AI Integration
Manage MnemoShare through AI assistants with 220+ tools via Model Context Protocol. AI-guided configuration, migrations, and workflow creation.
MCP Server
220+ tools exposed via Model Context Protocol (JSON-RPC 2.0). Full admin surface accessible to any MCP-compatible AI assistant.
MnemoShare is the first MFT platform with native AI integration at this scale. The MCP server exposes every admin capability — users, files, audit logs, DLP, compliance, workflows, email, migrations, and infrastructure — as structured tools that AI assistants can call directly. Not a chatbot wrapper. Real tools with JSON schema validation and approval workflows for sensitive operations.
AI-Guided Capabilities
- 220+ tools covering the full admin surface
- AI-guided migrations from MOVEit, GoAnywhere, Kiteworks, GlobalScape
- AI-guided workflow creation from natural language
- AI-guided configuration for DLP, SSO, SIEM, anomaly detection
Governance
- Two auth modes: API keys with MCP scopes + JWT sessions
- Change Management Request (CMR) workflow for approvals
- JSON schema validation on all tool inputs
- Documented change control for HITRUST compliance
AI-Powered Features
AI is embedded throughout MnemoShare — from content classification to workflow automation to natural language administration.
Intelligence
- DLP content classification via Anthropic/OpenAI
- LLM prompt step in workflow pipelines for file processing
- AI-assisted anomaly detection with contextual risk assessment
Automation
- Natural language admin — query DLP findings, manage users
- Describe data flows in English, AI builds the workflow
- AI-guided migration from legacy MFT systems
Enterprise Infrastructure
Deploy MnemoShare on the infrastructure your team already manages. Seven database backends, Kubernetes-native, and multi-architecture support.
Database
- 7 backends: MongoDB, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, DB2
- Per-tenant isolation (namespace, database, S3 bucket)
Deployment
- Kubernetes-native with Helm charts and CRD operator
- Docker Compose for single-node and dev
- Multi-replica HA with horizontal pod autoscaling
- ARM64 and AMD64 support
Beyond traditional MFT
Most managed file transfer platforms were designed before modern threats existed. Here is how MnemoShare compares.
| Capability | Traditional MFT | MnemoShare |
|---|---|---|
| AI integration | No AI support — admin via web UI only | 220+ MCP tools for Claude, GPT, and any MCP-compatible assistant |
| Admin interface | Click through web forms | Natural language: "create a folder for Q4 audit docs with 90-day retention" |
| AI in pipelines | No AI processing capabilities | LLM prompt step in workflows for AI-powered file processing and classification |
| Protocol | Proprietary admin API if any | Standard JSON-RPC 2.0 with OAuth 2.0 and API key auth |
| Database flexibility | Single database vendor | 7 backends: MongoDB, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, DB2 |
See how MnemoShare compares. Schedule a demo
Real-world use cases
Natural language admin
IT administrator connects Claude to MnemoShare MCP server. "Show me all users who haven't logged in for 30 days" returns a formatted list. "Disable user john@acme.com and revoke all API keys" — the AI submits a Change Management Request (CMR) for approval. A designated approver reviews and approves the change before it takes effect, creating the documented change control trail required by HITRUST.
AI-powered file processing
Workflow receives scanned invoices. LLM prompt step extracts vendor name, amount, and due date using AI. Results stored as metadata on MnemoShare. Downstream step routes to appropriate accounting folder.
Compliance automation
Compliance officer asks Claude: "Generate a compliance report for Q1 2026 covering all DLP findings and anomaly alerts." MCP tools query audit logs, aggregate findings, and produce a structured report.
Frequently asked questions
- Model Context Protocol (MCP) is a standard for AI assistants to interact with external tools. MnemoShare exposes 220+ tools via MCP using JSON-RPC 2.0 protocol — covering configuration, user management, file operations, audit queries, DLP policies, compliance, workflows, migrations, and more. Connect Claude, GPT, or any MCP-compatible assistant.
- Any MCP-compatible AI assistant works, including Anthropic Claude and OpenAI GPT. The MCP server supports both API key authentication and OAuth 2.0 user sessions.
- Yes. The workflow engine includes an LLM prompt step that sends file content or metadata to AI models (Anthropic/OpenAI) for classification, extraction, or transformation. Results flow to downstream workflow steps.
- MnemoShare supports seven production database backends: MongoDB, PostgreSQL, MySQL, SQLite, Microsoft SQL Server, Oracle Database, and IBM DB2. Deploy on the infrastructure your team already manages.
What is MCP and how does it work with MnemoShare?
Which AI assistants work with MnemoShare?
Can AI be used within file processing workflows?
What databases does MnemoShare support?
Ready to see MnemoShare in action?
Start a free trial, schedule a walkthrough, or dive into the docs.