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    Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.
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    MIT
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    Let AI agents build, measure and verify parametric parts and assemblies in your own running SolidWorks (Windows, COM). 46 tools, every step measured.
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    MIT
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    Enables MCP clients like Claude to automate SOLIDWORKS 2025 and SOLIDWORKS CAM via COM, covering parts, assemblies, drawings, and CAM toolpaths. It generates real geometry, mass properties, and posted G-code files directly on disk.
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    MIT
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    Enables Claude or any MCP client to drive a live SOLIDWORKS session through its COM API, modeling parts, building assemblies with mates, checking interferences and machining feasibility, and exporting STEP or DXF files. It also exposes a local semantic index of the SOLIDWORKS API so the model can look up signatures, enums, and official examples before running arbitrary Python against the session.
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    MIT
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    Enables connecting MCP clients to local SolidWorks for automated 3D part creation, template generation, file export, and basic review via natural language.
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    MIT
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    An MCP server for auditing automation health, finding failures, stale logs, and non-functional endpoints that report success while quietly failing.
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    MIT
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    Enables AI agents to operate the Unreal Editor via MCP: reading, creating, and editing blueprints at the node level, authoring materials and UMG widgets, auditing projects, and verifying runtime behavior in PIE with read-back checks.
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    Apache 2.0
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    Turns Canvas LMS into a scriptable pipeline and exposes it to AI assistants via MCP for querying courses, grades, assignments, and syncing files using natural language.
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    An open-source MCP server that gives parents real-time oversight and guardrails over their children's AI agent interactions, with features like content filtering, spiral detection, and approval flows.
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    5 npm
    MIT
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    Enables AI assistants to evaluate business processes for automation by collecting discovery answers, calculating labor costs, scoring automation potential, and saving completed audits to a local SQLite database.
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