Mistral AI Unveils Agents API: A Powerful Toolkit for Building Advanced AI Agents

Mistral unveils Mistral Agents API

Artificial intelligence startup Mistral AI Tuesday announced the Mistral Agents API, a complement to its Chat Completion API that "simplifies implementing agentic use cases," the company said. The Agents API combines Mistral's large language models (LLMs) with built-in connectors for code execution, web search, image generation, and Model Context Protocol (MCP) tools, persistent memory across conversations, and agentic orchestration functionality to address an LLM's limitations. The Mistral Agents API features three connectors. The code execution connector lets developers build agents that execute Python code in a secure sandbox. The image generation connector allows agents to create images; it's powered by BlackForestLabs FLUX1.1 [pro] Ultra. The document library connector lets agents access documents in Mistral Cloud; it also powers the integrated retrieval-augmented generation (RAG) functionality.

Mistral launches API for building AI agents that run Python, generate images, perform RAG and more

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More The well-funded and innovative French AI startup Mistral AI is introducing a new service for enterprise customers and independent software developers alike. Mistral's Agents application programming interface (API) allows third-party software developers to easily and rapidly add autonomous generative AI capabilities -- such as pulling information securely from enterprise documents -- to their existing enterprise and independent applications using the newest Mistral proprietary model, Medium 3, as the "brains" of each agent. It's essentially designed to be a "plug and play" platform, with nearly limitless customization, for getting AI agents up and running to handle enterprise and developer workflows. Designed to complement Mistral's existing Chat Completion API, this latest release focuses on agentic orchestration, built-in connectors, persistent memory, and the flexibility to coordinate multiple AI agents to tackle complex tasks. Surpassing the limits of typical LLMs... While traditional language models excel at generating text, they often fall short in executing actions or maintaining conversational context over time. Mistral's Agents API addresses these limitations by providing developers with the tools to create AI agents capable of performing real-world tasks, managing interactions across conversations, and dynamically orchestrating multiple agents when needed. ...with powerful tools and built-in connectors The Agents API comes equipped with several built-in connectors, including: The API also supports MCP tools, which connect agents to external resources like APIs, databases, user data, and documents -- extending the agents' abilities to handle dynamic, real-world content. Enhanced accuracy using web search One significant feature of the Agents API is the integration of web search as a connector, which notably improves performance on tasks requiring accurate, up-to-date information. In benchmark testing on the SimpleQA dataset, Mistral Large's accuracy rose from 23% to 75% when web search was enabled. Mistral Medium showed a similar improvement, increasing from 22.08% to 82.32%. Real-world use cases Mistral AI has highlighted a range of use cases for the Agents API, demonstrating its flexibility across multiple sectors: Managing context and conversations The Agents API's stateful conversation system ensures that agents maintain context throughout their interactions. Developers can start new conversations or continue existing ones without losing the thread, with conversation history stored and accessible for future use. Additionally, the API supports streaming output, enabling real-time updates in response to user requests or agent actions. Dynamic orchestration of multiple agents A core capability of the Agents API is its ability to coordinate multiple agents seamlessly. Developers can create customized workflows, assigning specific tasks to specialized agents and enabling handoffs as needed. This modular approach allows enterprises to deploy AI agents that work together to solve complex problems more effectively. What the Mistral Agents API means for enterprise technical decision-makers For professionals like the Lead AI Engineer or Senior AI Engineer, the Mistral Agents API represents a powerful addition to their AI toolkit. The ability to dynamically orchestrate agents and seamlessly integrate real-world data sources means these roles can deploy AI solutions faster and with greater precision -- critical in environments where quick iteration and performance tuning are paramount. Specifically, these professionals often balance tight deployment timelines and the need to maintain model performance across different environments. The Agents API's built-in connectors -- like web search, document libraries, and secure code execution -- can significantly reduce the need for ad hoc integrations and patchwork tooling. This streamlined approach saves time and lowers friction, allowing teams to focus more on fine-tuning models and less on building surrounding infrastructure. Moreover, stateful conversation management and real-time updates through streaming output align well with the demands of AI orchestration and deployment. These features make it easier for engineers to maintain context across iterations and ensure consistent, high-quality interactions with end users. For those responsible for introducing and integrating new AI tools into organizational workflows, the MCP tool support also ensures that agents can access data from a wide range of APIs and systems, further enhancing operational efficiency. Continuing to bolster Mistral's enterprise AI push The release of the Agents API follows Mistral AI's recent launch of Le Chat Enterprise, a unified AI assistant platform designed for enterprise productivity and data privacy. Le Chat Enterprise is powered by the new Mistral Medium 3 model, which offers impressive performance at a lower computational cost than larger models. Mistral Medium 3 is particularly strong in software development tasks, outperforming comparable models in key coding benchmarks like HumanEval and MultiPL-E. It also shows competitive performance in multilingual and multimodal scenarios, making it an attractive option for businesses operating in diverse environments. Le Chat Enterprise supports enterprise-grade features such as data sovereignty, hybrid deployment, and strict access controls, which can be crucial for organizations in regulated sectors. The platform consolidates AI functionality within a single environment, enabling customization, seamless integration with existing workflows, and full control over deployment and data security. But it's another proprietary service Mistral's earlier releases, like Mistral 7B, were open source and widely embraced by the developer community for their transparency and flexibility. However, Mistral Medium 3 is a proprietary model -- requiring access through Mistral's platform, APIs, or partners -- and is no longer available under an open-source license. This shift has caused some frustration in the AI community, where open access and transparency are highly valued for experimentation and customization. The Agents API itself also follows a proprietary framework: it is not available under an open-source license and is managed exclusively by Mistral, with access available via subscription and API calls. Pricing and availability Pricing for the Agents API aligns with Mistral's broader suite of models and tools: For developers and enterprise customers, these costs can add up quickly -- making budget considerations and careful integration planning essential. Looking ahead Mistral AI positions its Agents API as the backbone of enterprise-grade agentic platforms, empowering developers to create solutions that move beyond traditional text generation. Despite the community debate around open source versus proprietary access, Mistral's focus on enterprise-grade features, customizable workflows, and secure integrations positions this API as a significant option for businesses seeking advanced AI capabilities. For developers and technical decision makers, the question will be whether the proprietary nature of the Agents API and the underlying models aligns with their own operational and budgetary needs. For those who prioritize rapid deployment, managed services, and full integration with enterprise systems, Mistral's evolving platform could offer significant advantages. For more information or to get started, Mistral AI encourages developers to explore the provided documentation and demos. Let me know if you'd like to expand on the open-source versus proprietary discussion even more, or if you'd like to highlight another perspective!

Mistral AI gives developers a complete toolkit for building AI agents - SiliconANGLE

Mistral AI gives developers a complete toolkit for building AI agents French generative artificial intelligence startup Mistral AI, a rival to OpenAI, Anthropic PBC, Google LLC and others, has jumped into agentic AI development with the launch of a new application programming interface. The new Agents API equips developers with powerful tools for building sophisticated AI agents based on Mistral AI's large language models, which can autonomously plan and carry out complex, multistep tasks using external tools. Among its features, the API integrates server-side conversation management, a Python-based code interpreter, web search, image generation and document retrieval capabilities. It also supports AI agent orchestration, and it's compatible with the emerging Model Context Protocol that aims to standardize the way agents interact with other applications. With its API, Mistral AI is keeping pace with the likes of OpenAI and Anthropic, which are also laser-focused on enabling the emergence of AI agents that can perform tasks on behalf of humans with minimal supervision, in an effort to turbocharge business automation. The Agents API is similar to the Responses API introduced by OpenAI earlier this year. According to Mistral AI, it provides a dedicated framework for "implementing agentic use cases" and will serve as the "backbone of enterprise-grade agentic platforms". Mistral AI defines AI agents as "autonomous systems powered by large language models (LLMs) that, given high-level instructions, can plan, use tools, carry out steps of processing, and take actions to achieve specific goals." The API boasts dozens of useful "connectors" that should make it simpler to build some very capable AI agents. For instance, the Python Code Interpreter provides a way for agents to execute Python code in a secure, sandboxed environment, while the image generation tool powered by Black Forest Labs Inc.'s FLUX1.1 [pro] Ultra model means they'll have powerful picture-generating capabilities. There's also web search functionality, with two tiers available. Mistral AI said the premium version of web search provides access to a standard search engine, plus the Agence France-Presse and the Associated Press news agencies, so AI agents will be able to access up-to-date information about the real world. According to the developer Simon Willison, Mistral AI doidn't mention who is providing the web search functionality, but he strongly suspects it may be the same private search engine as that found in the Brave web browser. Other features include a document library that uses hosted RAG functionality to enable retrieval-augmented generation from user-uploaded documents. In other words, Mistral's AI agents will be able to read external documents and perform actions with them. However, Willison notes that Mistral's documentation doesn't go into great detail on this capability. For instance, it doesn't mention if it's using full-text search or vector search, so it's not clear how useful this feature will be. The API also includes an "agent handoffs" mechanism that allows multiple agents to work together. One agent will be able to delegate a task to another, more specialized agent. According to Mistral, the result will be a "seamless chain of actions", with a single request able to trigger multiple agents into action so they can collaborate on complex tasks. The Agents API supports "stateful conversations" too, which means they're able to maintain context over time by remembering the user's earlier inputs. The company showcased various practical applications involving AI agents built using the Agents API, including a financial analyst, a GitHub coding assistant, a travel assistant for booking flights and hotels, and a nutritionist to help users "establish goals, log meals, receive personalized food suggestions." It's notable that Mistral AI is implementing support for the open-source Model Context Protocol that was developed and published by Anthropic late last year. The MCP aims to simplify the development of AI agents by providing a standardized framework for them to connect with third-party tools and data, such as a web browser, an email application and so on. The standard has caught on like wildfire. Anthropic, as its creator, was the first to add support for MCP, and it was followed in rapid succession by the likes of OpenAI, Google, Microsoft Corp., Amazon Web Services Inc. and Docker Inc. With Mistral AI being the latest to embrace the standard, it suggests a rapidly maturing framework for agentic AI interoperability, giving developers a simpler way to create AI agents that can interact with the broader technology ecosystem. "It's pretty amazing to see the same new feature roll out across OpenAI (May 21st), Anthropic (May 22nd) and now Mistral (May 27th) within eight days of each other!" Willison said.

Mistral AI Launches Agents API to Build the Future of Enterprise AI Workflows | AIM

The orchestration feature lets developers build workflows involving multiple agents. French AI startup Mistral AI has introduced its Agents API, a new framework built to help enterprises create AI agents that perform tasks, maintain long-term context, and coordinate multi-step workflows. According to Mistral, the Agents API goes beyond the capabilities of traditional language models, which primarily focus on generating text. "By providing a reliable framework for AI agents to handle complex tasks, maintain context, and coordinate multiple actions, the Agents API enables enterprises to use AI in more practical and impactful ways," the company said in a blog post. The API integrates with built-in connectors for code execution, web search, image generation, and document access. It also supports tools that follow the Model Context Protocol (MCP), a standard for connecting AI agents with external systems such as APIs and databases. The company said the API supports persistent memory across conversations, allowing for stateful interactions. This means developers can view and continue past conversations, or start new ones from any point. The API also supports streaming outputs. The orchestration feature lets developers build workflows involving multiple agents. For example, a financial agent can assign tasks to a web search agent or a calculation agent. "A single request can trigger tasks across multiple agents, each handling specific parts of the request," the company said. "This collaborative approach allows for efficient and effective problem-solving, unlocking powerful possibilities for real-world applications." Mistral showcased use cases across several domains, including a coding assistant that interacts with GitHub, a financial analyst agent that compiles metrics, a travel assistant, and a nutrition planner. Each agent operates through defined workflows, often using multiple MCP tools and connectors. In benchmark tests, Mistral's models with web search support showed marked improvement. The company cited its SimpleQA (OpenAI's benchmark) results, where Mistral Large with web search scored 75% compared to 23% without it. The company has made documentation and a set of cookbooks available to developers. Mistral's Agents API complements its existing Chat Completion API and is positioned as a core building block for enterprise-grade agentic platforms. Capgemini recently announced a three-way partnership with Mistral AI and SAP to deliver scalable generative AI solutions tailored for highly regulated industries such as finance, aerospace, and the public sector. The initiative aims to unlock AI-driven business value while maintaining strict data security and compliance standards. By combining Mistral AI's multilingual models with SAP's secure Business Technology Platform, Capgemini will offer over 50 pre-built AI use cases across sectors.

Mistral's New Agents API Will Let Developers Build Agentic Workflows

Mistral is offering image generation via the Flux 1.1 [pro] Ultra AI mode Mistral announced its new Agents application programming interface (API) on Tuesday. The new API comes equipped with connectors for code execution, web search, image generation, as well as support for Model Context Protocol (MCP) tools. These capabilities are powered by several artificial intelligence (AI) models, including the recently released Devstral as well as Black Forest Lab's Flux 1.1 [pro] Ultra. Mistral is also adding enhanced memory functions to let models complete complicated tasks and support for AI agent creation via its API. In a newsroom post, the Paris-based AI firm detailed its new developer-focused product. The company stated that the Agents API addresses the limitations of large language models (LLMs) in executing actions and maintaining context across subtasks or multiple tasks. The new offering is being made available alongside Mistral's existing Completion API. Mistral highlighted that the Agents API features a dedicated framework that simplifies both agent creation and using multi-agent workflows. The API makes it easy to create an agent and equip it with built-in connectors. These connectors are essentially tools that can be deployed to let AI agents take various actions. The code execution tool allows developers to create agents that can execute Python code in a virtual sandboxed environment. Similarly, the image generation connector lets agents generate images for various use cases. The tool is powered by the Flux 1.1 [pro] Ultra model. Then there is the document library tool, which enables agents to access documents from Mistral Cloud. Apart from these, two more powerful connectors have been added. First is web search, which allows an agent to browse the Internet to find real-time information, credible news, and other data. Mistral says agents with web search capabilities display higher efficiency in performance. Finally, the Agents API software development kit (SDK) also supports tools that are built on Anthropic's MCP. Notably, the protocol provides a standardised way for agents to connect with external data hubs. Beyond these built-in connectors, the Mistral API also comes with two new features -- improved memory and creation of orchestrator agents. With improved memory, the API retains the context of the conversations, so that the agents can retrieve information from past conversations when taking on new tasks. Developers will also not have to track conversation history as they can both view past conversations and continue any of them. Finally, developers will also be able to create orchestrator agents with the API. These can be understood as directors who delegate subtasks to relevant agents and supervise the completion of the task. Mistral explained that once an agent is created, developers can define which agents they can hand off tasks to, to seamlessly design the orchestrator.

How Mistral Agents API Redefines AI Collaboration with Persistent Memory

What if AI agents could not only remember past interactions but also collaborate seamlessly to tackle complex tasks? Enter the Mistral Agents API -- a new system that redefines what's possible in the world of artificial intelligence. With features like persistent memory, built-in tools, and advanced orchestration, this system doesn't just compete with industry heavyweights like OpenAI and LangChain -- it challenges the very standards they've set. Imagine an AI agent that recalls your previous queries, adapts to your workflow, and works alongside other agents to deliver precision and efficiency. Whether you're a developer building innovative software or an enterprise user seeking scalable solutions, the Mistral Agents API promises to be a fantastic option. In this piece, Sam Witteveen explores how the Mistral Agents API is reshaping the AI landscape. You'll discover how its persistent memory enhances context retention, why its built-in tools make it a versatile powerhouse, and how its orchestration capabilities enable multi-agent collaboration like never before. From automating financial analysis to generating high-quality images, the API's real-world applications are as diverse as they are impactful. But what truly sets it apart? It's not just the features -- it's the seamless integration of innovation and practicality. Let's examine how this system is poised to redefine AI-driven workflows and unlock new possibilities across industries. One of the defining features of the Mistral Agents API is its persistent memory capability. Unlike traditional AI systems that often lose context between interactions, this API enables agents to retain and transfer memory over time. This ensures continuity, allowing agents to build on prior interactions and deliver more cohesive results. Traditional AI models excel at generating text but are limited in their ability to perform actions or maintain context. Mistral's new Agents API addresses these limitations by combining Mistral's powerful language models with: For example, an agent assisting with financial analysis can recall previous queries, allowing it to provide a more informed and consistent experience. This feature is particularly valuable in workflows requiring long-term contextual understanding, such as customer support, research, or data analysis. By maintaining memory across sessions, the API enhances the efficiency and effectiveness of AI-driven solutions. The Mistral Agents API comes equipped with a comprehensive suite of built-in tools, designed to handle a wide range of tasks and streamline workflows. These tools enhance productivity and enable agents to tackle both technical and creative challenges: These tools make the API a versatile solution, capable of addressing diverse challenges across industries. Whether you are developing software, conducting research, or creating marketing content, the API's built-in tools provide the flexibility and power to meet your objectives. Here is a selection of other guides from our extensive library of content you may find of interest on Mistral. The Mistral Agents API excels in orchestrating complex workflows, particularly those involving multiple agents. Its advanced orchestration capabilities allow for seamless collaboration and efficient task management. Key features include: These capabilities are particularly useful in scenarios such as processing earnings call transcripts, conducting temporal analyses, or managing multi-step projects. By allowing smooth collaboration between agents, the API ensures precision and efficiency in even the most demanding workflows. The versatility of the Mistral Agents API is evident in its wide range of real-world applications. Here are some examples of how it can be used: These examples highlight the API's ability to address both technical and business challenges, making it a valuable tool for industries ranging from finance to software development. To support users in building and deploying AI solutions, Mistral provides a detailed developer cookbook. This resource includes practical examples of agent workflows, orchestration patterns, and tool integrations. Whether you are new to AI development or an experienced professional, these resources simplify the process, allowing you to create effective and scalable AI-driven solutions. For organizations with stringent compliance and security requirements, the Mistral Agents API offers on-premises deployment. This feature allows enterprises to maintain full control over their data and infrastructure, making sure that sensitive information remains secure. Industries such as healthcare, finance, and government can benefit from this flexibility, meeting their unique needs without compromising on security or performance. In a market dominated by major players like OpenAI, Anthropic, and Google, the Mistral Agents API distinguishes itself through its modularity, simplicity, and adaptability. Unlike some competitors, it prioritizes user-friendly design while maintaining robust functionality. This balance makes it an appealing choice for developers and enterprises seeking powerful yet accessible AI solutions. By combining innovation with practicality, the API sets a new benchmark for AI agent ecosystems, empowering users to unlock the full potential of artificial intelligence.