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mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

eval_expression

Compute advanced mathematical operations by evaluating PARI/GP expressions. Supports factorization, primality testing, polynomial root finding, and elliptic curve calculations.

Instructions

Evaluate a PARI/GP expression string.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "expr": "<expr>"
    },
    "name": "eval_expression"
  }
}

Input Schema

NameRequiredDescriptionDefault
exprYesA PARI/GP expression as a string (e.g., "x^2 + 1", "factor(100)", "prime(10)"). For multiple computations, ALWAYS use vector expressions like "vector(15, n, qfbclassno(-4*n))" instead of for-loops with print statements. For-loops may cause timeouts.
timeoutNoMaximum execution time in seconds (default 60). Note: This is a best-effort timeout and may not work reliably for long-running PARI operations written in C.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only states the action without disclosing behavioral traits such as return format, error handling, side effects, or resource usage. The timeout parameter's note about best-effort is in the schema, not the description. The description adds minimal transparency.

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 a single, efficient sentence (7 words) with no wasted words. It is front-loaded with the core action. However, it could benefit from a bit more detail (e.g., result type) without becoming verbose, so it's concise but not perfectly complete.

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

Completeness2/5

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

Given no output schema, no annotations, and moderate complexity, the description does not explain what the tool returns or potential errors. It is incomplete for a generic evaluator that could produce various results. The schema covers parameters well, but the output and behavior are missing.

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

Parameters3/5

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

Schema description coverage is 100%, with detailed descriptions for both parameters including examples and guidance for expr and a note for timeout. The tool description adds no extra meaning beyond the schema. Baseline 3 is appropriate as schema does the heavy lifting.

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 'Evaluate a PARI/GP expression string' clearly states the tool's action (evaluate) and resource (expression string). It distinguishes from siblings, which are specific functions (e.g., factor, sin), by indicating a general evaluator. However, it could be slightly more precise by mentioning that it evaluates arbitrary expressions.

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?

No explicit guidance is provided on when to use this tool vs. alternatives like specific function tools. The description implies usage for evaluating expressions not covered by individual functions, but does not state this or provide exclusions. The context signal of many sibling tools hints at specialization, but the description lacks direct advice.

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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