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mcp-solver

mcp-solver

by szeider
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

python_reset

Create or reset a Python kernel for MiniZinc constraint solving, optionally installing solver packages; it becomes the target for bare python_exec calls.

Instructions

Create a new kernel (no kernel_id) or reset one (with kernel_id).

Prefer select_backend, which installs the right solver packages for you. The kernel created or reset here becomes the target of bare python_exec calls.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "python_reset"
  }
}

Input Schema

NameRequiredDescriptionDefault
packagesNo
kernel_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It usefully discloses that the created or reset kernel becomes the target of bare python_exec calls, but it does not mention that resetting may discard existing kernel state, nor does it explain the packages parameter's effect.

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

Conciseness5/5

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

The description is three short sentences with no wasted text. The main behavior is front-loaded, followed by the alternative tool guidance and the downstream effect on python_exec.

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?

For a two-parameter, state-changing tool with no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It covers purpose and one parameter but leaves packages undocumented and does not describe reset side effects or state loss.

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

Parameters2/5

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 for both parameters. It explains kernel_id's effect well by describing create-without vs reset-with, but it completely omits the packages parameter, leaving half the parameters undocumented.

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

Purpose5/5

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

The description gives a specific verb and resource, and it clearly distinguishes the two modes: no kernel_id creates a new kernel, while a provided kernel_id resets one. It also names the related sibling tool select_backend, so the tool's role is immediately identifiable.

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

Usage Guidelines4/5

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

It explicitly says to prefer select_backend when solver packages are needed, which is useful routing guidance. The create-vs-reset condition is also clear, though the description does not explicitly state when not to use python_reset or what prerequisites exist.

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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