servers and agent skills across your organization
Demo agents showcasing CapiscIO Agent Guard and MCP Guard — trust badges, identity verification, and tool-level authorization for A2A and MCP protocols
The merge gate for AI-written code, with signed, replayable attestation. Works across Claude Code, Codex, Cursor, and Gemini CLI.
The open-source safety layer for AI agents — block unsafe tool calls, require approval, enforce budgets, audit, replay.
Governed state engine for AI agents: typed, executable knowledge artifacts with a code-like lifecycle
LLM guardrails & prompt injection detection for Python. Auto-instruments LangChain, CrewAI, OpenAI, LiteLLM + 8 more frameworks. PII masking, toxicity detection, policy CI/CD. One line, zero code changes.
Give your AI agents structure, guardrails, and full observability — the Agent control plane built on MCP.
Open-source model inventory & governance. Discovers every model, rule, and pipeline across all your platforms as one immutable, agent-queryable graph — git for models.
MCP EU AI Act Compliance Scanner - Open source tool to detect EU AI Act violations in codebases
Agent control plane for governed AI coding: validate changes, enforce policy gates, track findings, proofs, and evals based on your habits.
MCP middleware that blocks dangerous AI agent actions using a simple YAML config
Open-source governed memory for AI agents: prompt-injection-resistant writes, purpose-bound retrieval, provenance, and tamper-evident audit.
MCP-powered memory, policy, and experience layer for safer AI agents.
Trust infrastructure for AI agents — constitution enforcement and cryptographic receipts. Python SDK.
29 free, open-source plugins for Claude Code & Cowork — Google Drive, WhatsApp, YouTube, WordPress, Apollo & more. Built on the SOSA™ security framework.
A self-hosted MCP Gateway for enterprise environments. Secure AI agent connections to MCP servers with tool governance, multi-tenant isolation, and full observability. Built with Rust and Vue.
AI governance infrastructure for agentic systems. Rust library behind systemprompt.io — MCP, A2A, OAuth2, audit trails, compile-time extensions. Evaluate with systemprompt-template.
Open-source context engineering protocol for AI agents: governed retrieval, bounded multi-agent handoffs, MCP, provenance, recoverable effects, and replay.
Agents change faster than audits. Ancilis discovers what agents can do, classifies the data they touch, activates the right controls, and continuously proves compliance. Trust your agents in production.
Enterprise and government control plane for AI agents and MCP servers: govern, secure, observe, and audit. Rust, multi-provider (incl. major Chinese models).
AgenticStore: The secure toolkit for AI agents. Instantly equip Claude Desktop, Cursor, and Windsurf with 27+ MCP tools, persistent memory, and SearXNG search, all protected by a built-in PII prompt firewall to protect your data from being exposed to AI agents.
The verification layer for autonomous agents — an independent, capital-aware verdict before an irreversible action (/review), a cryptographically signed proof after, and a public on-chain track record, losses included. Free EdgeProof backtest validation. Underneath: memory, sandboxed execution, marketplace. Pay in sats, USDC (x402), or card.
Cut API bills 40–70% and stop rogue agent behaviour with a single static binary that sits between any agent and its MCP server — enforcing tool-level security, deduplicating and semantically caching calls, and exposing Datadog‑style observability.
Contract-first orchestration for long-running coding agents: scoped work records, local dispatch, review evidence, and enforcement provenance.
Agent Run Config — an open specification for declaring, packaging, securing, and sharing portable, governed AI agents. Like a Dockerfile for agents: one reviewable Agentfile for identity, tools, boundaries, policy, and OCI packaging.
Open-source compliance engine for AI agents. Rules, SDKs, and examples.
Terraform-style plan/apply for agent systems: versioned YAML for agents, tools, workflows, and policies; local-first SQLite state; MCP & HTTP tools; structured traces.
Governed AI coding on Claude Code: tiered pipelines, audit skills, MCP server. Claude generates, your or your team decides.
Stop AI agents from doing dangerous things through MCP. Wraps any MCP server with allow/block/hold-for-approval guardrails.
RSCT Workflow Framework — memory + MCP governance that stops AI coding agents from skipping plans, bypassing authorization, or breaking conventions.
Open-source MCP server giving AI agents 9 deterministic tools for the EU AI Act (Regulation 2024/1689). No LLM in the loop.
The natural-language command layer for an AI workforce — direct governed AI agents to deploy cloud infra, train ML, and run research, all under human policy & approval. Agentic command-and-control.
Official SDK for Rulecatch — AI coding analytics, monitoring, and rule enforcement for Claude Code, Cursor, and AI coding assistants
AI Governance Infrastructure — open gateway demo. Self-hosted systemprompt.io gateway in a single Rust binary: policy, audit trails, and cost attribution on every AI request, with the Systemprompt Bridge desktop app for Windows and macOS connecting Claude Code and Claude Cowork.
Security & governance guardrails for MCP agents in Java — audit trail, agent-to-tool authorization, prompt-injection detection and rate limiting as a zero-config Spring Boot starter.
Trust infrastructure for AI agents — constitution enforcement and cryptographic receipts. TypeScript SDK.
Research scaffold for multi-source music attribution with transparent confidence scoring. Companion code to Teikari, Petteri. 2026. “Governing Generative Music: Attribution Limits, Platform Incentives, and the Future of Creator Income.” SSRN Scholarly Paper No. 6109087. SSRN, https://dx.doi.org/10.2139/ssrn.6109087
Dual-protocol gateway: 62 MCP tools + A2A Protocol agent (82/82 TCK intentional) in a single governed runtime
APAI is an open protocol for describing, documenting, and validating artificial intelligence systems.