About veriswarm-mcp
veriswarm-mcp is VeriSwarm’s MCP server for trust and governance functions used by AI agents. Its 89 tools cover trust scoring, credentials, compliance, and workflows.
Key features
- 0189 MCP tools
- 02Trust scoring and Guard
- 03Passport and Vault
- 04Workflows and compliance checks
- 05Cedar policies and ABAC attributes
- 06SRE and content provenance
Use cases
- 01Check an agent’s trust score
- 02Apply policies and access controls
- 03Run compliance and governance checks
MCP support
The server exposes 89 tools to MCP clients such as Claude Desktop and Cursor, covering trust scoring, Guard, Passport, Vault, workflows, compliance, and content provenance. JIT grant approval and JIT token issuance are not exposed to the LLM.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEVeriSwarm SDK & Integrations
Official client libraries, MCP server, and plugins for VeriSwarm — trust infrastructure for AI agents.
Packages
| 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 |
Quick Start
MCP Server (Recommended)
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.
Python SDK
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}
)
Node.js SDK
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'
})
OpenClaw Plugin
{
plugins: {
entries: {
veriswarm: {
enabled: true,
config: {
apiKey: "YOUR_API_KEY",
piiEnabled: true,
policyEnabled: true,
injectionScan: true,
auditEnabled: true
}
}
}
}
}
Free Plan
Get started with no credit card:
- 5,000 trust score queries/day
- Up to 10 agents
- Unlimited event ingestion
- Portable credentials issued on demand (rate-limited per plan; see pricing for current limits)
Sign up at veriswarm.ai.
Links
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.