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Anythink-MCP

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cli

Run any Anythink command the dedicated tools do not cover and return its output. Pass arguments exactly as after 'anythink', adding --yes or --json when needed.

Instructions

Run any Anythink CLI command and return its output. Prefer the dedicated tools; use this for anything they don't cover. Pass the command exactly as you would after 'anythink', e.g. 'entities list' or 'data list posts'. For destructive commands add '--yes' to skip confirmation prompts. Add '--json' where supported for machine-readable output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
commandYesCLI arguments after 'anythink', e.g. 'entities list', 'users me', 'data list blog_posts --json', 'migrate --from a --to b --dry-run', 'fetch /some/path'. Do NOT include 'anythink' itself or '--profile' (profile is injected automatically).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.2.27
    • removedInput schema / description
      Removed value: -"Run any Anythink CLI command and return its output. Use this for commands not covered by dedicated tools (entities, fields, data, workflows, roles, menus, secrets, users, files, pay, oauth, migrate, fetch, api, docs, etc.). Pass the command exactly as you would after 'anythink', e.g. 'entities list' or 'data list posts'. Menu commands: 'menus list' shows dashboard menus with tree structure; 'menus add-item <menu_id> <entity> --icon <Icon> --parent <parent_id>' adds an entity to a dashboard menu. For destructive commands add '--yes' to skip confirmation prompts. Add '--json' where supported for machine-readable output."
    • removedInput schema / title
      Removed value: -"cli"
  2. First observedv0.2.6

TDQS

A4.6/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that output is returned, that destructive commands may prompt unless '--yes' is added, and that '--json' is available for machine-readable output. It does not cover authentication, error handling, or general side effects, but does more than the minimum.

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?

Four compact sentences with zero waste. It front-loads the core purpose and fallback role, then adds examples and flag guidance in a logical order.

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 one-parameter generic CLI wrapper with no output schema and no annotations, this covers the main selection and invocation concerns. It could be slightly more complete about error behavior or permission requirements, but the essential information is present.

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 single command parameter is fully described in the schema, so baseline is 3. The description adds useful flag semantics beyond the schema, especially '--yes' for skipping confirmation prompts and '--json' for machine-readable output, plus concrete examples of command formatting.

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?

States a specific verb and resource ('Run any Anythink CLI command') and explicitly routes the agent away from dedicated tools toward this fallback. The scope and intended use are unambiguous even against a large sibling set.

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?

Gives explicit when-to-use guidance ('Prefer the dedicated tools; use this for anything they don't cover') and operational instructions like adding '--yes' for destructive commands and '--json' where supported. No inference is needed to select this tool correctly.

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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