Mistral AI API
★ Only Publicly Available OpenAPI DocumentAI/MLLanguage Modelsbearer71 EndpointsREST
For Agents
Generate text, embeddings, OCR, and classifications using Mistral models, and orchestrate stateful conversations and agents on La Plateforme. Supports fine-tuning, batch inference, and file uploads.
Use for: I want to generate a chat completion with Mistral Large, Create embeddings for a list of product descriptions, Run OCR on an uploaded invoice PDF, Set up a persistent Mistral agent with a custom system prompt
Not supported: Does not handle image generation, speech synthesis, or video — use for Mistral text, embeddings, OCR, and classifier workloads only.
Jentic publishes the only available OpenAPI specification for Mistral AI API, keeping it validated and agent-ready. The Mistral AI API exposes Mistral's open-weight and proprietary models for chat completion, fill-in-the-middle code generation, embeddings, content classifiers, OCR, agent and conversation orchestration, batch inference, and fine-tuning. It covers 71 endpoints across La Plateforme, including model listing, conversation memory, agent creation, file uploads for training and OCR, and asynchronous batch jobs for high-throughput workloads.
Install Jentic One Beta
Connect the Mistral AI API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the Mistral AI API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with Mistral AI API.
Generate chat completions with Mistral Large, Small, and Codestral models
Create embeddings for semantic search and retrieval pipelines
Run OCR jobs to extract structured text from PDFs and images
Build stateful conversations and persistent agents with tool calls
Submit batch inference jobs for high-volume offline scoring
Fine-tune base models on uploaded training files
Classify text content with prebuilt classifier endpoints
Use Cases
Patterns agents use Mistral AI API for, with concrete tasks.
★ RAG Pipeline Embeddings
Build retrieval-augmented generation systems by generating embeddings for a document corpus with Mistral's embeddings endpoint, then ranking results at query time. Mistral embeddings are competitive with closed-model alternatives at lower cost and run on EU-resident infrastructure for teams with data residency requirements.
Call POST /v1/embeddings with model mistral-embed and an array of 50 product descriptions, then store the returned vectors
Document OCR and Extraction
Upload a scanned PDF or image, then call the OCR endpoint to receive structured text with layout information. Useful for accounts payable automation, contract intake, and onboarding flows where receipts or identity documents arrive as images. Files are uploaded once and referenced by ID across calls.
Upload invoice.pdf via POST /v1/files, then call the OCR endpoint with the returned file ID and parse the structured text response
Stateful Conversational Agents
Create a Mistral agent with a system prompt and tool definitions, then drive multi-turn conversations through the conversations endpoints. State is persisted server-side so the client only sends the latest user message and the agent retains prior context, simplifying chatbot and copilot architectures.
Create an agent via POST /v1/agents with a customer-support system prompt, start a conversation, and append the next user message
Agent Discovery via Jentic
Discover and call Mistral operations through Jentic without hand-wiring the SDK. An agent searches for an intent like generate text with Mistral, Jentic returns the matching operation schema, and execution runs against api.mistral.ai with the bearer key handled by the Jentic vault.
Use Jentic to search for chat completion with Mistral, load the schema, and execute with model mistral-large-latest and a user message
Key Endpoints
71 endpoints — jentic publishes the only available openapi specification for mistral ai api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/v1/chat/completions
Generate a chat completion
POST
/v1/embeddings
Create vector embeddings
GET
/v1/models
List available models
POST
/v1/agents
Create a stateful agent
POST
/v1/conversations
Start a conversation
POST
/v1/files
Upload a file for OCR or fine-tuning
POST
/v1/chat/completions
Generate a chat completion
POST
/v1/embeddings
Create vector embeddings
GET
/v1/models
List available models
POST
/v1/agents
Create a stateful agent
POST
/v1/conversations
Start a conversation
POST
/v1/files
Upload a file for OCR or fine-tuning
Why Jentic?
Three things that make agents converge on Jentic-routed access.
Credential isolation
Mistral bearer keys are stored encrypted in the Jentic vault. Agents receive scoped execution rights and the Authorization header is injected at request time, so the raw key never enters agent context.
Intent-based discovery
Agents search Jentic with intents like generate text with mistral or create embeddings and Jentic returns the matching Mistral operation with input schema, model options, and a callable execution.
Time to first call
Direct Mistral integration: a few hours to wire the SDK, handle streaming, and add retries. Through Jentic: minutes — search, load, execute.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using Mistral AI API through Jentic.
Why is there no official OpenAPI spec for Mistral AI API?
Mistral AI does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call Mistral AI API via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.
What authentication does the Mistral AI API use?
The Mistral AI API uses bearer token authentication. Pass your La Plateforme API key in the Authorization header as Bearer your-key. Through Jentic the key is stored in the credential vault and injected at execution so agent code never holds the secret directly.
Can I run OCR on documents with the Mistral API?
Yes. Upload the file via POST /v1/files with purpose ocr, then call the OCR endpoint referencing the returned file ID. The response includes extracted text with layout structure suitable for downstream parsing.
What are the rate limits for the Mistral AI API?
Rate limits depend on your La Plateforme tier and the specific endpoint family. Chat completions, embeddings, and batch jobs each have separate quotas. Check your account dashboard at console.mistral.ai for the current numeric limits before running large workloads.
How do I fine-tune a Mistral model through Jentic?
Search Jentic for create fine tuning job, upload your training file via the files endpoint, then execute the fine-tuning operation with the file ID and base model. Job status can be polled through the same Jentic flow until the model is ready.
Does the Mistral API support persistent conversations?
Yes. The /v1/conversations endpoints store message history server-side. Create a conversation, append messages, and retrieve history without resending the entire transcript on each turn.
GET STARTED