DESTRUCTIVE: Permanently delete an app, its Docker service, volume, and all data including version history. This cannot be undone. You MUST confirm with the user before calling this tool.
Connector
127,427 tools. Last updated 2026-05-05 16:38
"Docker container and image management with IDE integration" matching MCP tools:
- Convert a single photo into a textured 3D GLB model. Uses Seed3D — generates accurate geometry and materials from one image. Async — returns requestId, poll with check_job_status. 350 sats per model. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='generate_3d_model'.Connector
- Solve an image-based text captcha and return the recognized text. Works on standard alphanumeric captchas (web signup forms, login walls, scraping checkpoints). OCR via ddddocr — typical p50 latency 30-80ms, 70-90% accuracy on common captcha fonts. Provide either an image URL we fetch on your behalf, or raw base64 image bytes if you already have them. Use when an agent encounters a captcha mid-task and needs to continue without human intervention. Cheaper and faster than 2captcha for simple image captchas; not designed for reCAPTCHA v2/v3 or hCaptcha (those are interaction-based). (price: $0.003 USDC, tier: metered)Connector
- Request an API key for a site you are running on (challenge-response). This starts a two-step verification flow: 1. A claim token is written to your container at ~/.borealhost/.claim_token (mode 600, owner admin — only readable if you're on the container) 2. Read that file and call claim_api_key(token) within 1 hour This proves you have access to the container without storing any secrets on disk permanently. The claim token is single-use and ephemeral. No authentication needed — the proof is reading the file from the container. Args: site_slug: The site identifier (your BorealHost site slug) Returns: {"status": "pending", "site_slug": "my-site", "expires_in_seconds": 3600, "claim_path": "~/.borealhost/.claim_token", "instructions": "Read the claim token and call claim_api_key()..."} Errors: VALIDATION_ERROR: Unknown site slug or no active subscription RATE_LIMITED: Too many pending claim tokensConnector
- Claim an API key using a claim token from the container. After calling request_api_key(), read the claim token from ~/.borealhost/.claim_token on your container and pass it here. The token is single-use — once claimed, it cannot be used again. The API key is automatically activated for this MCP session. Args: claim_token: The claim token string read from the container file Returns: {"api_key": "bh_...", "key_prefix": "bh_...", "site_slug": "my-site", "scopes": ["read", "write"], "message": "API key created and activated..."} Errors: VALIDATION_ERROR: Invalid, expired, or already-claimed tokenConnector
- Classify image safety (normal / suggestive / explicit). Falcons.ai NSFW detection — 100x cheaper and faster than asking an LLM. Returns classification label and boolean is_nsfw flag. Essential for content moderation pipelines. 2 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='detect_nsfw'.Connector
Matching MCP Servers
- Alicense-qualityCmaintenanceAn MCP server for managing and monitoring Docker, Docker Compose, and Kubernetes environments alongside Azure Application Insights. It enables advanced log filtering, container lifecycle management, and querying of cloud application traces and metrics.Last updatedMIT
- Alicense-qualityCmaintenanceA secure, container-based implementation of the Model Context Protocol (MCP) that provides sandboxed environments for AI systems to safely execute code, run commands, access files, and perform web operations.Last updated21Apache 2.0
Matching MCP Connectors
UK pest, disease, and weed management — symptom diagnosis, IPM, approved products
Upload, organize, search, and transform images, videos, and files with AI-powered tools.
- Edit an image with natural language instructions. Uses Nano Banana 2 — understands context, handles object addition/removal, style transfer, and inpainting. Returns JSON with image URL. Resolution-tiered pricing: 1K=200 sats, 2K=300 sats, 4K=450 sats. Pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='edit_image' and resolution param.Connector
- Restore and enhance faces in an image using GFPGAN. Detects all faces via RetinaFace, restores quality (fixes blur, noise, compression artifacts), and pastes them back. Optionally enhances the background using Real-ESRGAN. GPU-accelerated, sub-3s latency. Args: image_base64: Base64-encoded image data containing faces (PNG, JPEG, WebP). upscale: Output upscale factor -- 1 to 4 (default: 2). enhance_background: Whether to enhance background with Real-ESRGAN (default: true). Returns: dict with keys: - image (str): Base64-encoded restored image - format (str): Output image format - width (int): Output width - height (int): Output height - upscale (int): Scale factor applied - processing_time_ms (float): Processing time in millisecondsConnector
- WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.Connector
- Export a generated image asset by session and asset ID. Returns the image inline as base64 along with metadata (format, dimensions, size). When running locally (stdio transport), you can optionally provide a destinationPath to save the image to disk. USAGE: After generating an image with generateImage, use the sessionId and assetId to export: exportImageAsset(sessionId="...", assetId="...") To save to disk (local/stdio only): exportImageAsset(sessionId="...", assetId="...", destinationPath="/Users/me/project/images/logo.png")Connector
- Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.Connector
- Remove background from any image, returning transparent PNG. Uses BiRefNet (state-of-the-art, Papers with Code — Sm 0.901 on DIS5K). Handles hair, fur, glass, transparency, and complex edges. Stable endpoint — model upgrades automatically as SOTA evolves. 5 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='remove_background'.Connector
- WORKFLOW: Step 1 of 4 - Start infrastructure design conversation Open an InsideOut V2 session and receive the assistant's intro message. The response contains a clean message from Riley (the infrastructure advisor) - display it to the user. ⚠️ Riley will ask questions - forward these to the user, DO NOT answer on their behalf. CRITICAL: This tool returns a session_id in the response metadata. You MUST use this session_id for ALL subsequent tool calls (convoreply, tfgenerate, tfdeploy, etc.). Use when the user mentions keywords like: 'setup my cloud infra', 'provision infrastructure', 'deploy infra', 'start insideout', 'use insideout', or similar intent to begin infra setup. OPTIONAL: project_context (string) - General tech stack summary so Riley can skip discovery questions and jump to recommendations. The agent should confirm this with the user before sending. Include whichever apply: language/framework, databases/services, container usage, existing IaC, CI/CD platform, cloud provider, Kubernetes usage, what the project does. Example: 'Next.js 14 + TypeScript, PostgreSQL, Redis, Docker Compose, deployed to AWS ECS, GitHub Actions CI/CD, ~50k MAU'. NEVER include credentials, secrets, API keys, PII, source code, or internal URLs/IPs -- only general metadata summaries useful to a cloud architect agent. IMPORTANT: source (string) - You MUST set this to identify which IDE/tool you are. Auto-detect from your environment: 'claude-code', 'codex', 'antigravity', 'kiro', 'vscode', 'web', 'mcp'. If unsure, use the name of your IDE/tool in lowercase. Do NOT omit this — it controls the 'Open {IDE}' button on the credential connect screen. OPTIONAL: github_username (string) - GitHub username for deploy commit attribution. Pre-populates the GitHub username field on the connect page. 💡 TIP: Examine workflow.usage prompt for more context on how to properly use these tools.Connector
- Colorize black-and-white or grayscale photos. DDColor (dual-decoder, ICCV 2023) — vivid, natural colorization. Impossible for text/vision LLMs. 5 sats per image, pay per request with Bitcoin Lightning — no API key or signup needed. Requires create_payment with toolName='colorize_image'.Connector
- Execute an integration action — e.g., send an email via Resend, create a payment via Mollie. The system resolves vault credentials server-side so you never handle API keys directly. The integration must be configured first via setup_integration (not needed for built-in integrations). Call get_integration_schema first to get the exact endpoint name and required input fields.Connector
- Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...Connector
- Return the primary image URL and current metadata for a work, so you can visually analyze the image yourself and propose structured catalogue fields. Use this when the artist asks you to read a work you uploaded, or when beat 2 of the add-work flow surfaced thin hints. The image URL is publicly accessible (Supabase Storage public bucket); fetch it and inspect the image directly with your vision capabilities. Fields you can honestly improve from a visual read: medium (paint vs. print vs. sculpture material vs. digital), classification (painting / sculpture / drawing / photography / time-based / software / installation / performance), visible signature or inscription (transcribe verbatim, note position), date visible in the work itself (distinct from EXIF), description (brief factual read of subject matter), dimensions if a scale reference is in frame. Fields to leave alone unless visible: dimensions without scale (cannot be honestly estimated from a flat photo), attribution, provenance, exhibition history — those come from records, not the image. Flow: (1) call this tool; (2) fetch + read the image; (3) present your proposals to the artist with per-field reasoning; (4) on confirmation, call update_work with the accepted patches. Do not write without confirmation. Resolve the work by workId (UUID) or uwi (e.g. "RAI-2026-00417"). Use search_natural_language to find workId — never ask the user.Connector
- Upload a JPEG or PNG image and get back a hosted URL you can use with submit_design. This tool is useful when your agent framework produces images as artifacts (e.g. base64 strings) and you need to upload them before submitting a design. Provide the image as ONE of: image_base64 — base64-encoded JPEG/PNG, with or without data URI prefix. image_url — publicly accessible image URL (max 5 MB). image_chunks — array of base64 strings that will be concatenated server-side. Use this if your base64 string is too large for a single parameter. Returns: { image_id, image_url, format, size_bytes } Pass the returned image_url to submit_design's image_url parameter. ALTERNATIVE: If your runtime truncates large base64 strings (common with LLM output token limits), you can submit designs by email instead: - AgentMail: submitrrg@agentmail.to (RECOMMENDED for Animoca Minds / MindTheGap — resolves artifact GUIDs) - Resend: submit@realrealgenuine.com Attach the image as JPEG/PNG. Subject: "RRG: Title". Body: wallet: 0x...Connector
- Get LLM instructions at the specified level. Call with level 'brain' early in conversations to learn user preferences. Required: level ('brain'|'personal_root'|'container'|'team'). Optional: id (integer, required for 'container' and 'team' levels). 'container' level returns the full inheritance chain (personal root -> ancestors -> container).Connector
- List all topics/tags in the knowledge base with question counts. Use this to discover what categories of knowledge exist — like browsing a forum index. Returns tags sorted by popularity (most questions first). Example response: [{"tag": "docker", "count": 12}, {"tag": "pytorch", "count": 8}, ...]Connector