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Elaichi Elaichi

artificial_intelligence

Z.ai

Connect Z.ai to Elaichi and hand every teammate a governed MCP endpoint — 14 tools ready to call from Claude, Cursor, or any MCP client, clamped by roles, restrictions, and an audit log.

Z.ai

AI tools

Z.ai tools for your AI agents

14 tools are ready to mint as an MCP endpoint the moment you connect Z.ai — governed by the same roles, restrictions, and audit log as everything else in Elaichi.

create_a_zai_chat_completion

Create a chat completion in zai that generates AI replies for a given conversation history. Supports multimodal inputs (text, image, video, file), function calling via tools, and both streaming and non-streaming output modes. Returns the completion object including id, model, choices, and usage. Required: model, messages.

create_a_zai_videos_generation

Create a video generation task in Z.AI using CogVideoX or Vidu models from a text prompt, image URL, or pair of first/last frame images. Supports text-to-video, image-to-video, and first/last-frame-to-video workflows. Returns the created generation task. Returns: model, id, request_id, task_status. Required: model.

get_single_zai_paas_async_result_by_id

Get the result of an asynchronous request in zai by task id. Returns the async result object with task-type-specific fields — either an AsyncVideoGenerationResponse or AsyncImageGenerationResponse depending on the originating task; consult the zai upstream docs for field-level details. Required: id.

create_a_zai_images_generation

Generate a high-quality image from a text prompt using GLM-Image series models in zai. Returns: url, id, created_at. Required: model, prompt.

create_a_zai_audio_transcription

Transcribe an audio file into text in zai using the GLM-ASR-2512 model, supporting multiple languages and optional real-time streaming output. Returns: id, created, request_id, model, text. Required: model.

create_a_zai_paas_tokenizer

Tokenize text input using a specified model in zai to calculate token counts, suitable for text length evaluation, model input estimation, dialogue context truncation, and cost calculation. Returns: created, id, request_id, usage. Required: model, messages.

create_a_zai_paas_layout_parsing

Submit a layout parsing request in zai using the GLM-OCR model to extract text content and layout information from a document image or PDF. Returns: id, created, model, md_results, layout_details, layout_visualization, data_info, usage, request_id, attributes. Required: model, file.

create_a_zai_paas_web_search

Perform a web search using the zai LLM-optimized Web Search API, which enhances intent recognition to return results better suited for large language model processing, including webpage titles, URLs, summaries, site names, and favicons. Returns: id, created, search_result.

create_a_zai_paas_reader

Create a web reader request in zai to read and parse the content of a specified URL. Returns: id, created, request_id, model, reader_result, url, content. Required: url.

create_a_zai_paas_file

Upload an auxiliary file (such as a glossary or terminology list) to zai to enhance translation accuracy and consistency. Returns the uploaded file record including id, object, bytes, filename, purpose, and created_at. Required: purpose, file. File size limit is 100 MB; accepted formats are pdf, doc, xlsx, ppt, txt, jpg, and png.

create_a_zai_agent

Create a zai agent task for one of three agent types: General Translation (multilingual text translation with auto-detection and glossary support), Popular Special Effects Videos (AI video generation from an image and prompt via a template), or GLM Slide/Poster (slide or poster generation from natural language instructions). Returns: id, agent_id, choices, usage, status, async_id.

create_a_zai_agents_async_result

Query the result of an asynchronous zai agent request. Returns: status, agent_id, async_id, choices, id, usage. Required: async_id.

create_a_zai_agents_conversation

Query conversation history for a zai slides_glm_agent (the only supported agent type). Returns id, agent_id, choices (with messages containing role and content, and finish_reason), and usage token statistics for synchronous responses, or status and async_id for asynchronous responses.

create_a_zai_async_images_generation

Create an async image generation job in zai using the GLM-Image model. Returns: model, id, request_id, task_status. Required: model, prompt.

How it works

From Z.ai account to governed MCP endpoint

Connect

Link a Z.ai account through Elaichi's hosted connect flow. Credentials are vaulted — nobody, including the AI, ever sees them.

Compose

The connection becomes a toolbox instantly. Curate which Z.ai tools are exposed, rename them, or freeze arguments.

Mint

Mint a personal MCP endpoint on that toolbox and paste it into Claude, Cursor, or any MCP client — governed by roles, restrictions, and audit logs.

Give every teammate a governed MCP server

Start a 14-day Gold trial — connect a product, curate a toolbox, and paste an endpoint into Claude or Cursor in minutes.