agentsumo-mcp
MCP server for SUMO (Simulation of Urban MObility) traffic simulation. Orchestrate network extraction, trip generation, scenario customization, simulation runs, and SQL-based result analysis from any MCP-compatible LLM client.
Features
- Pipeline tools: OSM extraction -> network conversion -> trip generation -> route generation -> simulation
- Scenario customization: edge editing, lane reduction, speed limit changes, vehicle generation, traffic-light timing
- Result analysis: ingest tripinfo / edgedata / summary XML into SQLite for natural-language SQL queries
- Visualization: network plots, edge data heatmaps, policy-target visualizations
- Geocoding: place name -> coordinate -> nearest edge resolution
Requirements
- Python 3.10 or later
- SUMO installed locally (
SUMO_HOMEenvironment variable set)
Installation
pip install agentsumo-mcp
Or run without installing via uvx:
uvx agentsumo-mcp
Configuration
Set SUMO_HOME to point at your local SUMO installation:
export SUMO_HOME=/path/to/sumo
On macOS with the official SUMO installer this is usually /Library/Frameworks/EclipseSUMO.framework/Versions/<version>/EclipseSUMO.
Usage with Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"agentsumo": {
"command": "uvx",
"args": ["agentsumo-mcp"],
"env": {
"SUMO_HOME": "/path/to/sumo"
}
}
}
}
Usage with other MCP clients
Any MCP client that supports stdio transport works:
agentsumo-mcp
Tools
The server exposes ~25 tools across five categories:
| Category | Examples |
|---|---|
| Network | osm_extract, net_convert, network_summary_tool |
| Trips & routes | trip_generate, route_generate, vehicle_generation_tool, flow_generation_tool |
| Customization | edge_edit_tool, reduce_lanes_tool, speed_limit_edit_tool, tls_offset_tool, tls_adaptation_tool |
| Simulation | sumo_runner |
| Analysis | xml_to_sqlite_tool, simulation_report_tool, route_analysis_tool, analyze_road_details_tool |
| Visualization | visualize_net_tool, visualize_edge_tool, visualize_edgedata_tool |
Each tool returns structured JSON suitable for downstream LLM reasoning.
Citation
If you use AgentSUMO in academic work, please cite:
@article{jeong2025agentsumo,
title = {AgentSUMO: An Agentic Framework for Interactive Simulation Scenario Generation in SUMO via Large Language Models},
author = {Jeong, Minwoo and Chang, Jeeyun and Yoon, Yoonjin},
journal = {arXiv preprint arXiv:2511.06804},
year = {2025},
url = {https://arxiv.org/abs/2511.06804}
}
License
MIT. See LICENSE.
Metadata
Release files for agentsumo-mcp 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agentsumo_mcp-0.1.2.tar.gz | 71.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agentsumo_mcp-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 153.8 kB
Release files / agentsumo_mcp-0.1.2.tar.gz
| Download URL | agentsumo_mcp-0.1.2.tar.gz |
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| Size | 71.6 kB |
| Tags | Source |
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| Tags | Python 3 |
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