CNAPS.ai MCP Server

update_flow

DestructiveIdempotent

Change an existing flow: rename it, replace its tags, and/or update node parameters. Provide any combination — one call can do all three. Node parameters are merged with existing values, so specify only what changes; tags replace the existing set. Cannot update a flow that is currently running.

Input Schema

TableJSON Schema

Name	Required	Description
`name`	No	New name for the flow.
`tags`	No	Tags to replace all existing manual tags with. JSON array or comma-separated, e.g. '["upscale","4k"]' or 'upscale,4k'. Entries are trimmed.
`flow_id`	Yes	The unique identifier of the flow to update.
`node_updates`	No	JSON array of node parameter updates. Each entry has node_id (number) and parameters (object with key-value pairs to set/override). Example: [{"node_id": 1, "parameters": {"scale_factor": 4, "steps": 50}}]. Unspecified parameters keep their current values.

TDQS

A4.4/5.0

Behavior4/5

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

Beyond the annotations (readOnly=false, destructive=true, idempotent=true), the description adds valuable behavioral details: node parameters are merged with existing values, tags replace the existing set, and any combination of updates can be done in one call. It also discloses the running-flow limitation, adding context not present in annotations.

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, each earning its place: the first states the purpose and options, the second explains merge/replace behavior, and the third states the critical constraint. It is well-structured, front-loaded, and free of redundancy.

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 tool's moderate complexity (4 params, no output schema) and presence of annotations, the description covers the main behaviors and constraints. It lacks details about the return value or error handling, but these are not expected for a simple update operation without an output schema. The description is sufficient for an agent to use the tool effectively.

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 schema already describes all parameters at 100% coverage, so the baseline is 3. The description adds value by clarifying the merge-vs-replace semantics for node_updates and tags, and by emphasizing that any combination of parameters can be provided in a single call, which is not immediately obvious from the schema alone.

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 tool's purpose with a specific verb ('Change') and resource ('an existing flow'), and enumerates the three update actions (rename, replace tags, update node parameters). This distinguishes it from sibling tools like create_flow or delete_flow.

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 (when updating an existing flow) and includes a key constraint: 'Cannot update a flow that is currently running.' However, it does not explicitly name alternatives or state when not to use it, though sibling names imply the distinction.

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.

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