Mistral AI API

Name: Mistral AI API 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.

Quickstart

Get started with Mistral AI API in minutes using your preferred integration method.

# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
  "jentic": {
    "url": "https://api.jentic.com/mcp",
    "auth": "oauth"
  }
}

# Then ask your agent:
"generate a chat completion with Mistral"

# → Jentic returns the GET /events tool with parameter schema, agent executes.

Capabilities

What an agent can do with Mistral AI API 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

GET STARTED

Start building with Mistral AI API API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI document for Mistral AI API, keeping it validated and agent-ready.

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.

Use Cases

Patterns agents use Mistral AI API 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

Why though 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.

Alternative

OpenAI API

GPT models, embeddings, and assistants from OpenAI

Choose OpenAI when the workflow needs GPT-4 class reasoning or US-based hosting; choose Mistral for EU residency or open-weight model access.

Alternative

Anthropic Messages API

Claude chat completions from Anthropic

Choose Claude when the workflow benefits from large context windows or Anthropic's safety tuning.

Complementary

Groq API

Low-latency inference for open-weight models including Mixtral

Use Groq alongside Mistral when latency-sensitive workloads need faster token throughput on similar open-weight architectures.

FAQs

Specific to using Mistral AI API 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.