Mistral AI API

Name: Mistral AI API
Brand: Mistral AI API
Availability: InStock

★ 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.

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.

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 | sh

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 instance

Jentic 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

GET STARTED

Start building with Mistral AI API

Explore with Jentic

View OpenAPI Document

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 your Jentic One instance.

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

Why Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Your Mistral bearer key is stored once, encrypted, by your own Jentic One instance and injected into the Authorization header at execution time. It never enters the agent's prompt, logs, or context.

Intent-based discovery

Agents search Jentic by intent such as 'generate text with Mistral' or 'create embeddings', and Jentic returns the matching Mistral operation with its input schema and model options so the agent calls the right endpoint without browsing the reference docs.

Time to first call

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 with Jentic One, the self-hosted execution layer.

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.

Can I limit what my agent is allowed to do with the Mistral AI API?

Yes. Because you run Jentic One yourself, you decide which Mistral operations the agent may call, so you can allow only chat completions and embeddings while leaving out everything else. Mistral's chat, embeddings, and agent endpoints take the model and payload in the request body rather than a URL path resource, so scoping happens at the operation level rather than by resource path. Higher-impact operations such as uploading files or creating persistent agents are included only if you explicitly add them, and your stored bearer key is injected at execution time under those same rules.

Mistral AI API

Connect the Mistral AI API to your agent

Capabilities

Start building with Mistral AI API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs