Standardize how your AI models interact with your enterprise ecosystem using a comprehensive suite of connectors for MCP, A2A, industry-leading LLMs, and more. 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Standardize how your AI models interact with your enterprise ecosystem using a comprehensive suite of connectors for MCP, A2A, industry-leading LLMs, and more. Effortlessly bridge the gap between AI intelligence and your existing IT infrastructure to build secure, actionable agents at scale.
Eliminate the complexity of custom-coding AI integrations. MuleSoft AI connectors provide a unified interface for LLMs and Vector Stores, allowing developers to orchestrate, test, and deploy enterprise-grade agents
in a fraction of the time.
Ground AI in Enterprise Truth.
Seamlessly connect AI models to your existing systems. By bridging Salesforce and non-Salesforce data, MuleSoft ensures your agents have the real-time context necessary to provide accurate, hallucination-free responses.
Standardize Agent Communication.
Future-proof your AI strategy with support for emerging industry standards. Use the Model Context Protocol (MCP) and Agent-to-Agent (A2A) support to enable seamless interaction between agents and systems, forming a scalable foundation for a multi-agent evolution.
The Amazon Bedrock Connector
Integrate and orchestrate high-performing foundation models (FMs) from Amazon and leading AI companies. The Amazon Bedrock Connector allows you to easily build generative AI applications by connecting MuleSoft workflows to a wide range of models via a single connector. This enables developers to implement privacy-focused AI capabilities, such as automated content creation and complex data synthesis, while maintaining the security and scale of the AWS ecosystem.
Seamlessly integrate AI models and vector databases into your enterprise applications. Use the Inference Connector to access various large language models (LLMs) for text generation and summarization, and the Vector Connector to connect to external vector stores
. Together, they enable powerful Retrieval-Augmented Generation (RAG)
and semantic search by bridging the gap between your MuleSoft applications and your AI infrastructure.
Standardize how your agents interact with your existing tech stack. The MCP connector exposes MuleSoft APIs and integrations as tools for AI clients. By simplifying complex endpoints into manageable contexts, you enable agents to safely and efficiently browse, query, and take action across any system connected to MuleSoft.
Enable collaboration across your agentic ecosystem. The A2A connector implements industry-standard protocols that allow LLM agents
to discover and delegate tasks to one another. By facilitating secure communication and information exchange, this connector ensures that your agents can work together to solve complex, multi-step business problems.
Build and manage AI agents within Anypoint Platform with the security of the Einstein Trust Layer. This connector allows developers to leverage Salesforce’s trusted AI capabilities to monitor inputs, manage data privacy, and provide strict governance over AI operations, ensuring that every interaction is secure, reliable, and ethical.
Empower Salesforce Agentforce to take action in any external system. The MuleSoft Agentforce Connector streamlines the integration between Salesforce’s autonomous agents and your broader IT landscape via Anypoint Platform. This allows Agentforce to trigger workflows, update records, and retrieve data from legacy and third-party systems in real time.
Learn how to use NVIDIA NIM™ microservices with MuleSoft to securely connect enterprise data to dozens of GPU-accelerated LLM models for high-performance inference.
MuleSoft AI connectors are a specialized suite of integration tools designed to connect AI models, vector databases, and agentic frameworks (like MCP and A2A) to enterprise data and systems. They provide a standardized, no-code/low-code way to build AI-powered workflows and agents.
Yes. One of the primary benefits of the MuleSoft AI Connector portfolio is model agility. Because the connectors provide a unified abstraction layer, you can swap underlying LLM providers or models with minimal changes to your integration logic, preventing vendor lock-in.
While both facilitate communication, the MCP Connector focuses on Agent-to-System communication and letting an agent use a MuleSoft API as a tool. The A2A Connector focuses on Agent-to-Agent communication, allowing multiple specialized agents to coordinate, delegate tasks, and share information to complete complex workflows.
