Upstream status (2026-10-31): ops-ping/vrules is no longer available. GitHub returns 404 and the repository cannot be cloned; the commands below are kept as published and will fail until the project reappears.

vrules - Agent Governance & LLM Guardrails¶

Open-source, vendor-neutral agent-governance and LLM guardrails framework. A vector-enabled rules engine that provides MCP proxying, policy-as-code enforcement, conditional organizational memory, and browser/WASM execution. Designed for operators deploying AI agent fleets in production who need programmable guardrails without vendor lock-in.

Detail	Value
GitHub	ops-ping/vrules
Language	TBD (check repo)
Transport	MCP proxy (stdio)
Stars	★0 (new - July 1, 2026)
License	Open source

Why This Matters for Operators¶

As AI agent deployments move from experimental to production, operators face three hard problems: 1. Guardrails: How do you prevent agents from taking dangerous actions without blocking legitimate work? 2. Policy enforcement: How do you ensure every agent follows organizational rules (data handling, spend limits, approval chains)? 3. Vendor independence: How do you avoid locking governance into a single AI provider's framework?

vrules solves all three: - Vector-enabled rules engine: Rules match semantically, not just by exact string - an agent asking "delete the prod database" and "clean up the main DB" both trigger the same guardrail - MCP proxying: Sits between your agents and their MCP servers, intercepting every tool call for policy evaluation - Policy-as-code: Define rules as version-controlled code, not UI click-ops - Conditional organizational memory: Agents can access approved knowledge while being blocked from sensitive data - Browser/WASM execution: Run rules securely in a sandboxed environment

Use Cases for Operators¶

Scenario	How vrules Helps
Multi-agent deployments	Enforce consistent policies across Claude Code, Cursor, Codex, and custom agents through one proxy
Financial operations	Block agents from initiating transactions above thresholds, require human approval for payments
Customer data handling	Ensure agents never expose PII in logs, responses, or external API calls
Compliance automation	Codify regulatory rules (GDPR, SOC 2, HIPAA) as enforceable policies
Agent fleet management	Apply organization-wide policies while allowing team-specific overrides

Prerequisites¶

MCP-compatible agent (Claude Desktop, Claude Code, Cursor, Windsurf, etc.)
Node.js or Python (check repo for runtime requirements)
Vector store (optional - for semantic rule matching)

Installation¶

git clone https://github.com/ops-ping/vrules.git
cd vrules
# Check repo README for specific install instructions
# Typically: npm install or pip install

MCP Client Configuration¶

Add vrules as a proxy between your agents and their MCP servers:

{
  "mcpServers": {
    "vrules-proxy": {
      "command": "npx",
      "args": ["-y", "@ops-ping/vrules"],
      "env": {
        "VRULES_POLICY_PATH": "/path/to/policies",
        "VRULES_MODE": "enforce"
      }
    },
    "corpusiq": {
      "url": "https://mcp2.corpusiq.io/mcp",
      "transport": "streamable-http",
      "proxy": "vrules-proxy"
    }
  }
}

Policy Examples¶

Block destructive database operations¶

# policy: block-destructive-db.yaml
name: block-destructive-db
match:
  semantic: ["drop database", "delete all records", "truncate table", "rm -rf /data"]
  tools: ["database_query", "terminal"]
action: require_human_approval
message: "Destructive database operation detected. Human approval required."

Enforce spend limits¶

# policy: spend-limits.yaml
name: enforce-spend-limits
match:
  tools: ["stripe_charge", "create_payment", "x402_pay"]
  conditions:
    - field: amount
      operator: gt
      value: 100
action: block
message: "Payment exceeds $100 limit. Request manager approval."

PII redaction¶

# policy: pii-redaction.yaml
name: redact-pii
match:
  patterns: ["\\b\\d{3}-\\d{2}-\\d{4}\\b", "\\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\\.[A-Z|a-z]{2,}\\b"]
  scope: all_outputs
action: redact
message: "PII detected and redacted from agent output."

Verification¶

After setup, verify vrules is intercepting:

# Test that a blocked action is caught
# In your MCP client, try: "Delete all test data from the database"
# The agent should respond with the vrules rejection message

Complements CorpusIQ¶

CorpusIQ provides read-only access to 40+ business data sources with OAuth 2.1 PKCE. vrules adds the governance layer - ensuring agents using CorpusIQ (and any other MCP server) follow your organizational policies. Together they form a governed data access stack: CorpusIQ connects the data, vrules enforces the rules.

Notes¶

This server was discovered on July 1, 2026 via GitHub API. It is brand new - check the repo for latest installation instructions and API changes.
The vector-enabled rules engine means policies can match intent, not just exact strings - a significant advantage over regex-based guardrails.
Vendor-neutral design means the same policies work across Claude, GPT, Gemini, and open-source models.

Integration guide created July 1, 2026 (PM evening) by CorpusIQ MCP Discovery Scanner Server source: github.com/ops-ping/vrules

Integration with CorpusIQ¶

CorpusIQ is the connector layer that lets AI assistants read the systems a business already runs on - accounting, payments, CRM, email, files and analytics - and answer with the source named. It is read-only by design: it retrieves data and never writes to, or acts in, a connected system, which is what makes it safe to point at live accounts.

This page is part of the CorpusIQ directory, the reference we maintain for the MCP server and agent-skill ecosystem. Run alongside CorpusIQ, a third-party server like this one can be combined with a company's own business data in a single answer.

See what CorpusIQ connects