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mcp-sympy

by daedalus
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Python
Remote

sympy_dirichlet_eta

Compute the Dirichlet eta function for a given complex argument. Returns symbolic result using SymPy's implementation.

Instructions

Dirichlet eta function.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • src/mcp_sympy/tools.py:1432-1435 (handler)
    The tool handler function for 'sympy_dirichlet_eta'. It takes a string expression, sympifies it, and returns the Dirichlet eta function result as a string.
    @mcp.tool()
def sympy_dirichlet_eta(s: str) -> str:
    """Dirichlet eta function."""
    return str(dirichlet_eta(_sympify(s)))
  • src/mcp_sympy/tools.py:114-116 (helper)
    The _sympify helper function converts string expressions to SymPy objects, used by the handler.
    def _sympify(expr: str) -> sympy.Basic:
    """Convert string expression to SymPy object."""
    return sympy.sympify(expr)
  • src/mcp_sympy/tools.py:119-119 (registration)
    The FastMCP instance used as the decorator @mcp.tool() which registers sympy_dirichlet_eta as an MCP tool.
    mcp = fastmcp.FastMCP("mcp-sympy")
  • src/mcp_sympy/tools.py:60-60 (helper)
    Import of dirichlet_eta from sympy, used by the handler function.
    dirichlet_eta,

Tool Definition Quality

D1.3/5.0
Behavior1/5

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

With no annotations, the description should disclose behavioral traits. It does not describe what the tool does (e.g., evaluate a symbolic expression), return value format, handling of edge cases, or domain of the parameter.

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

Conciseness2/5

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

The description is very concise (one sentence) but fails to convey essential information. Conciseness should not come at the cost of utility.

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

Completeness1/5

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

Given one parameter, no annotations, and an output schema present but not referenced, the description is grossly inadequate for an agent to use the tool correctly. It lacks any notion of return values or usage hints.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain the meaning or expected format of the parameter 's' (e.g., that it should be a numeric expression).

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

Purpose2/5

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

The description 'Dirichlet eta function' merely restates the tool name without specifying an action like 'compute' or 'evaluate'. It is a tautology that provides no additional verb or resource clarification.

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

Usage Guidelines1/5

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

No guidance is given on when to use this tool versus sibling functions such as sympy_zeta. There is no mention of context, prerequisites, or alternatives.

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

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