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Stage 10 · Agentic AI & Model Context Protocol (MCP)Project #02 of 4

PHASE IV: Autonomous Agents & Protocol Standards

🔌 Stage 10: Agentic AI & MCPProject #02Telecom3 min read2026-08-15

Telecom Network Incident Diagnostic & Remediation MCP Agent

KM

Kiran Machha

Forward Deployed AI Solutions Architect · Singapore

Telecom Network Incident Diagnostic & Remediation MCP Agent

Engineering Field Notes & System Architecture • Domain Focus: Telecom


🏢 1. The Real-World Industry Challenge

When network router interfaces experience packet drops during off-hours, on-call network engineers must log into terminal sessions at 2 AM to run diagnostic CLI commands and reroute traffic.


🎯 2. Core Purpose & Architectural Solution

To build an autonomous network remediation agent connected to cell tower routers via an MCP server that executes pre-authorized diagnostic and traffic rerouting commands safely.

📈 Tangible ROI & Business Impact

Restores degraded network traffic in seconds before human engineers can even wake up, eliminating off-hours connectivity downtime for mobile subscribers.

  • Operational Efficiency: Eliminates error-prone manual intervention through end-to-end automation.
  • Latency & Reliability: Guarantees predictable, sub-second execution with defensive validation.
  • Compliance & Auditability: Enforces strict audit trails, zero-drift precision, and explainable decisions.


🏛️ 3. Production System Architecture & Data Flow

flowchart TD
    %% Node Definitions with High-Contrast Theme
    classDef client fill:#1e40af,stroke:#60a5fa,stroke-width:2px,color:#ffffff,rx:8,ry:8;
    classDef parser fill:#0f766e,stroke:#2dd4bf,stroke-width:2px,color:#ffffff,rx:8,ry:8;
    classDef engine fill:#581c87,stroke:#c084fc,stroke-width:2px,color:#ffffff,rx:8,ry:8;
    classDef store fill:#14532d,stroke:#4ade80,stroke-width:2px,color:#ffffff,rx:8,ry:8;
    classDef alert fill:#7f1d1d,stroke:#f87171,stroke-width:2px,color:#ffffff,rx:8,ry:8;
    classDef cloud fill:#78350f,stroke:#fbbf24,stroke-width:2px,color:#ffffff,rx:8,ry:8;

    subgraph INBOUND[" Ingestion and Validation Gateway "]
        IN1["Client Stream: Telecom"]:::client
        IN2["Pydantic Contract Validator"]:::parser
    end

    subgraph CORE_ENGINE[" Processing and Inference Engine "]
        CE1["Dynamic Feature Normalizer"]:::engine
        CE2["Core System: Telecom Network Incident Diagnostic & Remediation MCP Agent"]:::engine
        CE3["Output Guardrails and Rules"]:::cloud
    end

    subgraph PERSISTENCE[" Production Storage and Outbox "]
        DB1["Primary Database and Vector Lake"]:::store
        DB2["Audit Exception Queue"]:::alert
    end

    subgraph TELEMETRY[" Production Observability "]
        M1["Prometheus and Grafana Metrics"]:::store
    end

    IN1 -->|1. Inbound Ingress| IN2
    IN2 -->|2. Sanitized Data| CE1
    CE1 -->|3. Feature Vector| CE2
    CE2 -->|4. Predictions| CE3
    CE3 -->|5. Verified Record| DB1
    CE3 -->|6. Anomaly Detected| DB2
    CE2 -.->|7. Latency and Drift| M1
    CE3 -.->|8. Audit Health| M1

⚙️ 4. Engineering Specification & Stack Matrix

Architectural Layer Production Component & Selection Free Tier / Open-Source Tooling
Core Model Engine Model Context Protocol (MCP) Server + FastMCP SDK + Claude Desktop / ReAct Open-source weights / Framework native
Training & Fine-Tuning Typed Tool Schemas, Resource Subscriptions & Zero-Trust Audit Logs Kaggle GPU (Dual T4) / Colab / Unsloth
Benchmark Dataset Enterprise Telecom Internal Database Schemas, CLI Endpoints & REST APIs Free public datasets (Kaggle, HF, Data.gov)
User Interface (UI) Streamlit Interactive Web Cockpit & REST API Streamlit UI (app.py) with reactive components
Live UI Hosting FastMCP Local SSE Server / Streamlit Cloud + NVIDIA NIM Free Credits 100% Free Live Web Hosting
Validation & Test Suite Pytest Unit/Integration Suite + Synthetic Evals Automated pre-deployment verification

🔗 Source Code & Repository

Explore the complete reproducible implementation, tests, and configuration manifests in the master GitHub repository: 👉 View Code on GitHub: 10_agentic_ai_mcp/02_telecom_network_incident_remediation_mcp

Authored by Kiran Macha — Forward Deployed AI Solutions Architect.