MCP Image vs Replicate MCP Server

MCP Image tools

No tool names declared yet. Check the project README from the listing page.

Replicate MCP Server tools 36

• replicate_generate_imageGenerate one or more images from a text prompt using a Replicate image model. Use this for any "draw / create / generate an image of …" request. By default it uses Flux Schnell (fast, ~2 seconds per image). DISPLAY REQUIREMENT — after this tool returns successfully, you MUST embed the image inline in your reply by pasting ONE of the three embed blocks the tool prints verbatim (Option 1 iframe, Option 2 <img>, or Option 3 markdown — try them in that order; pick the first one your chat client renders). The iframe variant scales to the chat column width with the image's native aspect ratio; the <img> variant is a responsive fallback; markdown is the universal last resort. Place the chosen embed BEFORE any descriptive prose. Do NOT paraphrase the URL or omit the embed — the user wants the image to appear in the main chat flow, not only inside the collapsed tool widget. URLs expire in ~24h. Args: - prompt (string): Text description of the image to generate. - model (string, default "flux-schnell"): Either a curated key (flux-schnell, flux-dev, flux-pro, flux-2-max, sd-3.5-large, recraft-v3, recraft-v4.1, ideogram-v2, imagen-3, seedream) or a full Replicate identifier "owner/name[:version]". - aspect_ratio ("1:1" | "16:9" | "9:16" | "4:3" | "3:4" | "21:9" | "3:2" | "2:3", optional): Aspect ratio. Default 1:1. - num_outputs (1-4, optional): How many images to generate. - seed (integer, optional): Random seed for reproducible output. - extra_input (object, optional): Model-specific extra inputs (e.g. {guidance: 3.5, num_inference_steps: 28}). Use replicate_get_model_schema if unsure. - download (boolean, default true): Download files locally to ~/Downloads/replicate-mcp/. - timeout_ms (5000-1800000, optional): Max wait. Default 300000 (5min). Returns structuredContent matching PredictionResult: { "status": "starting" | "processing" | "succeeded" | "failed" | "canceled", "prediction_id": string, "model": string, "urls": string[], // Replicate URLs (expire ~24h) "local_paths": string[], // Absolute paths on disk when download=true "metrics": { "predict_time_seconds": number } | undefined, "error": string | undefined, "pending": boolean | undefined // true if timed out — poll via replicate_get_prediction } Examples: - "An origami fox in a misty forest" → uses flux-schnell, 1:1 - prompt="logo for a coffee shop called Crema", model="recraft-v3" → for text-in-image - prompt="cinematic shot of a lighthouse", model="flux-pro", aspect_ratio="21:9", seed=42 Error handling: - If REPLICATE_API_TOKEN is missing, returns an actionable error telling the user how to set it. - Invalid model IDs return Replicate's error message verbatim.
• replicate_generate_videoGenerate a video clip from a text prompt (and optionally a starting image). Video generation is slow — typically 1-5 minutes per clip. DISPLAY REQUIREMENT — after this tool returns successfully, include the URL(s) printed in the tool's text content so the user can open the video. URLs expire in ~24h. Args: - prompt (string): Text description of the video. - model (string, default "kling-pro"): Curated key (kling-pro, minimax-video, hunyuan-video, luma-ray, wan-2.2, grok-video, seedance) or "owner/name[:version]". - image_url (string, optional): Starting frame for image-to-video. Not all models support this. - duration_seconds (1-60, optional): Desired duration. Model-dependent. - aspect_ratio ("16:9" | "9:16" | "1:1", optional): Aspect ratio. - extra_input (object, optional): Additional model-specific inputs. - download (boolean, default true): Download the MP4 locally. - timeout_ms: Max wait. Default 300000 (5min). For very long videos, increase or rely on the pending+poll flow. Returns: PredictionResult (see replicate_generate_image for shape). The local_paths will contain .mp4 files when downloaded. Tip: If timeout_ms is exceeded, the result will have pending=true and a prediction_id. Wait a minute, then call replicate_get_prediction.
• replicate_generate_audioGenerate music, ambient audio, or full songs from a text prompt. DISPLAY REQUIREMENT — after this tool returns successfully, include the URL(s) printed in the tool's text content as a markdown link `[Audio](URL)` in your reply so the user can play it. URLs expire in ~24h. Models: - "musicgen" (default): Meta MusicGen. Instrumental music up to 30s. prompt → "prompt" field. - "ace-step": Full songs with lyrics. prompt → "tags" field (style/genre tags). Pass lyrics separately via extra_input.lyrics. ~3-4 minutes runtime. - "riffusion": Loop-friendly ambient/electronic. prompt → "prompt_a" field. No duration control. - "minimax-music": MiniMax Music 2.6. Full songs up to 6min. prompt=style description; pass lyrics via extra_input.lyrics. - "lyria-3-pro": Google Lyria 3 Pro. Full songs up to 3min WITH sung vocals. Put genre, mood, lyrics, and structure ([Verse]/[Chorus]) directly in the prompt. No duration — do NOT pass duration_seconds. Also "lyria-3" (30s clips) and "lyria-2" (48kHz instrumental). Args: - prompt (string): Description of the music. For ace-step this maps to the "tags" field (style tags like "rock, guitar, upbeat"). For riffusion this maps to "prompt_a". For lyria put genre/mood/lyrics/structure here. - model (string, default "musicgen"): Curated key (musicgen, ace-step, riffusion, minimax-music, lyria-3-pro, lyria-3, lyria-2) or "owner/name[:version]". - duration_seconds (1-300, optional): Duration in seconds. Supported by musicgen and ace-step. Ignored for riffusion and the lyria models (they have no duration parameter). - extra_input (object, optional): Additional inputs. Examples: {temperature: 1.0, top_k: 250} for MusicGen; {lyrics: "verse lyrics here"} for ace-step. - download (boolean, default true): Download as MP3/WAV. - timeout_ms: Default 300000 (5min). Returns: PredictionResult. local_paths contain audio files. Examples: - prompt="upbeat synthwave with driving bassline", duration_seconds=15 → musicgen - prompt="indie folk, acoustic guitar, female vocals", model="ace-step", extra_input={lyrics: "Leaving home on a rainy day..."} - prompt="ambient lo-fi chill", model="riffusion"
• replicate_generate_speechConvert text to natural-sounding speech. DISPLAY REQUIREMENT — after this tool returns successfully, include the URL printed in the tool's text content as a markdown link `[Speech](URL)` in your reply so the user can play it. URLs expire in ~24h. Args: - text (string, 1-5000): Text to synthesize. - model (string, default "kokoro"): Curated key (kokoro, minimax-speech, chatterbox, gemini-tts, grok-tts) or "owner/name[:version]". - voice (string, optional): Voice ID. For Kokoro: af_bella, af_sarah, am_adam, am_michael, bf_emma, bf_isabella, etc. (a-f = American female, b-f = British female, a-m = American male, b-m = British male). - speed (0.5-2.0, optional): Speech rate. - extra_input (object, optional): Model-specific extras (e.g. {audio_prompt: "<url>"} for voice cloning with Chatterbox). - download (boolean, default true). - timeout_ms: Default 300000. Returns: PredictionResult. local_paths contain WAV/MP3 files.
• replicate_chatRun a large language model hosted on Replicate. Use this for free-form text generation, Q&A, code writing, summarisation, translation — anything where the input is text and the output is text. Args: - prompt (string): User message. - model (string, default "llama-3-70b"): Curated key (llama-3.1-405b, llama-3-70b, llama-3-8b, mistral-7b, mixtral-8x7b, deepseek-r1) or "owner/name". - system_prompt (string, optional): Persona / instructions. - max_tokens (1-8192, optional): Generation limit. - temperature (0-2, optional): Sampling temperature. - extra_input (object, optional): Model-specific extras (top_p, top_k, frequency_penalty, etc.). - download (boolean, default false): No file outputs; leave false. - timeout_ms (5000-1800000, optional): Default 300000. Returns: PredictionResult with text_output[0] containing the model's reply (later entries are raw streamed segments if applicable). Examples: - prompt="Explain quantum entanglement in two sentences.", model="llama-3-70b" - prompt="Write a Python function to compute Levenshtein distance.", model="mistral-large", system_prompt="You are an expert software engineer."
• replicate_visionRun a vision-language model to describe, caption, or answer questions about an image. Args: - image (string URL): URL of the image to analyse. - prompt (string, optional): Question or instruction (e.g. "describe this image", "count the people"). Default is a generic caption. - model (string, default "llava-13b"): Curated key (llava-13b, llava-v1.6-34b, blip-2, qwen-vl) or "owner/name". - max_tokens (1-4096, optional): Response length. - extra_input (object, optional): Model-specific extras. Returns: PredictionResult with text_output containing the model's textual answer. Examples: - image="https://example.com/photo.jpg", prompt="What objects are visible?" - image="<chart-url>", prompt="Read the values off this chart and list them.", model="llava-v1.6-34b"
• replicate_upscale_imageUpscale an image to higher resolution. Optional face restoration for photos. DISPLAY REQUIREMENT — after this tool returns successfully, embed the upscaled image inline using one of the three blocks (iframe / <img> / markdown) printed by the tool. Place it BEFORE descriptive prose. URLs expire ~24h. Args: - image (string URL): URL of the source image. - model (string, default "real-esrgan"): Curated key (real-esrgan, clarity-upscaler, swinir, gfpgan) or "owner/name". - scale (1-10, optional): Upscale factor. Default 4 for real-esrgan; 2 for gfpgan; 2 for clarity-upscaler. - extra_input (object, optional): Model-specific extras (e.g. {face_enhance: true} for real-esrgan). - download (boolean, default true): Download upscaled file locally. Returns: PredictionResult with urls + local_paths to the upscaled image. Examples: - image="<low-res-photo>", scale=4 → real-esrgan - image="<face-photo>", model="gfpgan", scale=2 → restoration - image="<artwork>", model="clarity-upscaler", scale=2
• replicate_remove_backgroundProduce a transparent-background version (PNG) of an image. DISPLAY REQUIREMENT — after this tool returns successfully, embed the cut-out image inline using one of the three blocks (iframe / <img> / markdown) printed by the tool. Args: - image (string URL): URL of the source image. - model (string, default "rembg"): Curated key (rembg, birefnet, briaai-rmbg) or "owner/name". - extra_input (object, optional): Model-specific extras. - download (boolean, default true): Download the cut-out PNG locally. Returns: PredictionResult with urls + local_paths to a transparent PNG. Examples: - image="<product-photo>" → rembg quick cut - image="<portrait>", model="birefnet" → sharper edge for hair
• replicate_transcribe_audioTranscribe an audio or video file to text using Whisper-family models on Replicate. Args: - audio (URL): URL of the audio (or video) to transcribe. - model (default "incredibly-fast-whisper"): Curated key (whisper, incredibly-fast-whisper, whisperx, scribe) or "owner/name". - language (string, optional): ISO-639 hint (e.g. "en", "it"). Default: auto-detect. - translate_to_english (bool, optional): Translate the transcript to English instead of preserving source language. - extra_input (object, optional): Model-specific extras (e.g. {batch_size: 24} for incredibly-fast-whisper). Returns: PredictionResult with text_output containing the transcript.
• replicate_inpaintFill masked regions of an image based on a text prompt. Works for both inpainting (replace inside) and outpainting (extend canvas) when the mask covers the target area. DISPLAY REQUIREMENT — embed the result inline using one of the three blocks (iframe / <img> / markdown) printed by the tool. Args: - image (URL): Source image. - mask (URL): Mask image. White = keep, black/transparent = repaint. - prompt: Describes what should appear in the masked region. - model (default "flux-fill-pro"): Curated (flux-fill-pro, sd-inpaint, ideogram-v2-edit) or "owner/name". - extra_input (object, optional): Model-specific extras (e.g. {guidance: 30} for flux-fill-pro).
• replicate_segmentProduce a segmentation mask of an image. Use SAM 2 for point/box-prompt masks (auto-mask everything when no prompt given) or Grounded-SAM for text-prompt masking like "the red car". DISPLAY REQUIREMENT — embed the mask result inline using one of the three blocks printed by the tool. Args: - image (URL): Source image. - prompt (string, optional): Text prompt for grounded segmentation. Required for grounded-sam. - model (default "sam-2"): Curated (sam-2, grounded-sam) or "owner/name". - extra_input (object, optional): SAM-specific tuning (e.g. {points_per_side: 32}).
• replicate_embed_textConvert text(s) into numeric embedding vectors. Useful for RAG, semantic search, clustering, similarity scoring. Args: - texts: A single string or an array of strings (max 256). Each text is embedded independently. - model (default "bge-large"): Curated (bge-large, jina-embeddings-v3, all-minilm) or "owner/name". - extra_input (object, optional): Model-specific extras (e.g. {task: "retrieval.query"} for jina v3). Returns: PredictionResult — the embedding vectors are in structuredContent.output (model-specific shape).
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