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Anaplan MCP Server and API by Cotlet

Get model history in Anaplan

anaplan_get_model_history
Read-onlyIdempotent

Get model history in the user's own Anaplan account from ChatGPT, Claude or any AI agent. Returns how to do it in Anaplan step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Anaplan Cloud Browser. Anaplan's official API: Yes.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive and closed-world, so the safety profile is covered by structured data. The description adds genuinely non-obvious behavior: the call 'opens nothing by itself' and merely returns screens, buttons and fields to follow. That disclosure prevents an agent from assuming a side effect occurred. The trailing 'Anaplan's official API: Yes' is cryptic and adds little interpretable context.

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

Conciseness3/5

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

The core points (returns instructions, opens nothing, then use cotlet_browser_*) are front-loaded and useful. However, 'from ChatGPT, Claude or any AI agent' is promotional filler and 'Anaplan's official API: Yes' is an unexplained fragment that costs space without informing invocation. Two of four sentences are weaker than the rest.

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?

For a zero-parameter tool with no output schema, the definition supplies what an agent needs: what is returned (step-by-step UI instructions), what is not done (no action taken), and the next tool family to use. A slightly fuller statement of the return shape, or a note on whether the steps cover all model-history views, would close the remaining gap.

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 takes zero parameters and the schema is empty with additionalProperties false, so there is nothing the description needs to disambiguate. Baseline of 4 applies; no parameter meaning is missing or contradicted.

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 names the resource (model history in the user's Anaplan account) and then does the important work of clarifying that the tool itself returns step-by-step instructions rather than the history data. That correction is essential because the tool name alone would mislead an agent into expecting a data read. It stops short of 5 because the opening sentence restates the name and the true output type is only revealed in the second sentence.

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 clearly routes the agent: call this first, then execute the steps with the cotlet_browser_* tools in Anaplan Cloud Browser. That is a concrete when-to-use plus named follow-on tools. It lacks any when-not-to-use guidance or a named alternative for agents that want the history data returned programmatically rather than as instructions.

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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