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AgentSUMO MCP server

by mw-jeong·io.github.mw-jeong/agentsumo-mcp·v0.1.2·11 stars
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MCP server for LLM-driven SUMO traffic simulation, scenario design, and result analysis.

B80/100grade B
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Safety scan
B80/100

full report

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11 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

AgentSUMO tools (26, 3 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • analyze_road_details_tool

    Analyze detailed road information (lanes, speed limits, length, etc.).

  • edge_edit_toolwrite action

    Delete specific road segments from the network file.

  • flow_generation_tool

    Generate a SUMO flow from source to destination.

  • get_edge_ids_from_road_name_tool

    Convert road name to SUMO edge IDs using edge.getName().

  • get_road_names_tool

    Convert SUMO edge IDs to actual road names using edge.getName().

  • net_convert

    [Step 2/5] Convert OSM data to SUMO network format (.net.xml).

  • network_summary_tool

    Get a comprehensive summary of a SUMO network.

  • osm_extract

    [Step 1/5] Extract OpenStreetMap (OSM) road network data for a given area.

  • reduce_lanes_tool

    Reduce lanes on road segments with two modes.

  • route_analysis_tool

    Analyze the optimal route between two locations in the network.

  • route_generate

    [Step 4/5] Generate routes from trips using SUMO's duarouter.

  • simulation_report_tool

    Generate a comprehensive HTML simulation analysis report from SQLite database.

  • speed_limit_edit_tool

    Modify speed limits on specific road segments (supports partial application).

  • sumo_runner

    [Step 5/5] Run SUMO traffic simulation using TraCI.

  • tls_adaptation_toolwrite action

    Run SUMO tlsCycleAdaptation.py to optimize traffic light cycles and generate an additional XML file.

  • tls_offset_toolwrite action

    Run SUMO tlsCoordinator.py to optimize traffic light offsets and generate an additional XML file.

  • trip_generate

    [Step 3/5] Generate trip demand (trips.xml) for SUMO simulation.

  • validate_od_coordinates_tool

    Validate a list of coordinates against the SUMO network.

  • vehicle_generation_tool

    Add vehicles from source to destination with optimal path calculation.

  • vehicle_type_edit_tool

    Reassign vehicle types in the route file according to the electric_ratio.

  • visualize_edge_tool

    Visualize a SUMO network file with selected edges highlighted and save as PNG image.

  • visualize_edgedata_tool

    🎨 Visualize SUMO edgedata with flexible scaling modes for comparison.

  • visualize_net_tool

    Visualize a SUMO network file and save as PNG image.

  • visualize_policy_target_tool

    Visualize policy target area using SUMO's built-in visualization.

  • web_search_tool

    Search the web using DuckDuckGo. Use this to look up real-world information that helps with simulation scenario design.

  • xml_to_sqlite_tool

Public scan report

scanner v0.1.9 · 2026-09-27 · same rubric, same numbers if you re-run it

no findings
  • Code scan26 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitylocal package, no credentials required12/15
  • Maintenancelast push 102 days ago8/15
  • Maintainer identityregistry namespace matches repository owner7/10
Overall 80/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How AgentSUMO compares

Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
80/100
higher than 60% of 4,460 AI and agents servers
Tools
26
the typical AI and agents server has 6
Tools that change things
12%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
11
more than 85% of 2,711 AI and agents servers

What its tools let an agent do: 23 read · 3 change

Install AgentSUMO in Claude Code, Cursor or VS Code

claude mcp add agentsumo-mcp -- uvx agentsumo-mcp
Add to Cursor

What the publisher says

From the AgentSUMO repository's README, as published. We do not edit it. Read it on GitHub

AgentSUMO

An Agentic Framework for Interactive Simulation Scenario Generation in SUMO via Large Language Models

Documentation · Installation · Tools · Schema · Tutorials

Overview

AgentSUMO lets non-expert stakeholders design, execute, and analyze SUMO traffic simulations through natural-language interaction. The Planner Agent translates abstract policy questions into executable simulation plans, drives them via the Model Context Protocol (MCP), and surfaces results through a web dashboard.

  • Conversational scenario design — describe a policy question, get a runnable simulation
  • Policy experiments — road closures, lane reductions, signal optimization, demand changes
  • Cross-scenario analysis — SQL-based comparison across runs, with auto-generated HTML reports
  • Web dashboard — geospatial visualization, time-series charts, and trip replay

Demo

Web interface: conversational planning panel, scenario list, and live simulation status.

Geospatial visualization: per-edge metrics, congestion overlays, and trip replay on the 2.5D basemap.

Architecture

User (natural language)
    |
    v
Planner Agent (Claude LLM, Interactive Planning Protocol)
    |
    +--> AgentSUMO MCP Client --> AgentSUMO MCP Server (PyPI: agentsumo-mcp) --> SUMO
    |
    +--> SQLite MCP Client    --> SQLite MCP Server (Anthropic, open source)  --> simulations.db
    |
    +--> Filesystem MCP Client --> Filesystem MCP Server (Anthropic, open source) --> additional XML files

The reasoning layer (Planner Agent) lives in this repository. The execution layer (agentsumo-mcp) is published to PyPI and installed automatically as a dependency.

Tool Layer

The AgentSUMO MCP Server exposes 26 tools grouped into five capability categories that follow the simulation workflow. Full reference at agentsumo.readthedocs.io/.../tools.

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

AgentSUMO: common questions

Is AgentSUMO MCP server safe?
Mostly: it is graded B (80/100). Read the AgentSUMO safety report
How do I install AgentSUMO?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does AgentSUMO need an API key?
No secret keys are declared. It reads 2 settings from the environment.
Is AgentSUMO maintained?
The last commit was 140 days ago (2026-06-17). The latest release is v0.1.2.
What can I use instead of AgentSUMO?
Servers from other publishers that do the same job: Depwire MCP server, Figma Context MCP server and MCP Server for WinDbg Crash Analysis.
How does AgentSUMO compare with other AI and agents MCP servers?
safety score 80/100 (higher than 60% of 4,460 AI and agents servers); tools 26 (the typical AI and agents server has 6); tools that change things 12% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.

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