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Symbolic Algebra MCP Server

by sdiehl
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Python
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    TDQS

    B3.4/5.0

    Scored across 32 tools

    Disambiguation4/5

    Most tools have distinct purposes, such as calculate_curl for vector calculus, differentiate_expression for derivatives, and solve_algebraically for equation solving. However, there is some overlap between intro and intro_many (both introduce variables) and between the various solve_* tools (linear, nonlinear, algebraic), which could cause minor confusion. Descriptions help clarify, but the boundaries are not perfectly sharp.

    Naming Consistency4/5

    The tool names follow a consistent verb_noun pattern throughout, such as calculate_curl, create_coordinate_system, and simplify_expression. Minor deviations include intro and intro_many (abbreviated verbs) and reset_state (verb_noun but less descriptive), but overall the naming is predictable and readable.

    Tool Count3/5

    With 32 tools, the count feels heavy for a symbolic algebra server, bordering on excessive. While the domain is broad (covering calculus, linear algebra, differential equations, units, etc.), the set includes many specialized tools that might be overwhelming. A more streamlined set of 15-25 tools could improve coherence without losing functionality.

    Completeness5/5

    The tool surface is highly complete for symbolic algebra, covering core operations like differentiation, integration, equation solving (algebraic, linear, nonlinear, ODEs, PDEs), matrix operations (determinant, eigenvalues, inverse), vector calculus (gradient, divergence, curl), unit conversion, and expression manipulation (simplify, substitute). There are no obvious gaps; agents can perform complex workflows from variable introduction to solution output.

    Maintenance

    ActivityInactive
    ResponsivenessUnresponsive

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