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michaelmackenzie

analysis-mcp-server

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    • A
      license
      B
      quality
      B
      maintenance
      Enables any MCP client to plan and run verifiable analysis of engine hot-fire and bench test data through tools that open runs, segment phases, check sensor health, redlines, valve response and oscillations, compare simulations, verify every reported number against an evidence ledger, and write HTML reports. All findings stay traceable and reproducible from deterministic tool calls rather than raw samples.
      5
      50 PyPI
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    • A
      license
      A
      quality
      C
      maintenance
      Enables MCP clients to control the local Open Science research application, including creating projects, starting or continuing research sessions, inspecting progress and plans, canceling runs, and reading generated artifacts.
      12
      Apache 2.0
    • F
      license
      Not graded
      quality
      A
      maintenance
      Enables coding agents to coordinate local profilers, benchmark tools, trace processors, and direct targets, turning explicit artifacts or commands into bounded runtime evidence with provenance, coverage, and limitations. Exposes named analysis and capture tools through MCP without workspace setup, with optional durable preservation.
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    • A
      license
      A
      quality
      C
      maintenance
      Enables MCP-aware agents to estimate, submit, monitor, cancel, and retrieve artifacts from Jungle Grid workloads, supporting asynchronous AI execution, batch processing, training, fine-tuning, and access to logs and managed outputs.
      11
      14 npm
      MIT
    • F
      license
      Not graded
      quality
      A
      maintenance
      Exposes analysis and capture tools that turn explicit artifact paths or an argv-based command into typed, bounded runtime evidence such as profiles, traces, and benchmarks. Results return inline with provenance, coverage, limitations, and optional durable evidence bundles that agents can inspect and replay.
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