Get a list of all supported image-generation models with their credit cost, default aspect ratio, and input types. Identify the correct model ID to use for generating images.
MIT
596,087 tools. Updated 2026-09-21 06:28
"A Model Context Protocol (MCP) server for Leonardo.ai image generation" matching MCP tools:
- Register a generation model for testing by selecting an LLM from the registry, enabling use with run_test.Apache 2.0
- Get MCP server environment details: version info for server, FastMCP, MCP protocol, and Python runtime. Use for debugging and compatibility checks.Apache 2.0
- List the lipsync models available for video generation, returning model IDs you can use as the 'model' parameter when creating a new generation.MIT
- Update a registered generation model to point to a different LLM from the registry, enabling model swaps.Apache 2.0
- Run automated synthetic checks on any remote MCP server to verify reachability, protocol compliance, JSON Schema validity, and exposed credentials, returning a detailed diagnostic report.Apache 2.0
Matching MCP Servers
- AlicenseNot gradedqualityDmaintenanceMCP server enabling real-time weather queries via Tavily API and internet usage data by country via MongoDB.Apache 2.0
- AlicenseNot gradedqualityDmaintenanceA production-ready MCP server template that connects LLMs and AI agents to external data, tools, and services with built-in OAuth 2.1 authentication, Redis-backed session management, and a modular tools engine.1MIT
Matching MCP Connectors
New MCP servers on GitHub: discovery index. $0.01/query. Register in-session — free testnet funds.
- mcp-qwen-imageOAuth
MCP server for Qwen Image 3 AI image generation
- Checks an MCP server's provenance, permissions, tool safety, and risk signals before connection, so you can avoid unsafe third-party servers.MIT
- Capture the current page or screen as a base64-encoded image, resized and compressed to fit model context limits. Use it to inspect visual state during automation.MIT
- Delete a registered generation model and permanently erase all associated test runs and data points.Apache 2.0Destructive
- Generate images from text prompts using ModelScope AI models. Supports text-to-image and image-to-image, with an optional source image for transformation.Apache 2.0
- Clear the stored API key for a named company context to revoke access and remove credentials from server memory.Apache 2.0
- Look up current RunAPI pricing for gpt-4o-image model and text-to-image endpoint to estimate image generation costs.Apache 2.0
- Run AI inference on Theta EdgeCloud models for image generation, audio transcription, and text generation. Check available services with list_services to get required inputs.MIT
- Browse 550+ generative AI models by type and keyword to find model IDs for generation workflows.MIT
- Generate images from text descriptions using Pollinations models. Supports optional reference images for image-to-image generation.Apache 2.0
- Check per-provider pricing, supported parameters, and passthrough options for an OpenRouter image model to avoid failed image generation calls.Apache 2.0
- List Pollinations image and video models with filters for modality, pricing, capabilities, and search to choose the right model before generation.Apache 2.0
- Run a fal.ai model synchronously and receive the result. Ideal for fast models like image generation, image editing, and short text or audio tasks.MIT
- Fetch in-process Prometheus metrics from the PostgreSQL MCP server when the HTTP /metrics endpoint is unreachable, using the MCP protocol.MIT
- Verify server identity and protocol compatibility by retrieving the manifest with protocol version, server name, and available capabilities before interacting with tools.Apache 2.0
- Run a local Ollama model for summarization, extraction, and reformatting; reads files server-side so only the answer consumes your context.MIT