ABAQUS MCP Pro
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Related Servers
- FlicenseNot gradedqualityCmaintenanceEnables MCP clients like Claude Code or Cursor to control Abaqus/CAE in real time, including running Python scripts, reading ODB results, and capturing viewport screenshots.-
- FlicenseNot gradedqualityDmaintenanceEnables to interact with Abaqus FEA software through an MCP bridge, supporting connection checks, script execution, model queries, job submission, and simulation automation.3-
- AlicenseNot gradedqualityCmaintenanceAn MCP server that enables controlling a live Abaqus/CAE session through natural language, allowing model inspection, job submission, ODB analysis, and viewport capture.MIT
- FlicenseNot gradedqualityCmaintenanceEnables an AI assistant to drive Abaqus/CAE through file IPC—sending Python commands, querying model info, submiting jobs, and capturing viewport screenshots—so finite element models can be built and solved without manual GUI interaction.2-
- AlicenseNot gradedqualityBmaintenanceA secure local STDIO MCP server that lets OpenAI Codex automate Abaqus FEM workflows: create model scripts, submit jobs, monitor solver logs, and extract ODB results.MIT
- AlicenseBqualityCmaintenanceEnables AI agents to automate COMSOL Multiphysics simulations, including model management, geometry building, physics configuration, meshing, solving, and results visualization through the MCP protocol.78MIT
TDQS
Scored across 110 tools
The set contains explicit wrappers/duplicates such as run_python/execute_script, inspect_odb/get_odb_info, and capture_viewport/get_viewport_image, plus overlapping tools like check_silent_failures/check_model_integrity and monitor_job_status/diagnose_job. Even with good individual descriptions, an agent will struggle to tell which tool is the intended one.
Tool names are overwhelmingly snake_case and follow a consistent verb_noun pattern such as create_*, list_*, get_*, set_*, and check_*. Minor deviations like the bare 'ping', compatibility wrapper names, and _exp suffixes keep this from being a perfect 5.
110 tools is far beyond the calibrated extreme-mismatch threshold of 50+. The surface includes several near-duplicate and subset tools that should be merged, making the overall tool count excessive for effective agent selection.
The workflow coverage is broad: parts, materials, meshes, steps, loads, BCs, contacts, job submission, diagnosis, ODB extraction, and reporting are all present. However, nearly every create_* entity lacks corresponding update/delete tools, so iterative correction requires the generic run_python escape hatch rather than a complete structured lifecycle.