What can you do with this server?

The PiQrypt MCP Server provides cryptographic audit trail capabilities for AI agents, enabling tamper-proof recording, verification, and export of agent decisions for compliance purposes. * Stamp Events (piqrypt_stamp_event): Cryptographically sign and record agent decisions using Ed25519 signatures and hash chaining (AISS v2.0), supporting compliance with GDPR Art.22, EU AI Act Art.13, HIPAA, and SEC/FINRA. * Verify Chain Integrity (piqrypt_verify_chain): Validate that an agent's event history is intact, detecting tampering, missing records, hash chain breaks, or forks. * Export Audit Trails (piqrypt_export_audit): Export complete audit logs in portable JSON or encrypted .pqz format, with optional PiQrypt CA certification for legal admissibility (eIDAS Art.26). * Search Events (piqrypt_search_events): Query event history by type, time range, or session to reconstruct agent activity with full chain metadata. * Broad Integration: Works with MCP-compatible clients (Claude, Cursor, VS Code, Continue, Windsurf, n8n) and automation platforms like Make.com and Zapier.

Which integrations are available for this server?

Enables cryptographic audit trails for n8n automation workflows, allowing AI agents to sign decisions with cryptographic proof, verify event chain integrity, and export compliance-ready audit logs for SEC, FINRA, GDPR, or HIPAA requirements.

How do I use PiQrypt MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@PiQrypt MCP Server Sign my latest decision with a cryptographic proof for the audit trail" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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PiQrypt MCP Server

by PiQrypt

Overview Schema Related Servers Score Discussions

Python

Hybrid

PiQrypt MCP Server

Cryptographic Audit Trail for AI Agents via Model Context Protocol

Related MCP server: DCL Evaluator

🚀 What is PiQrypt MCP?

PiQrypt MCP Server provides Model Context Protocol access to PiQrypt — the post-quantum cryptographic audit trail for AI agents.

Use cases:

🤖 AI Agents: Sign every decision with cryptographic proof
📊 n8n Workflows: Add audit trail to automation workflows
🏦 Trading Bots: SEC/FINRA compliance for automated trading
👥 HR Automation: GDPR-compliant AI hiring decisions
🏥 Healthcare AI: HIPAA audit trail for medical decisions

📦 Installation

Prerequisites

1. Install piqrypt (required — Python 3.8+)

pip install piqrypt

The MCP server delegates all cryptographic operations to the piqrypt Python package. If it is not installed, the server will return a clear error on every tool call.

2. Install the MCP server (Node.js 18+)

npm install -g @piqrypt/mcp-server

Install via npx (no global install)

npx @piqrypt/mcp-server

Build from source

git clone https://github.com/piqrypt/piqrypt-mcp-server
cd piqrypt-mcp-server
npm install
npm run build

PIQRYPT_PYTHON — custom Python environment

By default the server uses python3 (Linux/Mac) or python (Windows). If piqrypt is installed in a virtual environment, set this variable to point to the right interpreter:

Windows

set PIQRYPT_PYTHON=C:\path\to\venv\Scripts\python.exe

Linux / Mac

export PIQRYPT_PYTHON=/path/to/venv/bin/python

To make it persistent, add it to your MCP client configuration:

{
  "mcpServers": {
    "piqrypt": {
      "command": "piqrypt-mcp-server",
      "args": [],
      "env": {
        "PIQRYPT_PYTHON": "/path/to/venv/bin/python"
      }
    }
  }
}

⚙️ Configuration

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "piqrypt": {
      "command": "piqrypt-mcp-server",
      "args": []
    }
  }
}

n8n (v1.88+)

Install n8n MCP integration
Add PiQrypt MCP server to configuration
Use in workflows via MCP node

Compatible with

MCP clients

Client	Version	Notes
Any MCP-compatible client	MCP spec 2024-11+	stdio transport
n8n	1.88+	via MCP node
Cursor	any	add to mcp settings
VS Code	any	add to mcp settings
Continue	any	add to mcp settings
Windsurf	any	add to mcp settings

Automation platforms (via MCP node)

Platform	Integration	Use case
n8n	MCP node (native)	No-code audit trail
Make.com	HTTP module	Webhook-triggered stamping
Zapier	Webhooks + HTTP	Basic event recording

What you can audit with PiQrypt MCP

Every tool call goes through the same 4 operations — stamp, verify, export, search. Here is what that means in practice depending on your context:

Automated trading / finance Any agent that submits orders, rebalances portfolios, or triggers transactions can stamp each decision before execution. The signed chain is exportable for SEC/FINRA audit without any additional infrastructure.

HR and hiring automation Any workflow that evaluates candidates, scores CVs, or routes applicants can stamp each decision. Provides a GDPR Art.22 compliant audit trail for AI-assisted hiring — who decided what, when, and what data was used (hashed, never stored raw).

Content and publishing pipelines Any agent that drafts, approves, or publishes content can stamp each step. Useful when multiple AI agents collaborate and you need to prove attribution — which agent wrote what, in what order.

DevOps and CI/CD Any agent that triggers deployments, merges branches, or rotates secrets can stamp each action. Provides a tamper-evident record of infrastructure changes made by autonomous agents.

Healthcare and medical AI Any diagnostic or triage agent can stamp each recommendation. Provides a HIPAA-compliant audit trail linking each AI output to a verifiable agent identity.

The common pattern in all cases:

[Agent makes decision]
↓
piqrypt_stamp_event    ← sign + chain
↓
[Agent executes action]
↓
piqrypt_export_audit   ← portable proof, verifiable
                          without PiQrypt installed

🛠️ Available Tools

1. `piqrypt_stamp_event`

Sign an AI decision with cryptographic proof.

Parameters:

agent_id (string, required): Agent identifier
payload (object, required): Decision data
previous_hash (string, optional): Previous event hash for chaining

Example:

const event = await mcp.call('piqrypt_stamp_event', {
  agent_id: 'trading_bot_v1',
  payload: {
    action: 'buy',
    symbol: 'AAPL',
    quantity: 100,
    price: 150.25
  }
});

Returns:

{
  "version": "AISS-1.0",
  "agent_id": "trading_bot_v1",
  "timestamp": 1739382400,
  "nonce": "uuid-...",
  "payload": { ... },
  "previous_hash": "sha256:...",
  "signature": "base64:..."
}

2. `piqrypt_verify_chain`

Verify integrity of event chain.

Parameters:

events (array, required): Events to verify

Example:

const result = await mcp.call('piqrypt_verify_chain', {
  events: [event1, event2, event3]
});

Returns:

{
  "valid": true,
  "events_count": 3,
  "chain_hash": "sha256:...",
  "errors": []
}

3. `piqrypt_export_audit`

Export audit trail for compliance.

Parameters:

agent_id (string, required): Agent to export
certified (boolean): Request PiQrypt certification
output_format (string): json or pqz

Example:

const audit = await mcp.call('piqrypt_export_audit', {
  agent_id: 'trading_bot_v1',
  certified: true,
  output_format: 'json'
});

4. `piqrypt_search_events`

Fast search via SQLite index.

Parameters:

event_type (string, optional): Filter by type
from_timestamp (number, optional): Start time
to_timestamp (number, optional): End time
limit (number): Max results (default: 100)

Example:

const trades = await mcp.call('piqrypt_search_events', {
  event_type: 'trade_executed',
  from_timestamp: 1739300000,
  limit: 50
});

📊 Vigil Dashboard (optional, free)

Every stamped event is visible in Vigil — PiQrypt's local monitoring dashboard.

Note: Vigil is not launched automatically by the MCP server. You must start it separately before opening the dashboard.

piqrypt vigil
# → http://localhost:8421

Free tier includes: chain health, VRS risk score, 7-day history, CRITICAL alerts. Upgrade to Pro for 90-day history, TrustGate governance, and post-quantum signatures.

🗑️ Managing Agents

Agents are created automatically on first stamp. To view and delete agents:

Start Vigil: piqrypt vigil
Open http://localhost:8421
Go to All Agents view
Check the agents to delete → click ✕ Delete selected
Confirm — Vigil returns to the welcome screen when no agents remain

Agents are stored in ~/.piqrypt/agents/ on your machine. Deleting an agent removes its keys and event history permanently.

🔒 Security Model

Process Isolation

┌─────────────────────────────────────┐
│  MCP Client (any MCP-compatible client)     │
│  ↓ JSON-RPC over stdio              │
├─────────────────────────────────────┤
│  MCP Server (TypeScript/Node.js)    │  ← No crypto here
│  ↓ subprocess call                  │
├─────────────────────────────────────┤
│  Python Bridge (bridge.py)          │
│  ↓ invokes CLI                      │
├─────────────────────────────────────┤
│  PiQrypt CLI (Python)               │
│  ↓ uses                             │
├─────────────────────────────────────┤
│  Core Crypto (aiss package)         │  ← All crypto here
│  • Ed25519 / Dilithium3             │
│  • RFC 8785 canonical JSON          │
│  • Hash chains                      │
└─────────────────────────────────────┘

Guarantees

✅ Private keys never exposed to MCP layer
✅ All crypto in Python (Ed25519, Dilithium3)
✅ Same security as CLI (process isolation)
✅ RFC AISS-1.1 compliant (identical output)
✅ Input validation before subprocess call

📚 Examples

Trading Bot (n8n)

[Webhook: price alert] 
    ↓
[AI Decision: buy/sell?]
    ↓
[PiQrypt MCP: stamp decision]  ← Audit trail
    ↓
[Execute trade API]
    ↓
[Database: store proof]

HR Automation

[Upload CV]
    ↓
[AI Agent: evaluate candidate]
    ↓
[PiQrypt MCP: stamp evaluation]  ← GDPR compliance
    ↓
[Email HR team]

🧪 Testing

# Build
npm run build

# Test bridge
python3 src/python/bridge.py stamp '{"agent_id":"test","payload":{"action":"test"}}'

# Test MCP server (manual)
node dist/index.js
# Then send MCP request via stdin

🔧 Troubleshooting

`Error: piqrypt is not installed in this Python environment`

The Python interpreter used by the MCP server cannot find the piqrypt package.

Fix:

pip install piqrypt

If piqrypt is installed in a virtual environment and not the system Python, set PIQRYPT_PYTHON to point to the correct interpreter:

# Linux / Mac
export PIQRYPT_PYTHON=/path/to/venv/bin/python

# Windows
set PIQRYPT_PYTHON=C:\path\to\venv\Scripts\python.exe

To verify which Python the server will use:

# Linux / Mac
$PIQRYPT_PYTHON -c "import aiss; print('ok')"

# Windows
%PIQRYPT_PYTHON% -c "import aiss; print('ok')"

📖 Documentation

🤝 Contributing

We welcome contributions! See CONTRIBUTING.md.

📄 License

MCP Server → MIT License - see LICENSE PiQrypt Core → free tier + commercial tiers

🔗 Links

PiQrypt Core: https://github.com/piqrypt/piqrypt
MCP Protocol: https://modelcontextprotocol.io
n8n: https://n8n.io
Documentation: https://docs.piqrypt.com

Built with ❤️ by PiQrypt Inc.

Available Tools

4 tools

piqrypt_export_auditA

Export the complete agent audit trail to a portable JSON archive. Set certified=true to request a PiQrypt CA signature for legal admissibility (eIDAS Art.26). The export is self-contained and verifiable without PiQrypt installed.

ParametersJSON Schema

Name	Required	Description	Default
`agent_id`	Yes	Agent ID to export
`certified`	No	Create certified export (requires Pro license)
`output_format`	No	Output format (json or encrypted pqz archive)	json

TDQS

A4.2/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that export is self-contained and verifiable, and mentions Pro license requirement. Does not detail side effects or reading behavior; with no annotations, this is moderate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, each adding essential information: purpose and certification detail. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks output schema but describes the result as a portable JSON archive. Missing details on error conditions or what the audit trail contains, but adequate for a simple export.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. Description adds value for the certified parameter (legal admissibility) and clarifies the export scope (complete trail).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool exports a complete agent audit trail to JSON, using a specific verb and resource. It distinguishes well from sibling tools like piqrypt_search_events.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides context on when to use certified=true and notes the export is self-contained. Lacks explicit when-not-to-use or alternatives, but siblings are distinct actions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

piqrypt_search_eventsA

Search the agent's cryptographic event history by type, time range, or session. Returns signed events with chain metadata. Use to reconstruct what an agent did during a specific period.

ParametersJSON Schema

Name	Required	Description
`event_type`	No	Filter by event type (e.g., "trade_executed", "decision_made")
`from_timestamp`	No	Start timestamp (Unix UTC seconds)
`to_timestamp`	No	End timestamp (Unix UTC seconds)
`limit`	No	Maximum number of results

TDQS

A3.9/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description states it returns signed events with chain metadata, implying read-only. However, it does not mention authentication, rate limits, pagination behavior, or what happens with empty results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences with no filler. The action verb is front-loaded, and every sentence adds useful context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema; description gives a brief idea of return values (signed events with chain metadata) but omits details like event structure or metadata fields. The mention of session without a corresponding parameter reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description adds minimal value beyond repeating filter options. It mentions session but the schema lacks a session parameter, creating slight ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states verb (search), resource (cryptographic event history), and scope (by type, time range, or session). Distinguishes from siblings like piqrypt_stamp_event (create) and piqrypt_export_audit (export).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a clear use case ('reconstruct what an agent did during a specific period'), but does not explicitly state when not to use or mention alternatives among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

piqrypt_stamp_eventA

Create a tamper-proof cryptographic record of an agent decision. Signs the event with Ed25519, links it to the previous event in a hash chain (AISS v2.0). Call this after every significant agent action. Required for GDPR Art.22, EU AI Act Art.13, HIPAA audit trail, SEC/FINRA trading compliance.

ParametersJSON Schema

Name	Required	Description
`agent_id`	Yes	Agent identifier (e.g., "trading_bot_v1", "hr_decision_engine")
`payload`	Yes	Event payload containing decision data (JSON object)
`previous_hash`	No	Optional hash of previous event for chain integrity

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description discloses key behaviors: tamper-proof record creation, Ed25519 signing, and hash chain linking. It lacks details on side effects, idempotency, or error handling, but covers essential traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise at two sentences, front-loading the purpose and including key details. It is efficient but could be slightly more structured by grouping regulations separately.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 3 parameters and no output schema, the description covers purpose, usage, and behavioral details adequately. The lack of return value description is a minor shortfall, but overall it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already describes all three parameters with 100% coverage. The description adds no additional semantics beyond the schema, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a cryptographic record, specifying the signing algorithm (Ed25519) and chaining mechanism (AISS v2.0), which distinguishes it from sibling tools for export, search, and verification.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly advises 'Call this after every significant agent action' and lists regulatory requirements, providing strong contextual cues. However, it does not explicitly exclude cases where the tool should not be called.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

piqrypt_verify_chainA

Verify that an agent's decision history is intact and untampered. Detects modified events, missing events, hash chain breaks, and forks. Call before trusting any historical agent output.

ParametersJSON Schema

Name	Required	Description	Default
`events`	Yes	Array of PiQrypt events to verify

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description adequately describes what the tool detects (tampering evidence). However, it lacks details on output/return behavior (e.g., error vs result) and side effects, which would improve transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no wasted words, front-loaded with the main action and key details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with full schema coverage, the description covers purpose and usage. It lacks specification of return value (e.g., boolean, report), but overall is complete enough for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the description does not add additional meaning beyond the schema's 'Array of PiQrypt events to verify'. Baseline score of 3 is appropriate as the schema already carries the parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: verifying integrity of an agent's decision history. It lists specific detection capabilities (modified events, missing events, etc.) and distinguishes itself from siblings by its verification role.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes explicit usage guidance: 'Call before trusting any historical agent output.' While it doesn't explicitly exclude scenarios or name alternatives, the clear context is sufficient for an agent to decide when to invoke this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

4 tool updatesv1.5.3Apr 24, 2026
- Addedpiqrypt_export_audit
- Addedpiqrypt_search_events
- Addedpiqrypt_stamp_event
- Addedpiqrypt_verify_chain

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A4.3/5.0

Disambiguation5/5

Each tool has a distinct purpose: export, search, stamp, and verify. No overlap, clear boundaries.

Naming Consistency5/5

All tools follow the consistent pattern 'piqrypt_verb_noun' (export_audit, search_events, stamp_event, verify_chain). Perfect uniformity.

Tool Count5/5

Four tools cover the essential operations for a cryptographic audit trail server without redundancy or deficiency.

Completeness5/5

The set provides a complete workflow: create events (stamp), search them, export them, and verify integrity. No obvious gaps for the domain.

Maintenance

ActivityInactive

ResponsivenessNo issues

Resources

Need Help?

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PiQrypt MCP Server

🚀 What is PiQrypt MCP?

📦 Installation

Prerequisites

Install via npx (no global install)

Build from source

PIQRYPT_PYTHON — custom Python environment

⚙️ Configuration

Claude Desktop

n8n (v1.88+)

Compatible with

MCP clients

Automation platforms (via MCP node)

What you can audit with PiQrypt MCP

🛠️ Available Tools

1. piqrypt_stamp_event

2. piqrypt_verify_chain

3. piqrypt_export_audit

4. piqrypt_search_events

📊 Vigil Dashboard (optional, free)

🗑️ Managing Agents

🔒 Security Model

Process Isolation

Guarantees

📚 Examples

Trading Bot (n8n)

HR Automation

🧪 Testing

🔧 Troubleshooting

Error: piqrypt is not installed in this Python environment

📖 Documentation

🤝 Contributing

📄 License

🔗 Links

Available Tools

Tool Schema Changelog

Maintenance

Resources

Looking for Admin?

Related MCP Connectors

Related MCP Servers

Latest Blog Posts

MCP directory API

1. `piqrypt_stamp_event`

2. `piqrypt_verify_chain`

3. `piqrypt_export_audit`

4. `piqrypt_search_events`

`Error: piqrypt is not installed in this Python environment`