tdmcp

Connect Replicate prediction bridge

connect_replicate_prediction_bridge

Create a scaffold for Replicate prediction handoffs with request templates, polling/webhook maps, output contracts, and credential-safety notes to bridge AI models into TouchDesigner.

Instructions

Create a Replicate-style prediction handoff scaffold with request templates, polling/webhook maps, output contracts, and credential-safety notes.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "connect_replicate_prediction_bridge"
  }
}

Input Schema

Name	Required	Description	Default
`name`	No	Generated baseCOMP name.	replicate_prediction_bridge
`active`	No
`model_ref`	No	Model/version reference hint.	owner/model:version
`output_mode`	No		image
`parent_path`	No	Parent COMP for the Replicate scaffold.	/project1
`webhook_url`	No	Optional webhook callback URL or adapter route.
`endpoint_url`	No	Prediction endpoint or local adapter URL.	https://api.replicate.com/v1/predictions
`poll_seconds`	No
`request_mode`	No		webclient_json

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.13.1Aug 2, 2026

TDQS

A3.5/5.0

Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false, so side effects are possible but not destructive. The description adds context by enumerating the scaffold's contents, including 'credential-safety notes' and 'polling/webhook maps', which offer insight into expected behavior. However, it does not explain whether the tool makes external API calls or just creates local project files.

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 a single concise sentence that immediately states the purpose and lists key components. There is no redundant or filler content, and it is appropriately sized for the tool's complexity.

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

Completeness3/5

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

With 9 parameters and no output schema, the description is adequate but not thorough. It communicates the core purpose and main artifacts, but does not describe prerequisites, resulting scaffold structure, expected usage flow, or how the parameters affect the output. For an advanced integration tool, more context would be beneficial.

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?

Schema description coverage is 56%, leaving some parameters undocumented in the schema. The description references high-level concepts like 'polling/webhook maps' and 'output contracts' that loosely map to parameters like poll_seconds, webhook_url, and output_mode, but it does not explicitly explain any parameter. It adds some contextual meaning but does not fully compensate for the coverage gap.

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 uses a specific verb ('Create') and resource ('Replicate-style prediction handoff scaffold') and enumerates concrete deliverables (request templates, polling/webhook maps, output contracts, credential-safety notes). The 'Replicate-style' qualifier clearly distinguishes it from sibling bridge tools like connect_huggingface_inference_bridge or connect_runway_video_bridge.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to use this tool versus alternatives. It does not name any sibling tools, state conditions for use, or mention exclusions. The implied usage is that you would use it when you want a Replicate prediction bridge, but that is not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server