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Generate Pollinations Video

pollinations_generate_video

Generate videos from text prompts or reference images using Pollinations video models, returning the final video URL for immediate use.

Instructions

Generate a video from a text prompt using Pollinations video models. This calls GET /video/{prompt} and returns the final media URL plus response metadata. Use this when the user wants text-to-video or image-to-video output. For static images, use pollinations_generate_image instead. Args: - prompt (string, required): Text description of the video. Include subject, scene, motion, camera movement, mood, lighting, style, and any timing notes. - model (string, required): Pollinations video model slug. Known video models include veo, seedance-pro, seedance-2.0, wan, wan-fast, wan-pro, wan-pro-1080p, grok-video-pro, ltx-2, p-video-720p, p-video-1080p, nova-reel. Call pollinations_list_models with modality=video first for current capabilities/pricing. - duration (number, optional, 1-120): Duration in seconds. Model rules vary: veo supports 4, 6, or 8s; seedance supports 2-10s; seedance-2.0 supports 4-15s; wan supports 2-15s; nova-reel supports 6-120s in multiples of 6. - aspectRatio (string, optional): 16:9 or 9:16. Use 16:9 for landscape, 9:16 for vertical/social video. If omitted, Pollinations may derive it from width/height. - width and height (numbers, optional): Requested dimensions. Video models map these to nearest supported resolution tiers such as 480p, 720p, or 1080p. - image (string or string[], optional): Reference frame URL(s). For video, image[0] is the start frame. image[1] is the end frame for models with end_frame support. End frame is documented for veo, seedance, seedance-2.0, and wan-fast; other models may ignore image[1]. - audio (boolean, optional): Request generated audio where supported. For veo, set true to enable audio. wan may generate audio regardless of this flag. - seed (number, optional): Reproducibility seed. Use -1 for random. Supported by seedance and nova-reel; unsupported models may ignore it. - quality (string, optional): low, medium, high, or hd. Unsupported models may ignore it. - safe (string, optional): Comma-separated safety filters: privacy, secrets, sexual, violence, shield, true, nsfw. - save_output (boolean, optional, default true): Download and save the returned video URL to a local file and include the path in the result. - output_dir (string, optional): Directory for saved files. Defaults to NECTAR_OUTPUT_DIR or ./nectar-output relative to the server process. - filename_prefix (string, optional): Prefix for saved video filenames. Nectar sanitizes this value. - response_format (string, optional, default markdown): markdown summary or json metadata. Returns: Markdown or JSON containing the video URL, content type, and content length when available. Examples: Use model=veo duration=8 aspectRatio=16:9 for a polished landscape clip. Use image=[startUrl,endUrl] with seedance-2.0 or wan-fast for first/last-frame interpolation. Use aspectRatio=9:16 for TikTok/Reels style output. Error handling: 401 means missing/invalid POLLINATIONS_API_KEY. 402 means insufficient pollen. 403 means key/model permission issue. 429 means wait and retry. 400 often means invalid duration/aspect/model combination; call pollinations_list_models and retry with supported values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
safeNoOptional comma-separated safety filters: privacy, secrets, sexual, violence, shield, true, nsfw. true enables privacy,secrets. nsfw enables sexual,violence.
seedNoOptional seed. Use -1 for random. Supported by seedance and nova-reel according to current docs; unsupported models may ignore it.
audioNoWhether to request generated audio when the model supports it. For veo, true enables audio. wan may generate audio regardless.
imageNoOptional reference image URL or up to two URLs. image[0] is the start frame. image[1] is the end frame for models that support end_frame, documented for veo, seedance, seedance-2.0, and wan-fast.
modelYesRequired Pollinations video model slug. Examples: veo, seedance-pro, seedance-2.0, wan, wan-fast, wan-pro, wan-pro-1080p, grok-video-pro, ltx-2, p-video-720p, p-video-1080p, nova-reel. Call pollinations_list_models with modality=video if unsure.
widthNoOptional requested width in pixels. Video models map this to the nearest supported tier such as 480p, 720p, or 1080p.
heightNoOptional requested height in pixels. Video models map this to the nearest supported tier such as 480p, 720p, or 1080p.
promptYesRequired text description of the video. Include scene, subject, motion, camera movement, style, lighting, and timing notes.
qualityNoOptional quality level. Unsupported models may ignore it.
durationNoVideo duration in seconds. Model support varies: veo 4/6/8; seedance 2-10; seedance-2.0 4-15; wan 2-15; nova-reel 6-120 in multiples of 6.
output_dirNoDirectory where generated video files should be saved. Defaults to NECTAR_OUTPUT_DIR or ./nectar-output.
aspectRatioNoOptional video aspect ratio. Use 16:9 for landscape and 9:16 for vertical/social video. If omitted, Pollinations may derive it from width and height.
save_outputNoDownload and save the generated video URL to a local file.
filename_prefixNoOptional prefix for saved video filenames. Example: product-teaser or intro-clip.
response_formatNoMCP response format: markdown for readable summaries, json for returned URL/content metadata plus saved_files metadata when saving is enabled.markdown
Behavior5/5

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

The description extensively discloses behavior beyond annotations: error handling (401/402/403/429/400), model-specific parameter support (e.g., veo durations, seed support), audio behavior for veo/wan, aspect ratio derivation, resolution mapping, end-frame handling, and save_output side effects. No contradictions with 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?

Despite its length, the description is well-structured and information-dense. It front-loads core functionality, then systematically covers parameters, return values, examples, and error handling. Every sentence adds unique value, particularly model compatibility details that are not in the schema.

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

Completeness5/5

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

For a complex tool with 15 parameters and no output schema, the description is exceptionally complete. It explains return values (Markdown/JSON with URL and metadata), error semantics, parameter constraints, and usage patterns. It fully equips an agent to invoke the tool correctly without needing external lookups.

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

Parameters5/5

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

Although schema coverage is 100%, the description adds substantial meaning beyond the schema: model-specific duration rules, supported models for seed, end-frame semantics, quality tiers, and practical examples (veo duration=8, aspectRatio=9:16 for TikTok). It clarifies parameter interactions and defaults like save_output and response_format.

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 it 'Generate a video from a text prompt using Pollinations video models' and references the specific endpoint GET /video/{prompt}. It also differentiates from the sibling tool by saying 'For static images, use pollinations_generate_image instead.'

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?

Explicitly states when to use: 'Use this when the user wants text-to-video or image-to-video output.' It gives an alternative tool for static images and even recommends calling pollinations_list_models first for current capabilities, providing both when-to-use and when-not-to-use guidance.

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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