[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-composio-openai-automation":3,"mdc-veqrkm-key":52,"related-org-composio-openai-automation":557,"related-repo-composio-openai-automation":703},{"slug":4,"name":5,"fn":6,"description":7,"org":8,"tags":13,"stars":27,"repoUrl":28,"updatedAt":29,"license":30,"forks":31,"topics":32,"repo":47,"sourceUrl":50,"mdContent":51},"openai-automation","OpenAI Automation","automate OpenAI API operations","Automate OpenAI API operations -- generate responses with multimodal and structured output support, create embeddings, generate images, and list models via the Composio MCP integration.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},"composio","Composio","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fcomposio.png","ComposioHQ",[14,18,21,24],{"name":15,"slug":16,"type":17},"LLM","llm","tag",{"name":19,"slug":20,"type":17},"Automation","automation",{"name":22,"slug":23,"type":17},"MCP","mcp",{"name":25,"slug":26,"type":17},"OpenAI","openai",67499,"https:\u002F\u002Fgithub.com\u002FComposioHQ\u002Fawesome-claude-skills","2026-07-15T05:50:17.593645",null,7603,[33,34,35,20,36,37,38,9,39,40,41,23,42,43,44,45,46],"agent-skills","ai-agents","antigravity","claude","claude-code","codex","cursor","developer-tools","gemini-cli","openai-codex","rube","saas","skill","workflow-automation",{"repoUrl":28,"stars":27,"forks":31,"topics":48,"description":49},[33,34,35,20,36,37,38,9,39,40,41,23,42,43,44,45,46],"A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows","https:\u002F\u002Fgithub.com\u002FComposioHQ\u002Fawesome-claude-skills\u002Ftree\u002FHEAD\u002Fcomposio-skills\u002Fopenai-automation","---\nname: OpenAI Automation\ndescription: \"Automate OpenAI API operations -- generate responses with multimodal and structured output support, create embeddings, generate images, and list models via the Composio MCP integration.\"\nrequires:\n  mcp:\n    - rube\n---\n\n# OpenAI Automation\n\nAutomate your OpenAI API workflows -- generate text with the Responses API (including multimodal image+text inputs and structured JSON outputs), create embeddings for search and clustering, generate images with DALL-E and GPT Image models, and list available models.\n\n**Toolkit docs:** [composio.dev\u002Ftoolkits\u002Fopenai](https:\u002F\u002Fcomposio.dev\u002Ftoolkits\u002Fopenai)\n\n---\n\n## Setup\n\n1. Add the Composio MCP server to your client: `https:\u002F\u002Frube.app\u002Fmcp`\n2. Connect your OpenAI account when prompted (API key authentication)\n3. Start using the workflows below\n\n---\n\n## Core Workflows\n\n### 1. Generate a Response (Text, Multimodal, Structured)\n\nUse `OPENAI_CREATE_RESPONSE` for one-shot model responses including text, image analysis, OCR, and structured JSON outputs.\n\n```\nTool: OPENAI_CREATE_RESPONSE\nInputs:\n  - model: string (required) -- e.g., \"gpt-5\", \"gpt-4o\", \"o3-mini\"\n  - input: string | array (required)\n    Simple: \"Explain quantum computing\"\n    Multimodal: [\n      { role: \"user\", content: [\n        { type: \"input_text\", text: \"What is in this image?\" },\n        { type: \"input_image\", image_url: { url: \"https:\u002F\u002F...\" } }\n      ]}\n    ]\n  - temperature: number (0-2, optional -- not supported with reasoning models)\n  - max_output_tokens: integer (optional)\n  - reasoning: { effort: \"none\" | \"minimal\" | \"low\" | \"medium\" | \"high\" }\n  - text: object (structured output config)\n    - format: { type: \"json_schema\", name: \"...\", schema: {...}, strict: true }\n  - tools: array (function, code_interpreter, file_search, web_search)\n  - tool_choice: \"auto\" | \"none\" | \"required\" | { type: \"function\", function: { name: \"...\" } }\n  - store: boolean (false to opt out of model distillation)\n  - stream: boolean\n```\n\n**Structured output example:** Set `text.format` to `{ type: \"json_schema\", name: \"person\", schema: { type: \"object\", properties: { name: { type: \"string\" }, age: { type: \"integer\" } }, required: [\"name\", \"age\"], additionalProperties: false }, strict: true }`.\n\n### 2. Create Embeddings\n\nUse `OPENAI_CREATE_EMBEDDINGS` for vector search, clustering, recommendations, and RAG pipelines.\n\n```\nTool: OPENAI_CREATE_EMBEDDINGS\nInputs:\n  - input: string | string[] | int[] | int[][] (required) -- max 8192 tokens, max 2048 items\n  - model: string (required) -- \"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"\n  - dimensions: integer (optional, only for text-embedding-3 and later)\n  - encoding_format: \"float\" | \"base64\" (default \"float\")\n  - user: string (optional, end-user ID for abuse monitoring)\n```\n\n### 3. Generate Images\n\nUse `OPENAI_CREATE_IMAGE` to create images from text prompts using GPT Image or DALL-E models.\n\n```\nTool: OPENAI_CREATE_IMAGE\nInputs:\n  - model: string (required) -- \"gpt-image-1\", \"gpt-image-1.5\", \"dall-e-3\", \"dall-e-2\"\n  - prompt: string (required) -- max 32000 chars (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2)\n  - size: \"1024x1024\" | \"1536x1024\" | \"1024x1536\" | \"auto\" | \"256x256\" | \"512x512\" | \"1792x1024\" | \"1024x1792\"\n  - quality: \"standard\" | \"hd\" | \"auto\" | \"high\" | \"medium\" | \"low\"\n  - n: integer (1-10; DALL-E 3 supports n=1 only)\n  - background: \"transparent\" | \"opaque\" | \"auto\" (GPT Image models only)\n  - style: \"vivid\" | \"natural\" (DALL-E 3 only)\n  - user: string (optional)\n```\n\n### 4. List Available Models\n\nUse `OPENAI_LIST_MODELS` to discover which models are accessible with your API key.\n\n```\nTool: OPENAI_LIST_MODELS\nInputs: (none)\n```\n\n---\n\n## Known Pitfalls\n\n| Pitfall | Detail |\n|---------|--------|\n| DALL-E deprecation | DALL-E 2 and DALL-E 3 are deprecated and will stop being supported on 05\u002F12\u002F2026. Prefer GPT Image models. |\n| DALL-E 3 single image only | `OPENAI_CREATE_IMAGE` with DALL-E 3 only supports `n=1`. Use GPT Image models or DALL-E 2 for multiple images. |\n| Token limits for embeddings | Input must not exceed 8192 tokens per item and 2048 items per batch for embedding models. |\n| Reasoning model restrictions | `temperature` and `top_p` are not supported with reasoning models (o3-mini, etc.). Use `reasoning.effort` instead. |\n| Structured output strict mode | When `strict: true` in json_schema format, ALL schema properties must be listed in the `required` array. |\n| Prompt length varies by model | Image prompt max lengths differ: 32000 (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2). |\n\n---\n\n## Quick Reference\n\n| Tool Slug | Description |\n|-----------|-------------|\n| `OPENAI_CREATE_RESPONSE` | Generate text\u002Fmultimodal responses with structured output support |\n| `OPENAI_CREATE_EMBEDDINGS` | Create text embeddings for search, clustering, and RAG |\n| `OPENAI_CREATE_IMAGE` | Generate images from text prompts |\n| `OPENAI_LIST_MODELS` | List all models available to your API key |\n\n---\n\n*Powered by [Composio](https:\u002F\u002Fcomposio.dev)*\n",{"data":53,"body":56},{"name":5,"description":7,"requires":54},{"mcp":55},[43],{"type":57,"children":58},"root",[59,66,72,92,96,103,130,133,139,146,159,171,197,203,215,224,230,242,251,257,269,278,281,287,444,447,453,539,542],{"type":60,"tag":61,"props":62,"children":63},"element","h1",{"id":4},[64],{"type":65,"value":5},"text",{"type":60,"tag":67,"props":68,"children":69},"p",{},[70],{"type":65,"value":71},"Automate your OpenAI API workflows -- generate text with the Responses API (including multimodal image+text inputs and structured JSON outputs), create embeddings for search and clustering, generate images with DALL-E and GPT Image models, and list available models.",{"type":60,"tag":67,"props":73,"children":74},{},[75,81,83],{"type":60,"tag":76,"props":77,"children":78},"strong",{},[79],{"type":65,"value":80},"Toolkit docs:",{"type":65,"value":82}," ",{"type":60,"tag":84,"props":85,"children":89},"a",{"href":86,"rel":87},"https:\u002F\u002Fcomposio.dev\u002Ftoolkits\u002Fopenai",[88],"nofollow",[90],{"type":65,"value":91},"composio.dev\u002Ftoolkits\u002Fopenai",{"type":60,"tag":93,"props":94,"children":95},"hr",{},[],{"type":60,"tag":97,"props":98,"children":100},"h2",{"id":99},"setup",[101],{"type":65,"value":102},"Setup",{"type":60,"tag":104,"props":105,"children":106},"ol",{},[107,120,125],{"type":60,"tag":108,"props":109,"children":110},"li",{},[111,113],{"type":65,"value":112},"Add the Composio MCP server to your client: ",{"type":60,"tag":114,"props":115,"children":117},"code",{"className":116},[],[118],{"type":65,"value":119},"https:\u002F\u002Frube.app\u002Fmcp",{"type":60,"tag":108,"props":121,"children":122},{},[123],{"type":65,"value":124},"Connect your OpenAI account when prompted (API key authentication)",{"type":60,"tag":108,"props":126,"children":127},{},[128],{"type":65,"value":129},"Start using the workflows below",{"type":60,"tag":93,"props":131,"children":132},{},[],{"type":60,"tag":97,"props":134,"children":136},{"id":135},"core-workflows",[137],{"type":65,"value":138},"Core Workflows",{"type":60,"tag":140,"props":141,"children":143},"h3",{"id":142},"_1-generate-a-response-text-multimodal-structured",[144],{"type":65,"value":145},"1. Generate a Response (Text, Multimodal, Structured)",{"type":60,"tag":67,"props":147,"children":148},{},[149,151,157],{"type":65,"value":150},"Use ",{"type":60,"tag":114,"props":152,"children":154},{"className":153},[],[155],{"type":65,"value":156},"OPENAI_CREATE_RESPONSE",{"type":65,"value":158}," for one-shot model responses including text, image analysis, OCR, and structured JSON outputs.",{"type":60,"tag":160,"props":161,"children":165},"pre",{"className":162,"code":164,"language":65},[163],"language-text","Tool: OPENAI_CREATE_RESPONSE\nInputs:\n  - model: string (required) -- e.g., \"gpt-5\", \"gpt-4o\", \"o3-mini\"\n  - input: string | array (required)\n    Simple: \"Explain quantum computing\"\n    Multimodal: [\n      { role: \"user\", content: [\n        { type: \"input_text\", text: \"What is in this image?\" },\n        { type: \"input_image\", image_url: { url: \"https:\u002F\u002F...\" } }\n      ]}\n    ]\n  - temperature: number (0-2, optional -- not supported with reasoning models)\n  - max_output_tokens: integer (optional)\n  - reasoning: { effort: \"none\" | \"minimal\" | \"low\" | \"medium\" | \"high\" }\n  - text: object (structured output config)\n    - format: { type: \"json_schema\", name: \"...\", schema: {...}, strict: true }\n  - tools: array (function, code_interpreter, file_search, web_search)\n  - tool_choice: \"auto\" | \"none\" | \"required\" | { type: \"function\", function: { name: \"...\" } }\n  - store: boolean (false to opt out of model distillation)\n  - stream: boolean\n",[166],{"type":60,"tag":114,"props":167,"children":169},{"__ignoreMap":168},"",[170],{"type":65,"value":164},{"type":60,"tag":67,"props":172,"children":173},{},[174,179,181,187,189,195],{"type":60,"tag":76,"props":175,"children":176},{},[177],{"type":65,"value":178},"Structured output example:",{"type":65,"value":180}," Set ",{"type":60,"tag":114,"props":182,"children":184},{"className":183},[],[185],{"type":65,"value":186},"text.format",{"type":65,"value":188}," to ",{"type":60,"tag":114,"props":190,"children":192},{"className":191},[],[193],{"type":65,"value":194},"{ type: \"json_schema\", name: \"person\", schema: { type: \"object\", properties: { name: { type: \"string\" }, age: { type: \"integer\" } }, required: [\"name\", \"age\"], additionalProperties: false }, strict: true }",{"type":65,"value":196},".",{"type":60,"tag":140,"props":198,"children":200},{"id":199},"_2-create-embeddings",[201],{"type":65,"value":202},"2. Create Embeddings",{"type":60,"tag":67,"props":204,"children":205},{},[206,207,213],{"type":65,"value":150},{"type":60,"tag":114,"props":208,"children":210},{"className":209},[],[211],{"type":65,"value":212},"OPENAI_CREATE_EMBEDDINGS",{"type":65,"value":214}," for vector search, clustering, recommendations, and RAG pipelines.",{"type":60,"tag":160,"props":216,"children":219},{"className":217,"code":218,"language":65},[163],"Tool: OPENAI_CREATE_EMBEDDINGS\nInputs:\n  - input: string | string[] | int[] | int[][] (required) -- max 8192 tokens, max 2048 items\n  - model: string (required) -- \"text-embedding-3-small\", \"text-embedding-3-large\", \"text-embedding-ada-002\"\n  - dimensions: integer (optional, only for text-embedding-3 and later)\n  - encoding_format: \"float\" | \"base64\" (default \"float\")\n  - user: string (optional, end-user ID for abuse monitoring)\n",[220],{"type":60,"tag":114,"props":221,"children":222},{"__ignoreMap":168},[223],{"type":65,"value":218},{"type":60,"tag":140,"props":225,"children":227},{"id":226},"_3-generate-images",[228],{"type":65,"value":229},"3. Generate Images",{"type":60,"tag":67,"props":231,"children":232},{},[233,234,240],{"type":65,"value":150},{"type":60,"tag":114,"props":235,"children":237},{"className":236},[],[238],{"type":65,"value":239},"OPENAI_CREATE_IMAGE",{"type":65,"value":241}," to create images from text prompts using GPT Image or DALL-E models.",{"type":60,"tag":160,"props":243,"children":246},{"className":244,"code":245,"language":65},[163],"Tool: OPENAI_CREATE_IMAGE\nInputs:\n  - model: string (required) -- \"gpt-image-1\", \"gpt-image-1.5\", \"dall-e-3\", \"dall-e-2\"\n  - prompt: string (required) -- max 32000 chars (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2)\n  - size: \"1024x1024\" | \"1536x1024\" | \"1024x1536\" | \"auto\" | \"256x256\" | \"512x512\" | \"1792x1024\" | \"1024x1792\"\n  - quality: \"standard\" | \"hd\" | \"auto\" | \"high\" | \"medium\" | \"low\"\n  - n: integer (1-10; DALL-E 3 supports n=1 only)\n  - background: \"transparent\" | \"opaque\" | \"auto\" (GPT Image models only)\n  - style: \"vivid\" | \"natural\" (DALL-E 3 only)\n  - user: string (optional)\n",[247],{"type":60,"tag":114,"props":248,"children":249},{"__ignoreMap":168},[250],{"type":65,"value":245},{"type":60,"tag":140,"props":252,"children":254},{"id":253},"_4-list-available-models",[255],{"type":65,"value":256},"4. List Available Models",{"type":60,"tag":67,"props":258,"children":259},{},[260,261,267],{"type":65,"value":150},{"type":60,"tag":114,"props":262,"children":264},{"className":263},[],[265],{"type":65,"value":266},"OPENAI_LIST_MODELS",{"type":65,"value":268}," to discover which models are accessible with your API key.",{"type":60,"tag":160,"props":270,"children":273},{"className":271,"code":272,"language":65},[163],"Tool: OPENAI_LIST_MODELS\nInputs: (none)\n",[274],{"type":60,"tag":114,"props":275,"children":276},{"__ignoreMap":168},[277],{"type":65,"value":272},{"type":60,"tag":93,"props":279,"children":280},{},[],{"type":60,"tag":97,"props":282,"children":284},{"id":283},"known-pitfalls",[285],{"type":65,"value":286},"Known Pitfalls",{"type":60,"tag":288,"props":289,"children":290},"table",{},[291,310],{"type":60,"tag":292,"props":293,"children":294},"thead",{},[295],{"type":60,"tag":296,"props":297,"children":298},"tr",{},[299,305],{"type":60,"tag":300,"props":301,"children":302},"th",{},[303],{"type":65,"value":304},"Pitfall",{"type":60,"tag":300,"props":306,"children":307},{},[308],{"type":65,"value":309},"Detail",{"type":60,"tag":311,"props":312,"children":313},"tbody",{},[314,328,354,367,402,431],{"type":60,"tag":296,"props":315,"children":316},{},[317,323],{"type":60,"tag":318,"props":319,"children":320},"td",{},[321],{"type":65,"value":322},"DALL-E deprecation",{"type":60,"tag":318,"props":324,"children":325},{},[326],{"type":65,"value":327},"DALL-E 2 and DALL-E 3 are deprecated and will stop being supported on 05\u002F12\u002F2026. Prefer GPT Image models.",{"type":60,"tag":296,"props":329,"children":330},{},[331,336],{"type":60,"tag":318,"props":332,"children":333},{},[334],{"type":65,"value":335},"DALL-E 3 single image only",{"type":60,"tag":318,"props":337,"children":338},{},[339,344,346,352],{"type":60,"tag":114,"props":340,"children":342},{"className":341},[],[343],{"type":65,"value":239},{"type":65,"value":345}," with DALL-E 3 only supports ",{"type":60,"tag":114,"props":347,"children":349},{"className":348},[],[350],{"type":65,"value":351},"n=1",{"type":65,"value":353},". Use GPT Image models or DALL-E 2 for multiple images.",{"type":60,"tag":296,"props":355,"children":356},{},[357,362],{"type":60,"tag":318,"props":358,"children":359},{},[360],{"type":65,"value":361},"Token limits for embeddings",{"type":60,"tag":318,"props":363,"children":364},{},[365],{"type":65,"value":366},"Input must not exceed 8192 tokens per item and 2048 items per batch for embedding models.",{"type":60,"tag":296,"props":368,"children":369},{},[370,375],{"type":60,"tag":318,"props":371,"children":372},{},[373],{"type":65,"value":374},"Reasoning model restrictions",{"type":60,"tag":318,"props":376,"children":377},{},[378,384,386,392,394,400],{"type":60,"tag":114,"props":379,"children":381},{"className":380},[],[382],{"type":65,"value":383},"temperature",{"type":65,"value":385}," and ",{"type":60,"tag":114,"props":387,"children":389},{"className":388},[],[390],{"type":65,"value":391},"top_p",{"type":65,"value":393}," are not supported with reasoning models (o3-mini, etc.). Use ",{"type":60,"tag":114,"props":395,"children":397},{"className":396},[],[398],{"type":65,"value":399},"reasoning.effort",{"type":65,"value":401}," instead.",{"type":60,"tag":296,"props":403,"children":404},{},[405,410],{"type":60,"tag":318,"props":406,"children":407},{},[408],{"type":65,"value":409},"Structured output strict mode",{"type":60,"tag":318,"props":411,"children":412},{},[413,415,421,423,429],{"type":65,"value":414},"When ",{"type":60,"tag":114,"props":416,"children":418},{"className":417},[],[419],{"type":65,"value":420},"strict: true",{"type":65,"value":422}," in json_schema format, ALL schema properties must be listed in the ",{"type":60,"tag":114,"props":424,"children":426},{"className":425},[],[427],{"type":65,"value":428},"required",{"type":65,"value":430}," array.",{"type":60,"tag":296,"props":432,"children":433},{},[434,439],{"type":60,"tag":318,"props":435,"children":436},{},[437],{"type":65,"value":438},"Prompt length varies by model",{"type":60,"tag":318,"props":440,"children":441},{},[442],{"type":65,"value":443},"Image prompt max lengths differ: 32000 (GPT Image), 4000 (DALL-E 3), 1000 (DALL-E 2).",{"type":60,"tag":93,"props":445,"children":446},{},[],{"type":60,"tag":97,"props":448,"children":450},{"id":449},"quick-reference",[451],{"type":65,"value":452},"Quick Reference",{"type":60,"tag":288,"props":454,"children":455},{},[456,472],{"type":60,"tag":292,"props":457,"children":458},{},[459],{"type":60,"tag":296,"props":460,"children":461},{},[462,467],{"type":60,"tag":300,"props":463,"children":464},{},[465],{"type":65,"value":466},"Tool Slug",{"type":60,"tag":300,"props":468,"children":469},{},[470],{"type":65,"value":471},"Description",{"type":60,"tag":311,"props":473,"children":474},{},[475,491,507,523],{"type":60,"tag":296,"props":476,"children":477},{},[478,486],{"type":60,"tag":318,"props":479,"children":480},{},[481],{"type":60,"tag":114,"props":482,"children":484},{"className":483},[],[485],{"type":65,"value":156},{"type":60,"tag":318,"props":487,"children":488},{},[489],{"type":65,"value":490},"Generate text\u002Fmultimodal responses with structured output support",{"type":60,"tag":296,"props":492,"children":493},{},[494,502],{"type":60,"tag":318,"props":495,"children":496},{},[497],{"type":60,"tag":114,"props":498,"children":500},{"className":499},[],[501],{"type":65,"value":212},{"type":60,"tag":318,"props":503,"children":504},{},[505],{"type":65,"value":506},"Create text embeddings for search, clustering, and RAG",{"type":60,"tag":296,"props":508,"children":509},{},[510,518],{"type":60,"tag":318,"props":511,"children":512},{},[513],{"type":60,"tag":114,"props":514,"children":516},{"className":515},[],[517],{"type":65,"value":239},{"type":60,"tag":318,"props":519,"children":520},{},[521],{"type":65,"value":522},"Generate images from text prompts",{"type":60,"tag":296,"props":524,"children":525},{},[526,534],{"type":60,"tag":318,"props":527,"children":528},{},[529],{"type":60,"tag":114,"props":530,"children":532},{"className":531},[],[533],{"type":65,"value":266},{"type":60,"tag":318,"props":535,"children":536},{},[537],{"type":65,"value":538},"List all models available to your API key",{"type":60,"tag":93,"props":540,"children":541},{},[],{"type":60,"tag":67,"props":543,"children":544},{},[545],{"type":60,"tag":546,"props":547,"children":548},"em",{},[549,551],{"type":65,"value":550},"Powered by ",{"type":60,"tag":84,"props":552,"children":555},{"href":553,"rel":554},"https:\u002F\u002Fcomposio.dev",[88],[556],{"type":65,"value":10},{"items":558,"total":702},[559,573,589,598,608,620,629,642,656,669,682,692],{"slug":560,"name":561,"fn":562,"description":563,"org":564,"tags":565,"stars":27,"repoUrl":28,"updatedAt":572},"21risk-automation","-21risk-automation","automate 21risk compliance and safety tasks","Automate 21risk tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[566,567,568,569],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},{"name":570,"slug":571,"type":17},"Risk Assessment","risk-assessment","2026-07-15T05:54:18.790529",{"slug":574,"name":575,"fn":576,"description":577,"org":578,"tags":579,"stars":27,"repoUrl":28,"updatedAt":588},"2chat-automation","-2chat-automation","automate 2chat messaging tasks","Automate 2chat tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[580,581,584,585],{"name":19,"slug":20,"type":17},{"name":582,"slug":583,"type":17},"Communications","communications",{"name":22,"slug":23,"type":17},{"name":586,"slug":587,"type":17},"Messaging","messaging","2026-07-15T05:51:27.190332",{"slug":590,"name":590,"fn":591,"description":592,"org":593,"tags":594,"stars":27,"repoUrl":28,"updatedAt":597},"ably-automation","automate Ably tasks with Composio","Automate Ably tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[595,596],{"name":19,"slug":20,"type":17},{"name":22,"slug":23,"type":17},"2026-07-12T08:09:55.453088",{"slug":599,"name":599,"fn":600,"description":601,"org":602,"tags":603,"stars":27,"repoUrl":28,"updatedAt":607},"abstract-automation","automate Abstract tasks via Composio","Automate Abstract tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[604,605,606],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},"2026-07-15T05:45:16.470309",{"slug":609,"name":609,"fn":610,"description":611,"org":612,"tags":613,"stars":27,"repoUrl":28,"updatedAt":619},"abuselpdb-automation","automate Abuselpdb tasks via Composio","Automate Abuselpdb tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[614,615,616],{"name":19,"slug":20,"type":17},{"name":22,"slug":23,"type":17},{"name":617,"slug":618,"type":17},"Security","security","2026-07-15T05:56:20.013366",{"slug":621,"name":621,"fn":622,"description":623,"org":624,"tags":625,"stars":27,"repoUrl":28,"updatedAt":628},"abyssale-automation","automate Abyssale tasks via Composio","Automate Abyssale tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[626,627],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},"2026-07-15T05:54:50.762889",{"slug":630,"name":630,"fn":631,"description":632,"org":633,"tags":634,"stars":27,"repoUrl":28,"updatedAt":641},"accelo-automation","automate Accelo tasks via Composio","Automate Accelo tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[635,636,637,640],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":638,"slug":639,"type":17},"CRM","crm",{"name":22,"slug":23,"type":17},"2026-07-15T05:48:43.429136",{"slug":643,"name":643,"fn":644,"description":645,"org":646,"tags":647,"stars":27,"repoUrl":28,"updatedAt":655},"accredible-certificates-automation","automate Accredible certificate management","Automate Accredible Certificates tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[648,649,652],{"name":19,"slug":20,"type":17},{"name":650,"slug":651,"type":17},"Documents","documents",{"name":653,"slug":654,"type":17},"E-Signature","e-signature","2026-07-15T05:55:33.159639",{"slug":657,"name":657,"fn":658,"description":659,"org":660,"tags":661,"stars":27,"repoUrl":28,"updatedAt":668},"acculynx-automation","automate Acculynx construction management tasks","Automate Acculynx tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[662,663,664,665],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},{"name":666,"slug":667,"type":17},"Operations","operations","2026-07-15T05:58:48.059284",{"slug":670,"name":670,"fn":671,"description":672,"org":673,"tags":674,"stars":27,"repoUrl":28,"updatedAt":681},"active-campaign-automation","automate ActiveCampaign marketing and CRM tasks","Automate ActiveCampaign tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[675,676,677,678],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":638,"slug":639,"type":17},{"name":679,"slug":680,"type":17},"Email Marketing","email-marketing","2026-07-15T05:49:44.281711",{"slug":683,"name":683,"fn":684,"description":685,"org":686,"tags":687,"stars":27,"repoUrl":28,"updatedAt":691},"addresszen-automation","automate Addresszen address validation","Automate Addresszen tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[688,689,690],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},"2026-07-15T05:47:51.742515",{"slug":693,"name":693,"fn":694,"description":695,"org":696,"tags":697,"stars":27,"repoUrl":28,"updatedAt":701},"adobe-automation","automate Adobe tasks via Composio","Automate Adobe tasks via Rube MCP (Composio). Always search tools first for current schemas.",{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[698,699,700],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},"2026-07-15T05:45:05.303254",863,{"items":704,"total":748},[705,712,719,724,730,736,741],{"slug":560,"name":561,"fn":562,"description":563,"org":706,"tags":707,"stars":27,"repoUrl":28,"updatedAt":572},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[708,709,710,711],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},{"name":570,"slug":571,"type":17},{"slug":574,"name":575,"fn":576,"description":577,"org":713,"tags":714,"stars":27,"repoUrl":28,"updatedAt":588},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[715,716,717,718],{"name":19,"slug":20,"type":17},{"name":582,"slug":583,"type":17},{"name":22,"slug":23,"type":17},{"name":586,"slug":587,"type":17},{"slug":590,"name":590,"fn":591,"description":592,"org":720,"tags":721,"stars":27,"repoUrl":28,"updatedAt":597},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[722,723],{"name":19,"slug":20,"type":17},{"name":22,"slug":23,"type":17},{"slug":599,"name":599,"fn":600,"description":601,"org":725,"tags":726,"stars":27,"repoUrl":28,"updatedAt":607},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[727,728,729],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":22,"slug":23,"type":17},{"slug":609,"name":609,"fn":610,"description":611,"org":731,"tags":732,"stars":27,"repoUrl":28,"updatedAt":619},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[733,734,735],{"name":19,"slug":20,"type":17},{"name":22,"slug":23,"type":17},{"name":617,"slug":618,"type":17},{"slug":621,"name":621,"fn":622,"description":623,"org":737,"tags":738,"stars":27,"repoUrl":28,"updatedAt":628},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[739,740],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"slug":630,"name":630,"fn":631,"description":632,"org":742,"tags":743,"stars":27,"repoUrl":28,"updatedAt":641},{"slug":9,"name":10,"logoUrl":11,"githubOrg":12},[744,745,746,747],{"name":19,"slug":20,"type":17},{"name":10,"slug":9,"type":17},{"name":638,"slug":639,"type":17},{"name":22,"slug":23,"type":17},860]