AI-powered cross-silo orchestration for telecommunications BSS, OSS, ITSM & Infrastructure. Connect any LLM to your live network, business, incident management and sovereign data centre systems through the Model Context Protocol.
BSS + OSS + ITSM + Infrastructure in real-time. Single conversation across network, business, incident management and sovereign data centre systems.
Live system data via deterministic API responses. Not generated, not stale embeddings.
Every action logged for compliance. ISO 27001 aligned governance and RBAC.
Standards-based TM Forum APIs (TMF620-TMF640). Works with existing systems.
Get up and running in 5 minutes. Connect Claude Desktop to the Telepath AI MCP servers for live BSS, ENM, ITSM (ServiceNow or Jira/Confluence) and Bare Metal infrastructure access.
Download from claude.ai/download and install for your platform (macOS, Windows, or Linux).
In Claude Desktop, create a new Project and give it a description to help Claude understand the tools it will be working with. For example:
"I am attaching MCP servers to connect Claude to telecommunications platforms. The servers implement TM Forum APIs to Business Support Systems, Ericsson ENM APIs for Operations Support Systems, ITSM APIs for trouble ticket management (ServiceNow or Jira/Confluence), and a Bare Metal/GPU provisioning system for sovereign data centre infrastructure."This gives Claude the context it needs to use the BSS, OSS and ITSM tools effectively.
In Claude Desktop, go to Settings → Connectors, then press the "Add Custom Connector" button. Enter the URL for each MCP server:
https://akuig.bss.ngrok.dev/mcp (BSS — catalog, orders, customers)
https://akuig.ngrok.io/mcp (ENM — network, alarms, topology)
https://akuigservicenow.ngrok.dev/mcp (ITSM - trouble tickets via live ServiceNow)
https://akuigjiramcp.ngrok.dev/mcp (ITSM - trouble tickets + KB via live Jira/Confluence)
https://akuig.baremetal.ngrok.dev/mcp (Infrastructure - bare metal & GPU provisioning)
Quit and reopen Claude Desktop. You should see the MCP tools icon (🔨) appear in the chat input area, confirming the servers are connected.
Try your first prompt:
"What's the current network health status?"Walk through these scenarios to see cross-silo BSS + OSS + ITSM + Infrastructure orchestration in action. Each prompt can be typed directly into Claude Desktop.
A fiber cut occurs on the Springfield OLT. The AI agent detects the alarm, identifies affected customers, cross-references their SLA tiers, auto-creates a trouble ticket in your ITSM platform (ServiceNow or Jira), and prioritises the response - all in a single conversation spanning ENM (network), BSS (customer) and ITSM systems.
"Check if there are any critical alarms in the network""What customers are affected by that alarm?""Create a trouble ticket for this outage with all the details""Tell me more about Alice Johnson's account"| Step | System | Data Retrieved |
|---|---|---|
| Alarm detection | ENM | Critical fiber cut on SPFLD-OLT-01 |
| Customer impact | ENM | 3 customers affected via ONTs |
| SLA prioritisation | ENM | Alice Johnson = Platinum (contact first!) |
| Trouble ticket created | ITSM (SN/Jira) | Ticket auto-created with severity, affected customers, network details |
| Account verification | BSS | Good standing, no payment issues |
A new customer wants fiber service. The AI qualifies the address, shows available products with pricing, creates the order, activates the service in the network, and confirms the customer equipment is online — end-to-end orchestration via natural language.
"Can we provide fiber service at 456 Oak Avenue, Springfield?""What internet products do we have available?""Create an order for the 1Gbps fiber package""Activate the service""Confirm the equipment is online"| Step | System | Result |
|---|---|---|
| Service qualification | BSS (TMF637) | Fiber available at address |
| Product catalog | BSS (TMF620) | Lists products with pricing |
| Order creation | BSS (TMF622) | Order ID created, status: created |
| Service activation | BSS (TMF640) | Service activated |
| ONT verification | ENM | ONT online, synchronized |
A sales rep needs to quickly qualify an enterprise opportunity. Instead of waiting days for a response, the AI agent checks network topology, verifies capacity, qualifies the service, and retrieves eligible products — all in one conversation.
"Can we offer 1Gbps fibre at Linköping Science Park? What's the lead time?"The agent validates the address, checks nearest network elements, verifies capacity on local aggregation nodes, performs a formal service qualification (TMF637), and retrieves eligible products from the catalog (TMF620).
An engineer is planning maintenance on a cell tower tonight and needs to understand the blast radius before taking it down.
"If I take down eNodeB ERBS01 for maintenance tonight, what's the impact?"The agent identifies the eNodeB, checks connected cells, handover configurations, assesses neighbour capacity, lists dependent services and customers, and checks pending orders — then recommends an optimal maintenance window.
Manage the full incident lifecycle through natural language. The AI agent creates, enriches, updates and resolves trouble tickets in a live ServiceNow or Jira Cloud instance, automatically correlating network faults and customer data from the BSS and ENM systems. The Jira integration also includes Confluence knowledge base search.
"Show me all open trouble tickets""Create a high-priority ticket for the fiber outage affecting Springfield customers""Add a work note to that ticket with the root cause analysis from ENM""Search the knowledge base for fiber cut resolution procedures""What Confluence articles do we have about fiber troubleshooting?""Resolve the ticket — fiber splice completed, service restored"| Step | System | Result |
|---|---|---|
| List open tickets | ITSM (SN/Jira) | Active incidents with severity, priority, assignment |
| Create ticket | ITSM + ENM + BSS | Ticket created with network details and affected customers |
| Add work note | ITSM (SN/Jira) | Internal note with root cause from ENM analysis |
| KB search | SN KB / Confluence | Resolution articles for fiber cut procedures |
| Resolve ticket | ITSM (SN/Jira) | Ticket resolved with resolution details and category |
A customer needs an H100 GPU cluster for AI training in a specific sovereign data centre. The AI agent checks GPU availability across data centres, provisions the server, allocates GPUs, configures networking and storage - and links everything back to the customer's BSS account for billing.
"What GPU servers are available in our Singapore data centres?""Check H100 availability across all sovereign data centres""Provision an 8x H100 GPU cluster for Jane Doe (customer 8452934) in Singapore DC 1""Show me all infrastructure allocated to customer 8452934""What's the total capacity summary across all our data centres?"| Step | System | Result |
|---|---|---|
| GPU availability | Bare Metal | H100/H200/A100 inventory across 6 sovereign DCs |
| Server provisioning | Bare Metal | Server allocated, OS installed, GPUs assigned |
| Network config | Bare Metal | VLAN, IP, firewall profile configured |
| Customer linkage | Bare Metal + BSS | Allocation tied to BSS customer ID for billing |
| Audit trail | Bare Metal | Full provisioning history logged for compliance |
A natural progression from safe read-only intelligence to autonomous operations, allowing operators to build confidence incrementally.
Cross-silo visibility · Low Risk
Situational awareness and faster decisions
Human-in-loop automation · Medium Risk
Staff productivity, reduced escalations
AI-initiated actions with guardrails · Higher Risk
Operational efficiency, new capabilities
Strategic decision support · Low Risk
Data-driven planning, executive insights
The demo environment simulates a two-city network covering Springfield and Shelbyville with 26 network elements and 7 customers across fiber and cable services, plus sovereign data centre infrastructure across 6 locations with bare metal servers and GPU clusters (A100, H100, H200).
| Customer | ID | Address | Service | SLA | Status |
|---|---|---|---|---|---|
| Jane Doe | 8452934 | 456 Main St | 2Gbps Fiber | Gold | Active |
| John Smith | 8452935 | 123 Main St | 1Gbps Fiber | Silver | Active |
| Alice Johnson | 8452936 | 789 Oak Ave | 2Gbps Fiber | Platinum | Active |
| Stig Larsson | 8452940 | 456 Oak Ave | 2Gbps Fiber | Platinum | NEW |
| Carol Brown | 8452938 | 555 Maple Dr | 1Gbps Fiber | Silver | Active |
| Bob Williams | 8452937 | 321 Elm St | 400Mbps Cable | Bronze | Suspended |
| David Lee | 8452939 | 777 Cherry Ln | 200Mbps Cable | Bronze | Active |
| Element | ID | Type | Location |
|---|---|---|---|
| Core Router | SPFLD-CR-01 | Core Router | Central Office |
| Downtown OLT | SPFLD-OLT-01 | OLT | Main St Hub |
| North OLT | SPFLD-OLT-02 | OLT | North Springfield |
| Springfield CMTS | SPFLD-CMTS-01 | CMTS | Elm Street |
| Downtown Tower | SPFLD-ENB-01 | 4G/5G | Downtown |
| Shelbyville CMTS | SHBY-CMTS-01 | CMTS | Shelbyville |
| Microwave Link | SPFLD-MW-01 | Backhaul | 18GHz, 12.5km |
Explore the full network visually. Hover over elements for details, click customers to inspect. Use the controls to simulate alarms and filter link types.
The Telepath AI MCP servers expose these tools to any connected LLM. All operations follow TM Forum Open API standards where applicable.
| API | Standard | Function |
|---|---|---|
| Service Qualification | TMF637 | Check service availability at address |
| Product Catalog | TMF620 | List available products and pricing |
| Product Ordering | TMF622 | Create and manage orders |
| Customer Management | TMF629 | Retrieve customer account details |
| Service Activation | TMF640 | Activate services in network |
| Tool | Function |
|---|---|
enm_get_alarms | Retrieve active network alarms |
enm_get_alarm_summary | Quick health check — alarm counts by severity |
enm_get_customers_by_element | Find customers served by a network element |
enm_get_network_element | Get details of specific equipment (ONT, OLT) |
enm_get_impact_analysis | Downstream impact analysis |
enm_inject_fault | Create test alarm (demo only) |
enm_clear_alarm | Resolve alarm (demo only) |
Connected to live ServiceNow and Jira Cloud instances - not simulations. Two MCP servers wrap their respective APIs and expose them as TMF621-compliant tools for trouble ticket lifecycle management. The Jira server also integrates Confluence for knowledge base search.
| Tool | Standard | Function |
|---|---|---|
create_trouble_ticket | TMF621 | Create incident with severity, priority, customer and service linkage |
get_trouble_ticket | TMF621 | Retrieve ticket details by INC number or sys_id |
list_trouble_tickets | TMF621 | Query and filter tickets by status, severity, priority, text search |
update_trouble_ticket | TMF621 | Update status, assignment, description, add work notes |
add_ticket_note | TMF621 | Add comments (customer-visible) or work notes (internal) |
get_ticket_counts | TMF621 | Aggregate counts by state, priority, severity, assignment group |
search_knowledge_base | - | Search ServiceNow KB or Confluence for resolution guidance |
get_knowledge_article | - | Retrieve full KB article (Jira/Confluence) |
list_knowledge_categories | - | Browse KB categories (Jira/Confluence) |
get_project_info | - | Discover Jira project issue types and priorities |
relatedParty[].id and to ENM network elements via relatedObject[].id - enabling full cross-silo traceability from network fault to customer impact to incident resolution. Both ServiceNow and Jira servers share the same TMF621 tool interface.Sovereign data centre infrastructure management. Provision bare metal servers and GPU clusters across multiple data centres with full lifecycle management and audit trail.
| Tool | Function |
|---|---|
list_available_servers | List available servers with filtering (DC, class, GPU, RAM, CPU) |
check_gpu_availability | GPU inventory across DCs by model (A100, H100, H200) |
get_server_specifications | Server class/SKU details and capabilities |
list_data_centres | Sovereign DC locations with capacity and power info |
provision_bare_metal | Allocate a server to a customer with OS and SLA tier |
provision_gpu_cluster | Allocate GPU server + GPUs, validates availability |
deprovision_server | Release server to pool (requires data wipe confirmation) |
get_server_status | Full server details including GPUs, allocation, network |
reboot_server | Graceful or hard reboot via BMC/IPMI |
get_customer_infrastructure | All infrastructure allocated to a customer |
assign_network | Configure VLAN, IP, firewall on provisioned server |
configure_storage | Attach NFS/iSCSI/FC storage volumes |
get_provisioning_history | Audit trail of all provisioning actions |
get_capacity_summary | Capacity overview across all sovereign DCs |
customer_id - enabling cross-silo correlation between infrastructure provisioning, customer billing, network services and incident management.BSS Server: https://akuig.bss.ngrok.dev/mcp
ENM Server: https://akuig.ngrok.io/mcp
ITSM Server (ServiceNow): https://akuigservicenow.ngrok.dev/mcp LIVE
ITSM Server (Jira/Confluence): https://akuigjiramcp.ngrok.dev/mcp LIVE
Bare Metal Server: https://akuig.baremetal.ngrok.dev/mcp
All servers use Server-Sent Events (SSE) transport and are compatible with any MCP client. Both ITSM servers connect to live instances - ServiceNow and Jira Cloud/Confluence.
MCP is an open standard. While Claude Desktop provides the easiest setup, you can connect the Telepath AI servers to other LLM platforms too.
OpenAI added MCP support via their Agents SDK. Use the SSE transport to connect:
from agents import Agent
from agents.mcp import MCPServerSse
bss_server = MCPServerSse(
url="https://akuig.bss.ngrok.dev/mcp"
)
enm_server = MCPServerSse(
url="https://akuig.ngrok.io/mcp"
)
itsm_servicenow = MCPServerSse(
url="https://akuigservicenow.ngrok.dev/mcp"
)
itsm_jira = MCPServerSse(
url="https://akuigjiramcp.ngrok.dev/mcp"
)
infra_server = MCPServerSse(
url="https://akuig.baremetal.ngrok.dev/mcp"
)
agent = Agent(
name="Telepath NOC Agent",
instructions="You are a telecom operations assistant...",
mcp_servers=[bss_server, enm_server, itsm_servicenow, itsm_jira, infra_server]
)Mistral supports MCP connectors in Le Chat and via their agents API:
from mistralai import Mistral
client = Mistral(api_key="your-key")
response = client.agents.complete(
agent_id="your-agent-id",
messages=[{"role": "user", "content": "Check network alarms"}],
tools=[
{"type": "mcp", "server_url": "https://akuig.bss.ngrok.dev/mcp"},
{"type": "mcp", "server_url": "https://akuig.ngrok.io/mcp"},
{"type": "mcp", "server_url": "https://akuigservicenow.ngrok.dev/mcp"},
{"type": "mcp", "server_url": "https://akuigjiramcp.ngrok.dev/mcp"},
{"type": "mcp", "server_url": "https://akuig.baremetal.ngrok.dev/mcp"}
]
)Google announced MCP support for Gemini through Vertex AI and the Gemini API. Configure the SSE server URLs as tool providers in your Vertex AI agent setup.
Any MCP-compatible client can connect using SSE transport. Point your client at the server URLs and the available tools will be automatically discovered via the MCP protocol handshake.