Official Connector

Flusia CRM — MCP Server

Connect Flusia CRM to Model Context Protocol–compatible AI assistants: Claude.ai, Claude Desktop, Claude Code, ChatGPT Connectors and the Claude mobile app.

MCP endpoint:https://api.flusia.it/mcp
Version:1.0.0

1. What it is

The Flusia MCP server exposes ~212 tools that let an AI assistant read and modify leads, deals, tasks, projects, invoices, newsletter campaigns, WhatsApp chats and other entities of the CRM organization tied to the API token.

The granular permission model configured by the admin is enforced: the AI can never do more via MCP than the user is already authorized to do in the CRM.

2. Features and use cases

Exposed resources (212 tools total):

ResourceTool prefixCapability
Leads / Clientscrm_clients_*CRUD, search, related deals, notes, recordings
Dealscrm_deals_*CRUD, status, services, contacts, commissions, notes
Taskscrm_tasks_*CRUD, checklist, attachments, tags, assignment
Projectscrm_projects_*CRUD, brief, activities, archive, assignments
Activitiescrm_activities_*Timeline of calls, meetings, emails, notes
Servicescrm_services_*Service/product catalog
Pipelinescrm_pipelines_*Pipelines and sales stages
Invoicescrm_invoices_*Read FattureInCloud invoices, allocation, queue
Newslettercrm_newsletter_*Lists, email campaigns, blacklist, quota, domains
WhatsAppcrm_whatsapp_*Chats, messages, notes, per-user ACL
QR Codescrm_qr_codes_*Generate and manage QR tracking
Wikicrm_wiki_*Organization knowledge base
Workflowcrm_workflows_*Automation builder steps + triggers
Settingscrm_settings_*Org settings (users, roles, templates)
Statscrm_stats_*KPI snapshot + revenue analytics

Every tool declares the standard MCP annotations (readOnlyHint for reads, destructiveHint for irreversible operations) as required by the Anthropic MCP Directory Policy.

Typical use cases

  • Conversational sales assistant: search leads, update status, create follow-up tasks, send WhatsApp messages.
  • Automatic reporting from natural prompt ("Summary of deals won this week by pipeline X").
  • Safe bulk operations: the AI proposes, the user confirms (human-in-the-loop on destructive tools).
  • Customer onboarding: lead + deal + task + checklist in a single conversational turn.
  • Diagnostics: the AI queries CRM state to investigate anomalies reported by operators.

3. How to connect

Claude.ai (web)

  1. Go to claude.ai → Settings → Connectors → Add custom connector
  2. Name: "Flusia CRM"
  3. Server URL: https://api.flusia.it/mcp
  4. Confirm. On first use Claude will start the OAuth flow.

Claude Desktop

In ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "flusia-crm": {
      "url": "https://api.flusia.it/mcp"
    }
  }
}

Restart Claude Desktop. On the first tool call the OAuth flow will open in the browser.

Claude Code

claude mcp add flusia-crm https://api.flusia.it/mcp

Static API token (server-to-server)

For server-to-server integrations (scripts, automations) generate a permanent API token:

  1. Sign in to app.flusia.it → Settings → API Tokens
  2. Create a new token with the required permissions (per resource: read/write/delete)
  3. Use the token as Authorization: Bearer flusia_<token>

4. OAuth 2.1

The server exposes the standard discovery metadata:

EndpointRFC / Function
GET /.well-known/oauth-protected-resourceRFC 9728 — protected resource metadata
GET /.well-known/oauth-authorization-serverRFC 8414 — authorization server metadata
POST /registerRFC 7591 — Dynamic Client Registration
GET /authorizeAuthorization endpoint (interactive consent)
POST /tokenToken endpoint (PKCE S256)
POST /revokeToken revocation

Features

  • Grant types: authorization_code + refresh_token
  • PKCE required (S256)
  • Token endpoint auth: none (public client)
  • Scope: mcp:full (capped by user CRM permissions)
  • All valid HTTPS redirect URIs are accepted in production

Pre-configured supported callbacks

  • https://claude.ai/api/mcp/auth_callback
  • https://claude.com/api/mcp/auth_callback
  • http://localhost:6274/oauth/callback (MCP Inspector)
  • http://localhost:6274/oauth/callback/debug

5. Usage examples

Example 1 — Create a lead from natural chat

User prompt

"Create a new lead called Studio Dentistico Bianchi, VAT 12345678901, based in Milan at Via Roma 10, and assign the opportunity to Mario Rossi. Add a follow-up task to call him tomorrow."

Expected tool chain
  1. crm_users_list (search Mario Rossi → obtains user_id)
  2. crm_clients_create_lead with business_name, vat_number, address, assigned_to
  3. crm_tasks_create with client_id of the new lead, due_date = tomorrow
Expected output
The AI confirms with the 2 created IDs and a verbal summary.

Example 2 — Report of deals won last month

User prompt

"Which deals did we close as won last month? Show total revenue and the top 3 by value."

Expected tool chain
  1. crm_stats_revenue with start_date and end_date → returns total_revenue and win_rate
  2. crm_deals_list with status: "accepted", limit: 50
  3. The AI sorts and produces a table + KPIs
Expected output
Revenue closed last month: €127,430
Win rate: 34%
Top 3 deals: ACME Corp €45,000, Studio Verdi €28,500, TechStart €19,800

Example 3 — Conversational cleanup with confirmation

User prompt

"Delete all duplicate leads of ‘Mario Rossi’ with the same VAT number."

Expected tool chain
  1. crm_clients_search with q: "Mario Rossi" → candidates
  2. Client-side filter for duplicate VAT
  3. The MCP client asks explicit confirmation because crm_clients_delete has destructiveHint: true
  4. On confirm → loop of crm_clients_delete
Expected output
The user sees the confirmation prompt for each operation, the AI shows the final summary.

Tools with destructiveHint: true (delete, remove, cancel, archive, unassign) automatically trigger the human-in-the-loop pattern in MCP clients, which ask user confirmation before execution.

6. Privacy and data protection

Data processing follows:

What flows through MCP

  • Only requests/responses to MCP tools explicitly invoked by the AI
  • Logs include only organization_id, tool name, timing and status code — not user payloads
  • Log retention: 30 days
  • Server: OVH Roubaix (France, EU)
  • Application data: Supabase EU (Frankfurt, eu-central-1)

What does NOT flow through

  • The Flusia server does not receive the user-AI conversation, only the arguments of the tools the AI chooses to invoke
  • Anthropic (claude.ai) can see tool responses in the conversation, but has no direct access to the Flusia database

7. Support

Technical supportsupport@flusia.it
Security / vulnerabilitiessecurity@flusia.it
Privacy / GDPRprivacy@flusia.it
Status pagehttps://status.flusia.it
User documentation/en/wiki

SLA: response within 1 business day for standard support, within 4 business hours for confirmed security issues.

Ready to connect your CRM to your AI assistant?

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