Skip to main content
Glama

Discover New Popular Replicate Models

replicate_refresh_models
Read-only

Discover new popular Replicate models missing from the curated registry. Get categorized suggestions with run counts to decide which models to add.

Instructions

Search Replicate for popular models NOT yet in the curated registry. Returns suggestions only — does not modify code.

Use this to find new models worth adding. Then ask Claude to edit src/models.ts with the ones you want.

Args:

  • categories (string[], optional): Which categories to check. Default: all 15 (image, video, audio, tts, llm, vision, upscale, bg, stt, inpaint, segment, embed, voiceclone, threed, lipsync).

  • min_run_count (integer, optional): Minimum run_count threshold. Default: 1000.

  • limit_per_category (integer, optional): Max suggestions per category (1-20). Default: 5.

Returns structuredContent: { "checked_at": string, "categories_checked": string[], "suggestions": [{ category, owner, name, model_id, run_count, description, replicate_url }], "already_curated": number, "total_suggestions": number }

Examples:

  • "Check for new popular models" → all categories, min 1000 runs

  • categories=["image","video"], min_run_count=10000 → only top-tier image/video models

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoriesNoCategories to check. Default: all 15 (image, video, audio, tts, llm, vision, upscale, bg, stt, inpaint, segment, embed, voiceclone, threed, lipsync).
min_run_countNoMinimum run_count to surface a model. Default: 1000.
limit_per_categoryNoMax suggestions per category (1–20). Default: 5.
Behavior4/5

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

Adds behavioral context beyond annotations: explains it returns suggestions only, does not modify code, and details the search scope (popular models not in curated registry). Annotations already provide readOnlyHint and destructiveHint.

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?

Well-structured with one-line summary, usage advice, parameter list with defaults, return structure, and examples. No redundant sentences.

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?

Comprehensive for a read-only search tool with three optional parameters. Describes output structure in detail, compensating for missing output schema. Annotations support safe usage.

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 100%, but description elaborates with default values, full list of category options, and practical examples. Adds meaning beyond schema descriptions.

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?

Clearly states it searches for popular Replicate models not in the curated registry and returns suggestions without modifying code. Distinguishes from siblings by focusing on uncurated popular models.

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?

Provides explicit usage advice: 'Use this to find new models worth adding. Then ask Claude to edit src/models.ts with the ones you want.' Does not explicitly exclude alternatives but context is clear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/sena-labs/replicate-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server