HunyuanVideo 1.5 720p MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_video_modelsB | List the single enabled HunyuanVideo generation profile. |
| upload_video_input | Upload one PNG/JPEG to private R2 and return an asset_id for submit_video_job. Supply exactly one source. Use local_path when the agent has an attachment's local file path; otherwise pass base64 bytes or a PNG/JPEG data URI. |
| list_uploaded_video_inputsC | List recent images uploaded through upload_video_input. |
| estimate_video_jobC | Estimate runtime and compute cost without contacting RunPod. |
| submit_video_job | Queue a HunyuanVideo-1.5 720p I2V job and return immediately. |
| get_video_jobA | Return the current state and metadata for a Hunyuan job. |
| get_video_result | Return a completed result URL, or the current status if incomplete. |
| cancel_video_job | Request cancellation of a queued or running job. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a distinct purpose: listing models, listing uploaded inputs, estimating a job, and getting a job's state. There is no overlap or ambiguity.
All tools follow a consistent verb_noun pattern (list_, estimate_, get_), making it predictable for agents.
With 4 tools, the set is small but reasonable for a focused server. A few more tools might be expected, but the count is not problematic.
The tool surface has significant gaps: there is no tool to upload video inputs or to create a video generation job, which are core operations implied by the server's purpose.