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Replicate-MCP-Server

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TypeScript
Hybrid

Generate a 3D model with Replicate

replicate_generate_3d

Generates a downloadable 3D mesh (GLB/OBJ) from a text prompt or reference image, enabling 3D asset creation for design, prototyping, and visualization.

Instructions

Generate a 3D mesh (GLB/OBJ) from a text prompt or a reference image. 3D generation is slow — typically 1-5 minutes.

DISPLAY REQUIREMENT — after this tool returns successfully, include the download URL(s) so the user can open the 3D file. URLs expire in ~24h.

Args:

  • prompt (string, optional): Text description of the 3D object. Provide at least one of prompt or image_url.

  • image_url (URL, optional): Reference image to convert to 3D. Provide at least one of prompt or image_url. Use replicate_upload_file for local files.

  • model (string, default "hunyuan-3d"): Curated key (hunyuan-3d, rodin, triposr) or "owner/name[:version]".

  • extra_input (object, optional): Model-specific extras (e.g. {num_inference_steps: 50}).

  • download (boolean, default true): Download the GLB/OBJ locally.

  • timeout_ms: Default 300000. For complex objects, increase or use the pending+poll flow.

Returns: PredictionResult. local_paths will contain .glb or .obj files.

Examples:

  • prompt="A red ceramic teapot" → hunyuan-3d

  • image_url="", model="triposr" → fast single-image 3D

  • image_url="", model="rodin" → high-quality 3D

Input Schema

NameRequiredDescriptionDefault
modelNo3D generation model. Curated: hunyuan-3d, rodin, triposr. Or "owner/name".hunyuan-3d
promptNoText description of the 3D object to generate. Provide either this or image_url (or both).
downloadNo
image_urlNoURL of a reference image to convert to 3D. Provide either this or prompt (or both). Use replicate_upload_file for local images.
timeout_msNoMax ms to wait for the prediction. If exceeded, returns the prediction ID so you can poll via replicate_get_prediction. Default: 300000 (5min).
extra_inputNoAdditional model-specific inputs (e.g. {num_inference_steps: 50}).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv3.3.1
    • addedInput schema / properties / extra_input / propertyNames
      Added value: +{
+  "type": "string"
+}
  2. First observedv3.2.3

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial context beyond the annotations: expected latency (1-5 min), URL expiry (~24h), a display requirement for the returned URLs, and the timeout->prediction-ID->poll fallback. These are operational traits the readOnly/openWorld/idempotent hints cannot convey.

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

Conciseness4/5

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

Front-loaded with purpose and latency, then cleanly sectioned into display requirement, args, returns, and examples. Minor redundancy where the prompt/image_url 'provide at least one' rule is stated twice, but nothing is padding.

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?

No output schema exists, and the description compensates by naming the return type (PredictionResult) and the field holding artifacts (local_paths with .glb/.obj). Combined with the timeout/poll note and display requirement, an agent has everything needed to call and surface results.

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?

Schema coverage is 83%, so baseline is 3, but the description adds real value: it explains that model accepts either a curated key or an owner/name[:version] string, that download controls local GLB/OBJ retrieval, and that timeout_ms should be raised for complex objects. Only extra_input remains thinly described beyond the schema's example.

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?

States a specific verb (generate) and resource (3D mesh in GLB/OBJ) plus both input modalities (text prompt or reference image). This clearly separates it from replicate_generate_image, replicate_generate_video, and replicate_upscale_image in the sibling list.

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?

Gives concrete selection guidance: at least one of prompt/image_url must be supplied, local files must go through replicate_upload_file first, and three worked examples map scenario to model (triposr for fast single-image, rodin for high quality). It does not explicitly state when NOT to use this tool (e.g. to edit an existing mesh), which keeps it below a 5.

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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