Headwaters Inc., a company engaged in AI solutions business, has begun MCP integration for “SyncLect AI Agent,” which enables companies to build their own advanced AI agent platforms.
As many companies seek best practices for utilizing AI agents in recent years, there is a growing voice that the traditional single AI agent model has limitations in processing complex tasks and supporting customization.
Additionally, improving cost performance is a key issue in AI agent projects, and new approaches to solving this issue are needed.
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Headwaters has supported the development of a variety of AI agents, including contact center AI agents, station staff AI agents, migration AI agents, in-vehicle edge AI agents, and SLM AI agents, as well as text proofreading AI and translation AI.
One next-generation technology that is attracting attention for AI agents is “MCP (Model Context Protocol).” “MCP” is a system in which multiple autonomous agents work together, with each agent acting based on its own criteria and sharing information with other agents to accomplish complex tasks.
Previous AI agents were often specialized in specific tasks or data, making it difficult to integrate different information sources and tools. For example, an AI agent that creates emails based on data from a customer relationship management system (CRM) and an AI agent that updates tasks in a project management tool were typically treated as separate entities.
MCP has the potential to unify these siloed AI agents and enable them to work together on multiple tasks while sharing context, enabling more complex and intelligent workflows, such as referencing up-to-date customer data, creating personalized follow-up emails based on open tasks, and logging the results in CRM and project management tools.
SyncLect AI Agent, a microservices platform for multi-AI agents, enables faster AI agent construction by linking with MCP servers provided by companies such as Azure, Excel, OneNote, Teams, Cosmos DB, GitHub, Deep Research, Databricks, Elasticsearch, Dify, Stripe, Salesforce, etc. It also makes it possible to componentize custom AI agents using existing MCP servers and store and call them for multi-agent use.
SOURCE: PRTimes
