Topolograph MCP

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

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 thetopolograph-dockerrepository and is available via the provideddocker-compose.ymlfile.

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

export TOPOLOGRAPH_API_TOKEN="your-api-token"

This MCP server is included in thetopolograph-dockerrepository. 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

- 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=trueto 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

get_events_timelinegroups node/host up/down events into chronologicalwaves, each labelled with apattern(outage/flap/up). For the full field reference and thepattern↔ graph-status mapping, see the docs:

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