Wraps the VeriSwarm trust infrastructure API as 89 MCP tools covering trust scoring, policy enforcement, credential issuance, and compliance checks against OWASP, EU AI Act, NIST, and ISO 42001. You get decision gates (should this agent send email?), event ingestion for building trust profiles, Cedar policy evaluation with ABAC attributes, PII tokenization via Guard, and content provenance tracking. The setup CLI configures Claude Desktop or Cursor with API credentials and optional Guard hooks for activity logging. Useful when you need centralized trust evaluation across multiple AI agents or want to enforce compliance policies before actions execute. Free tier covers 5,000 queries per day and up to 10 agents.
Official client libraries, MCP server, and plugins for VeriSwarm — trust infrastructure for AI agents.
| Package | Language | Install | Description |
|---|---|---|---|
| Python SDK | Python | pip install veriswarm | REST client with Workflows, credential issuance, scoring profiles, LangChain adapter |
| Node.js SDK | JavaScript | npm install @veriswarm/sdk | ESM client for decisions, events, Workflows, agent management |
| MCP Server | Python | pip install veriswarm-mcp | 89 MCP tools for trust scoring, Guard, Passport, Vault, Workflows, Compliance (OWASP/EU AI Act/NIST/ISO 42001), Cedar policies + ABAC attributes, SRE, context governance, and content provenance (EU AI Act Art. 50). Works with Claude Desktop, Cursor, and any MCP client. (approve_jit_grant and issue_jit_token are deliberately not exposed to the LLM — those actions live behind an authenticated session in the web UI.) |
| OpenClaw Plugin | TypeScript | openclaw plugins install veriswarm | 11 tools + 3 hooks for OpenClaw agents. PII tokenization, policy enforcement, audit. Per-feature enable/disable. |
| GitHub Action | Python | GitHub Marketplace | CI/CD trust gate — check agent trust scores in your pipeline |
| JSON Schemas | JSON | npm install @veriswarm/schemas | Schema definitions for events, profiles, scores, and workflows |
Add to your MCP client config (Claude Desktop, Cursor, etc.):
{
"mcpServers": {
"veriswarm": {
"command": "python3",
"args": ["-m", "veriswarm_mcp"],
"env": {
"VERISWARM_API_URL": "https://api.veriswarm.ai",
"VERISWARM_API_KEY": "YOUR_API_KEY"
}
}
}
}
Or use the setup CLI:
pip install veriswarm-mcp
veriswarm-setup --platform claude --api-key YOUR_API_KEY
This installs the MCP server, Guard hooks (PII protection + activity logging), and Guard Proxy config.
from veriswarm import VeriSwarmClient
client = VeriSwarmClient("https://api.veriswarm.ai", "YOUR_API_KEY")
# Register an agent
agent = client.register_agent({"slug": "my-agent", "display_name": "My Agent"})
# Check if an action should be allowed
result = client.check_decision(agent_id="agt_123", action_type="send_email")
print(result["decision"]) # "allow", "review", or "deny"
# Ingest events
client.ingest_event(
event_id="evt_001", agent_id="agt_123", source_type="platform",
event_type="task.completed", occurred_at="2026-04-01T00:00:00Z",
payload={"task": "onboarding", "success": True}
)
import { VeriSwarmClient } from '@veriswarm/sdk'
const client = new VeriSwarmClient({
baseUrl: 'https://api.veriswarm.ai',
apiKey: 'YOUR_API_KEY'
})
const result = await client.checkDecision({
agentId: 'agt_123',
actionType: 'send_email'
})
{
plugins: {
entries: {
veriswarm: {
enabled: true,
config: {
apiKey: "YOUR_API_KEY",
piiEnabled: true,
policyEnabled: true,
injectionScan: true,
auditEnabled: true
}
}
}
}
}
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