Dokploy MCP Server

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

Annotations provide structured information (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), which the description doesn't contradict. However, the description adds minimal behavioral context beyond what annotations already declare. It doesn't explain what kind of suggestions are generated, whether there are rate limits, authentication requirements, or what the typical response format looks like. With annotations covering the basic safety profile, the description adds some value by indicating it's a POST operation but lacks rich behavioral details.

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

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

The description is extremely concise with just the operation type and parameter listing. While it could be more informative, every element serves a purpose - it identifies the HTTP method and lists the parameters. There's no wasted text, though the structure is minimal rather than optimally informative.

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

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

Given the complexity of an AI suggestion tool with 3 parameters, 0% schema description coverage, no output schema, and no behavioral context beyond basic annotations, the description is inadequate. It doesn't explain what the tool returns, what kind of suggestions it generates, or how the parameters interact. For a tool that likely involves AI model interaction, this leaves significant gaps in understanding how to use it effectively.

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

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

Schema description coverage is 0%, meaning none of the parameters have descriptions in the schema. The tool description only lists parameter names and types (aiId, input, serverId) without explaining what these parameters represent, what format they should be in, or what values are expected. For a tool with 3 parameters and 0% schema coverage, the description fails to compensate by providing meaningful semantic information about what each parameter does.

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

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

The description is essentially a tautology that restates the tool name 'ai_suggest' as 'ai.suggest' with minimal additional information. It doesn't specify what kind of suggestions are generated, for what purpose, or what resource is being acted upon. While it mentions it's a POST operation, this doesn't meaningfully clarify the tool's purpose beyond the name.

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

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling AI tools available (dokploy_ai_create, dokploy_ai_get, dokploy_ai_getAll, dokploy_ai_getModels, dokploy_ai_one, dokploy_ai_update, dokploy_ai_delete, dokploy_ai_deploy), there's no indication of when 'suggest' is appropriate versus other AI operations. No context, prerequisites, or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.