CNAPS.ai MCP Server

create_community_post

Publish one of your flows to the cnaps.ai community. Creates a community post with a snapshot of the flow. Others can then discover and fork your flow. Requires a source_flow_id (from list_flows) and a title.

Input Schema

TableJSON Schema

Name	Required	Description
`tags`	No	Tags for discoverability. JSON array or comma-separated, e.g. 'super-resolution,image,upscale'. Max 20 tags, 64 characters each.
`title`	Yes	Post title — a clear, descriptive name for the flow.
`content`	No	Post body/description. Explain what the flow does and how to use it.
`thumbnail_url`	No	Pre-uploaded thumbnail image URL (use upload_file first if needed).
`source_flow_id`	Yes	The flow ID to publish (use list_flows to find your flows).

TDQS

A4/5.0

Behavior3/5

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

Annotations only indicate non-read-only and non-idempotent, so the description carries the burden of explaining side effects. It adds that a 'snapshot' of the flow is created and that others can 'discover and fork' it. However, it does not disclose whether posts are permanent, publicly visible by default, or how to manage/delete them, leaving some behavioral ambiguity for a mutation tool.

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 sentences with no filler. It opens with the core verb and resource, then explains the outcome and prerequisites, making it efficient and easy to parse.

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?

Given the moderate complexity of a 5-parameter creation tool with no output schema, the description covers the main action, effect, and prerequisite. It does not detail return values or confirmation behavior, but combined with sibling context and a fully described schema, it is adequately complete.

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

Parameters3/5

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

The input schema has 100% coverage with descriptions for all five parameters. The description mentions source_flow_id from list_flows, which mirrors the schema text, and does not add new parameter-level meaning beyond what the schema already provides.

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 clearly states the action: 'Publish one of your flows to the cnaps.ai community' and the result: 'Creates a community post with a snapshot of the flow.' This distinguishes it from sibling tools like fork_community_flow or get_community_post, making the purpose unambiguous.

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?

The description provides clear context for when to use the tool: to share flows for community discovery and forking. It also mentions the required prerequisite source_flow_id from list_flows. No explicit exclusions or alternatives are given, but the use case is specific enough to guide an agent.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool targets a distinct resource and action, with clear separation between flow lifecycle, execution, model exploration, community, and account tools. Even similar-sounding tools like create_flow, preview_flow, and suggest_flow have clearly different purposes (actually creating, dry-running, and recommending models). Descriptions prevent misselection.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case (e.g., create_flow, list_flows, run_batch, cancel_flow). No mixed conventions or vague verbs like 'process' or 'handle'. The naming is uniform and predictable.

Tool Count3/5

At 33 tools, this is a large surface, but each tool addresses a distinct feature of the cnaps.ai platform, from flow CRUD and execution to community features and notifications. Still, it exceeds the typical well-scoped range and feels heavy, making it a borderline case between appropriate and too many.

Completeness3/5

The core flow lifecycle (create, read, update, delete, restore, duplicate) and execution (run, batch, cancel) are covered, but structural editing of flow graphs is missing—update_flow only changes parameters, not topology. Additionally, there is no run history, batch list/cancel, or community post update/delete, leaving notable gaps for a platform API.

Resources

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