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MCP Integration

Model Context Protocol (MCP) is an industry-standard protocol for connecting AI assistants to external services. Archivus supports MCP as both a client and server, enabling seamless integration with your existing tools.

What Is MCP?

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Model Context Protocol:

  • Open standard for AI tool integration
  • Bidirectional communication
  • Secure credential management
  • Health monitoring and failover

Think of MCP as:

  • USB for AI assistants
  • Plug-and-play tool integration
  • No custom code required
  • Standard interface for all tools

MCP as Client

Connect Archie to external MCP servers:

Supported Integrations

GitHub

  • Create and manage issues
  • Search repositories
  • Manage pull requests
  • Access code and commits

Slack

  • Send notifications
  • Search message history
  • Post updates to channels
  • Manage workspace

Databases

  • Query internal databases
  • Run reports
  • Update records
  • Aggregate data

Custom APIs

  • Any MCP-compatible service
  • Internal tools and systems
  • Third-party platforms
  • Legacy systems

Example Integration: GitHub

User: "Create a GitHub issue for the bugs in the QA report"

Archie:
  1. Searches for "QA report" in documents
  2. Extracts bug descriptions using AI
  3. Creates GitHub issues via mcp_github_create_issue
  4. Links issues back to source document

Result: Created 3 GitHub issues:
  - #142: Login form validation error
  - #143: Dashboard loading timeout
  - #144: Export CSV formatting issue

All issues tagged with source: QA-Report-2026-02.pdf

MCP as Server

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Expose Archivus capabilities to external AI systems:

Available Tools

Document Operations

  • archivus_search_documents - Search document library
  • archivus_get_document - Retrieve document content
  • archivus_upload_document - Upload new document
  • archivus_analyze_document - AI analysis

Knowledge Graph Enterprise

  • archivus_query_graph - Search entities and relationships
  • archivus_validate_claim - Verify facts
  • archivus_get_entity - Retrieve entity details

Workspace Management

  • archivus_list_workspaces - Get available workspaces
  • archivus_create_workspace - Set up new workspace
  • archivus_get_summary - AI-generated overview

Analytics

  • archivus_get_stats - Usage and performance metrics
  • archivus_generate_report - Create custom reports

Use Cases

Claude Desktop Integration

{
  "mcpServers": {
    "archivus": {
      "command": "npx",
      "args": ["-y", "@archivus/mcp-server"],
      "env": {
        "ARCHIVUS_API_KEY": "your-api-key",
        "ARCHIVUS_TENANT_ID": "your-tenant-id"
      }
    }
  }
}

Custom AI Application

from mcp import ClientSession
from mcp.client.stdio import stdio_client

# Connect to Archivus MCP server
async with stdio_client("npx", ["-y", "@archivus/mcp-server"]) as client:
    async with ClientSession(client[0], client[1]) as session:

        # Search documents
        result = await session.call_tool(
            "archivus_search_documents",
            {"query": "contract expiring Q1 2026"}
        )

        # Analyze results
        for doc in result.content:
            analysis = await session.call_tool(
                "archivus_analyze_document",
                {"document_id": doc.id}
            )

MCP Server Configuration

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Adding MCP Servers

Via Web Interface:

  1. Navigate to Settings → Integrations → MCP
  2. Click "Add MCP Server"
  3. Configure connection:
  4. Server name
  5. Command/endpoint
  6. Environment variables
  7. Credentials

Via API:

POST /api/v1/mcp/servers
{
  "name": "github",
  "command": "npx",
  "args": ["-y", "@modelcontextprotocol/server-github"],
  "env": {
    "GITHUB_TOKEN": "ghp_xxxxx"
  }
}

Security Features

Credential Encryption

  • AES-256-GCM encryption
  • Credentials never logged
  • Encrypted at rest in database
  • Automatic key rotation support

Tenant Isolation

  • MCP servers scoped per tenant
  • No cross-tenant access
  • Separate credential storage
  • Independent health monitoring

Health Monitoring

  • 5-minute health check intervals
  • Automatic failover on errors
  • Status dashboard
  • Alert notifications

DAG Workflow Integration

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Use MCP tools in workflows:

- id: validate_po
  type: mcp_tool
  config:
    server: erp_system
    tool: validate_purchase_order
    params:
      po_number: "{{extracted_po_number}}"
      vendor: "{{extracted_vendor}}"

- id: create_issue
  type: mcp_tool
  config:
    server: github
    tool: create_issue
    params:
      title: "{{bug_title}}"
      body: "{{bug_description}}"
      labels: ["bug", "from-archivus"]

Common Integration Patterns

Document Upload Trigger

name: external_document_processing
trigger: mcp_server_webhook

nodes:
  - id: upload_to_archivus
    type: mcp_tool
    config:
      server: archivus
      tool: archivus_upload_document

  - id: analyze
    type: ai_analyze

  - id: notify_slack
    type: mcp_tool
    config:
      server: slack
      tool: post_message
      params:
        channel: "#documents"
        text: "New document processed: {{document_name}}"

Cross-System Sync

name: crm_document_sync
trigger: document_upload

nodes:
  - id: extract_contact
    type: ai_extract
    config:
      fields: [name, email, company]

  - id: update_crm
    type: mcp_tool
    config:
      server: salesforce
      tool: upsert_contact
      params:
        email: "{{extracted_email}}"
        document_url: "{{archivus_document_url}}"

Research + GitHub

name: research_to_issues
trigger: manual

nodes:
  - id: research
    type: research_task
    config:
      topic: "{{research_topic}}"
      mode: power

  - id: extract_action_items
    type: ai_extract
    config:
      fields: [action_items, owners, priorities]

  - id: create_issues
    type: mcp_tool
    config:
      server: github
      tool: create_issue
      params:
        title: "{{action_item}}"
        assignee: "{{owner}}"
        labels: ["from-research"]

MCP Server Status

Monitor MCP server health:

Dashboard View:

MCP Servers Status

┌──────────────────────────────────────────────────────┐
│ GitHub Integration                                   │
│ Status: ● Healthy                                    │
│ Last Check: 2 minutes ago                            │
│ Requests (24h): 147                                  │
│ Success Rate: 99.3%                                  │
└──────────────────────────────────────────────────────┘

┌──────────────────────────────────────────────────────┐
│ Slack Integration                                    │
│ Status: ● Healthy                                    │
│ Last Check: 1 minute ago                             │
│ Requests (24h): 56                                   │
│ Success Rate: 100%                                   │
└──────────────────────────────────────────────────────┘

┌──────────────────────────────────────────────────────┐
│ ERP System                                           │
│ Status: ⚠️ Degraded                                  │
│ Last Check: Failed 30 seconds ago                    │
│ Requests (24h): 234                                  │
│ Success Rate: 87.2%                                  │
│ Action: [Retry] [Disable] [View Logs]               │
└──────────────────────────────────────────────────────┘

Audit Logging

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Complete audit trail of MCP operations:

Logged Events:

  • Tool invocations
  • Parameters and responses
  • Success/failure status
  • Execution duration
  • User attribution

Example Log:

{
  "timestamp": "2026-02-07T15:30:45Z",
  "user_id": "user-uuid",
  "server": "github",
  "tool": "create_issue",
  "params": {
    "title": "Bug in login form",
    "repo": "company/product"
  },
  "response": {
    "issue_number": 142,
    "url": "https://github.com/company/product/issues/142"
  },
  "duration_ms": 847,
  "status": "success"
}

Cost Tracking

MCP tool usage tracked for analytics:

  • Calls per server/tool
  • Success/failure rates
  • Average response times
  • Credit consumption (if applicable)

Use Cases by Industry

Software Development

  • GitHub issue creation from documents
  • Automated testing trigger
  • Code review automation
  • Deploy pipeline integration

Customer Support

  • Slack notifications for documents
  • CRM contact updates
  • Ticket system integration
  • Knowledge base sync

Finance

  • ERP purchase order validation
  • Banking API integration
  • Payment system triggers
  • Accounting software sync

Healthcare

  • EHR patient matching
  • Lab system integration
  • Insurance verification
  • Scheduling system updates

Getting Started

  1. Navigate to Settings → Integrations → MCP
  2. Add MCP server with credentials
  3. Test connection
  4. Use in Archie conversations or workflows
  5. Monitor status and logs

View MCP API Docs → Browse MCP Servers →