Symbolic Algebra MCP Server

introduce_function

Creates and stores a SymPy function variable from a given name, enabling construction of differential equations and use of symbolic functions like f(x) in expressions.

Instructions

Introduces a SymPy function variable and stores it.

Takes a function name and creates a SymPy Function object for use in defining differential equations.

Example:
    {func_name: "f"} will create the function f(x), f(t), etc. that can be used in expressions

Returns:
    The name of the created function.

Input Schema

Name	Required	Description	Default
`func_name`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 29, 2026

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and discloses key behavior: it creates and stores a SymPy Function object, which is a state-changing operation. It also explains the return value, though it omits edge cases like overwriting an existing function name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded and appropriately sized, with the core purpose stated first, followed by a helpful example. The explicit Returns section is somewhat redundant because an output schema exists, but it does not detract significantly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (one parameter) and the presence of an output schema, the description is nearly complete: it covers purpose, usage context, an example, and return behavior. It could be improved by mentioning sibling alternatives, but nothing essential for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The example {func_name: "f"} clarifies that the parameter is a bare function name and that the resulting function can take arbitrary arguments like x or t, adding meaningful semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb and resource: 'Introduces a SymPy function variable' and 'creates a SymPy Function object'. It is clear what the tool does, but it does not explicitly distinguish itself from sibling tools like introduce_expression or intro.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives implied usage context ('for use in defining differential equations'), but it does not state when to use this tool instead of alternatives such as introduce_expression or dsolve_ode. No explicit exclusions or alternatives are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.