NovaSolver Studio MCP Server
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- AlicenseBqualityBmaintenanceEnables AI agents to drive OpenFOAM end to end: cloning tutorials or custom cases, editing dictionaries, meshing and running solvers in the background, tracking convergence and job status, and analyzing results. It also renders flow images — slices, patches, streamlines, iso-surfaces and residual or force plots — back to the agent.251MIT
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- AlicenseNot gradedqualityCmaintenanceEnables coding agents to run bounded COMSOL simulations with contract validation, model inspection, provenance tracking, and deterministic verifier feedback.2MIT
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- AlicenseNot gradedqualityCmaintenanceEnables AI agents to drive desktop CAD software through natural language with verified execution, failure recovery, and traceable results across modeling, assemblies, drawings, exports, motion, FEA, and related engineering workflows.MIT
TDQS
Scored across 37 tools
Most tools occupy a clearly distinct slot in a real simulation workflow (case lifecycle, meshing, solving, results, sweeps, surrogates, topology optimisation, print screening). A few boundaries are fuzzy: instant_estimate vs surrogate_predict (both 'instant answer with error bar'), check_convergence vs run_sweep with study="convergence", and describe_case vs validate_case all require reading the descriptions closely. The thorough descriptions largely resolve these, but misselection is still plausible.
The dominant pattern is verb_noun snake_case (create_case, import_geometry, run_simulation, probe_results, build_surrogate), applied consistently across action tools. A handful of resource-first names (job_status, surrogate_status, genesis_result, environment_check) and one verbless name (instant_estimate) break the pattern, though they form a readable sub-convention for status/artifact tools.
37 tools is well past the comfortable range, but the surface genuinely spans many sub-domains: case CRUD, CAD import, meshing, solving, jobs, results inspection, verification, exports, parameter sweeps, surrogates, topology optimisation, and a standards-based estimator. Nothing is obviously trivial, yet several clusters (four surrogate tools, four result-inspection tools, two convergence paths) make the set heavier than it needs to be.
Case lifecycle is essentially complete (create/import/open/clone/update/undo/delete/export/list/describe/validate), and the solve-inspect-verify-export loop is fully covered, including background jobs and stopping them. The main gap is run management: get_results accepts 'the given run' but no tool lists a case's runs or deletes a single run, so agents working with multiple runs per case hit a dead end. There is also no standalone way to discover valid material presets or parameter paths other than describe_case(detail="full").