Topolograph MCP

A MCP server that enables LLMs to interact with OSPF and IS-IS protocols and analyze network topologies, query network events, and perform path calculations for OSPF and IS-IS protocols.

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Topolograph MCP Server

A Model Context Protocol (MCP) server that provides access to Topolograph API for OSPF/IS-IS network analysis.

Overview

This MCP server enables AI agents to interact with Topolograph API to analyze network topologies, monitor events, and perform path calculations for OSPF and IS-IS protocols. MCP (Model Context Protocol) is essential for connecting Large Language Models (LLMs) to network infrastructure, allowing AI agents to query and analyze network data in real-time.

This MCP server is included in the topolograph-docker repository and is available via the provided docker-compose.yml file.

Features

  • Graph Management: Retrieve and upload network graphs
  • Network Analysis: Query network information by IP, node ID, or network mask
  • Event Monitoring: Track network and adjacency events with time filtering
  • Path Calculation: Calculate shortest paths between nodes with backup path support
  • Status Monitoring: Check graph connectivity and health status
  • Node/Edge Queries: Retrieve detailed node and edge information from diagrams

Installation

pip install -r requirements.txt

Configuration

Set the required environment variable:

export TOPOLOGRAPH_API_BASE="https://your-topolograph-api-url"

Optional authentication:

export TOPOLOGRAPH_API_TOKEN="your-api-token"

Usage

Start the MCP server:

python mcp-server.py

The server runs on http://0.0.0.0:8000/mcp by default.

Docker Compose Integration

This MCP server is included in the topolograph-docker repository. To use it as part of the complete Topolograph stack:

git clone https://github.com/Vadims06/topolograph-docker.git
cd topolograph-docker
docker-compose pull
docker-compose up -d

The MCP server will be available at http://localhost:8000/mcp and automatically connects to the Flask API.

Available Tools

  • get_all_graphs: List available graphs with filtering options
  • get_graph_by_time: Fetch specific graph by time
  • get_network_by_graph_time: Query network information
  • get_graph_status: Check graph health and connectivity
  • get_network_events: Retrieve network up/down events
  • get_adjacency_events: Get node/host and link events
  • get_events_timeline: Node/host events grouped into time waves for incident narration
  • get_nodes: Query diagram nodes (filter by role flags: ABR/ASBR, IS-IS overload/attached)
  • get_edges: Query diagram edges (include=["lsp_left_bw", "lsps", "is_te_link", "edge_key"] for MPLS TE fields)
  • get_shortest_path: Calculate the shortest path between two nodes (with_lsps=true to account for autoroute-enabled MPLS-TE tunnels)
  • get_edge_failure_reaction: Predict whole-network impact if one or more links go down
  • upload_graph: Upload new graphs to the API
  • get_lsps / add_lsp / update_lsp / delete_lsp: CRUD for MPLS TE LSP tunnels (filters: status, via_node, via_edge, via_edge_key)
  • get_cspf_path: Constrained-shortest-path (CSPF) feasibility check between two nodes, without creating a tunnel

Wave patterns (get_events_timeline)

get_events_timeline groups node/host up/down events into chronological waves, each labelled with a pattern (outage / flap / up). For the full field reference and the pattern ā†” graph-status mapping, see the docs:

āž”ļø Events Timeline (Waves)

License

See LICENSE file for details.