Mistral AI Automation
Helps your agent manage Mistral AI operations. It can handle files, documents, and build AI pipelines. Useful for those working with large language models.
What it does
This tool helps you manage and automate tasks with Mistral AI. You can upload files to train models, organize documents for the AI to use, check the progress of training jobs, and more.
When to use it
- ✓Uploading files to train a Mistral AI model.
- ✓Organizing documents so the AI can find and use them.
- ✓Checking the status of model training jobs.
Example of what to ask your AI
“Upload the file 'my_data.jsonl' to train an AI model.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You connect to your Mistral AI account and use specific commands to upload files, create document 'libraries', or check training progress. The tool handles the communication with Mistral AI.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add ComposioHQ/awesome-claude-skills --skill Mistral AI AutomationOr download just the file:
curl -L https://raw.githubusercontent.com/ComposioHQ/awesome-claude-skills/master/composio-skills/mistral-ai-automation/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Mistral AI Automation
Automate your Mistral AI workflows -- upload files for fine-tuning, batch processing, and OCR, manage document libraries for RAG-enabled agents, list and retrieve files, track fine-tuning jobs, and integrate Mistral AI into cross-app data pipelines.
Toolkit docs: composio.dev/toolkits/mistral_ai
Setup
- Add the Composio MCP server to your client:
https://rube.app/mcp - Connect your Mistral AI account when prompted (API key authentication)
- Start using the workflows below
Core Workflows
1. Upload Files to Mistral AI
Use MISTRAL_AI_UPLOAD_FILE to upload files for fine-tuning, batch processing, or OCR.
Tool: MISTRAL_AI_UPLOAD_FILE
Inputs:
- file: object (required)
- name: string -- destination filename (e.g., "training_data.jsonl")
- mimetype: string -- MIME type (e.g., "application/pdf", "application/jsonl")
- s3key: string -- S3 key of a previously downloaded/stored file
- purpose: "fine-tune" | "batch" | "ocr" (default "fine-tune")
Limits: Maximum file size is 512 MB. For fine-tuning, only .jsonl files are supported.
2. List and Retrieve Files
Use MISTRAL_AI_LIST_FILES to browse uploaded files with pagination, and MISTRAL_AI_RETRIEVE_FILE to get metadata for a specific file.
Tool: MISTRAL_AI_LIST_FILES
Inputs:
- limit: integer (optional, min 1)
- after: string (file ID cursor for next page)
- order: "asc" | "desc" (default "desc")
Tool: MISTRAL_AI_RETRIEVE_FILE
Inputs:
- file_id: string (required) -- UUID obtained from List Files
3. Create Document Libraries
Use MISTRAL_AI_CREATE_LIBRARY to group documents into libraries for use with RAG-enabled Mistral AI agents.
Tool: MISTRAL_AI_CREATE_LIBRARY
Inputs:
- name: string (required) -- e.g., "Project Documents"
- description: string (optional)
4. Upload Documents to a Library
Use MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT to add documents to a library for RAG retrieval by Mistral AI agents.
Tool: MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT
- Requires library_id and file details
- Call RUBE_GET_TOOL_SCHEMAS for full input schema before use
5. List Libraries and Download Files
Use MISTRAL_AI_LIST_LIBRARIES to discover available document libraries, and MISTRAL_AI_DOWNLOAD_FILE to retrieve file content.
Tool: MISTRAL_AI_LIST_LIBRARIES
- Lists all document libraries with metadata (id, name, document counts)
- Call RUBE_GET_TOOL_SCHEMAS for full input schema
Tool: MISTRAL_AI_DOWNLOAD_FILE
- Downloads raw binary content of a previously uploaded file
- Call RUBE_GET_TOOL_SCHEMAS for full input schema
6. Track Fine-Tuning Jobs
Use MISTRAL_AI_GET_FINE_TUNING_JOBS to list and filter fine-tuning jobs by model, status, and creation time.
Tool: MISTRAL_AI_GET_FINE_TUNING_JOBS
- Supports filtering by model, status, creation time, and W&B integration
- Call RUBE_GET_TOOL_SCHEMAS for full input schema
Known Pitfalls
| Pitfall | Detail |
|---|---|
| Fine-tune file format | Only .jsonl files are supported for fine-tuning uploads. Other formats will be rejected. |
| File size limit | Maximum upload size is 512 MB per file. |
| File object structure | MISTRAL_AI_UPLOAD_FILE requires an s3key referencing a previously stored file, not raw binary content. Use a download action first to stage files in S3. |
| Pagination cursors | MISTRAL_AI_LIST_FILES uses cursor-based pagination via the after parameter (file ID). Continue fetching until no more results are returned. |
| Library document processing | Uploaded library documents are processed asynchronously. They may not be immediately available for RAG queries after upload. |
| Schema references | Several tools (MISTRAL_AI_UPLOAD_LIBRARY_DOCUMENT, MISTRAL_AI_LIST_LIBRARIES, MISTRAL_AI_GET_FINE_TUNING_JOBS, MISTRAL_AI_DOWNLOAD_FILE) require calling RUBE_GET_TOOL_SCHEMAS to load full input schemas before execution. |
Quick Reference
| Tool Slug | Description |
|---|---|
MISTRAL_AI_UPLOAD_FILE |
Upload files for fine-tuning, batch processing, or OCR |
MISTRAL_AI_LIST_FILES |
List uploaded files with pagination |
MISTRAL_AI_RETRIEVE_FILE |
Get metadata for a specific file by ID |
MISTRAL_AI_DOWNLOAD_FILE |
Download content of an uploaded file |
MISTRAL_AI_CREATE_LIBRARY |
Create a document library for RAG |
…
FAQ
What is the maximum file size I can upload?
The maximum size per file is 512 MB.
Can I upload any file type to train a model?
No, for training models, only '.jsonl' files are accepted.
How does the AI find the documents I upload?
You can organize documents into 'libraries'. The AI can then access these libraries to find relevant information, especially for 'RAG' systems.
Details
Original description by the author
Automate Mistral AI operations -- manage files and libraries, upload documents for fine-tuning, batch processing, and OCR, track fine-tuning jobs, and build RAG pipelines via the Composio MCP integration.
Popularity
- GitHub stars
- 77k
- Ranking position
- #1354
- License
- —
- Updated
- 9/18/2026
Comments
- …
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