Topolograph MCP

★ 5

from Vadims06

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

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
get_shortest_path: Calculate shortest paths between nodes
upload_graph: Upload new graphs to the API

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 ↔ graph-status mapping, see the docs:

➡️ Events Timeline (Waves)

Copy & paste — that's it

pip install -r requirements.txt

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.