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taliasoftworks

planvortex-mcp

Official
by taliasoftworks
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TypeScript
Hybrid

Get the AI planner templates

get_planner_templates
Read-only

Retrieve plan templates and their credit costs before generating a plan. Compare standard, from_images, from_text, from_catalog, and campaign options to choose the right format and budget.

Instructions

What an AI plan can be generated FROM, with the credits each template costs. Five of them: standard (a theme prompt, images generated by the model), from_images (the user's own photos, each with a description), from_text (an article by URL or pasted), from_catalog (products read live from a connected shop) and campaign (a countdown to a date, with a narrative arc). Read this before proposing a plan: the costs and the fields are prices, and they are not to be guessed or remembered. The ones that do not generate images cost a fraction — a week of 7 posts with a picture each is 519 credits on standard and 48 on from_images. Creating plans is off unless the server was started with PLANVORTEX_MCP_ALLOW_AI=1, because generating one spends AI credits. If create_ai_plan is not in your tool list, that is why: tell the user to add it to the env block of their MCP configuration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.7.0
    • addedInput schema / additionalProperties
      Added value: +false
  2. Addedv0.3.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations only mark the tool as read-only. The description adds detailed behavioral context: the exact template list, the warning that credit costs are prices not to be guessed, a concrete cost comparison, and the gating of AI plan creation behind a server flag. This goes well beyond the annotations and contains no contradiction.

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 every sentence contributes meaningful context. However, it is written as one dense paragraph, and the illustrative 519-vs-48 credits example, while helpful, makes it slightly longer than strictly necessary for a zero-parameter read-only tool.

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

Completeness5/5

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

For a tool with no parameters and no output schema, this description is complete: it identifies what the returned data contains, warns about cost implications, and explains the relationship to related actions like creating a plan. An agent has everything it needs to invoke and interpret this tool correctly.

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?

The tool has zero parameters and the schema already covers 100% of the empty property set. With no parameters to document, there is nothing for the description to add, so the baseline of 4 is appropriate.

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 states a precise purpose: returning what an AI plan can be generated from, along with credit costs. It then enumerates all five template types, making the resource and scope unmistakable and clearly distinguishing it from sibling tools like list_ai_plans or get_ai_plan.

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

Usage Guidelines5/5

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

It explicitly says to read this before proposing a plan, which establishes when to use it as a reference lookup. It also explains the dependency on create_ai_plan and the PLANVORTEX_MCP_ALLOW_AI=1 environment variable, including how to guide the user if plan creation is unavailable.

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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