Connect Google Gemini to live Kafka data, securely.
CData Connect AI lets you plug any business application into any AI tool—like Kafka into Google Gemini—for live, trusted answers and actions with zero data copies.
Schema-aware MCP server
Google Gemini reads your full Kafka data model on connect
Cross-source MCP toolset
Join live Kafka with hundreds of other systems in one prompt
Bidirectional with identity passthrough
Google Gemini reads and writes under your access rules
Kafka:
Apache Kafka is an open-source distributed event streaming platform that is designed to handle high volumes of real-time data. It allows for the seamless integration of data streams from various sources and enables real-time processing and analysis. Kafka is highly scalable, fault-tolerant, and offers low-latency data processing capabilities.
Google Gemini:
Gemini is Google’s multimodal AI platform, and the Google Agent Development Kit (ADK) provides a stateful agent framework for building, customizing, and deploying Gemini-powered AI agents. These agents can reason, plan, and orchestrate workflows across your stack. With Connect AI, you can give Gemini/ADK agents live, governed business data from enterprise systems—without staging data or writing custom connectors for every tool.
Popular Google Gemini & Kafka integration use cases
- Goal-driven Gemini agents — Enable Gemini agents to plan and execute complex tasks grounded in real-time Kafka data.
- Stateful multi-step workflows — Build ADK agents that reason over Kafka data, orchestrate actions, and validate results with memory and control.
- Cross-system orchestration — Let Gemini agents coordinate actions across multiple systems while grounding decisions in governed Kafka data.
- Auditable agent activity — Expose only approved read/write operations on Kafka with full RBAC, masking, and logging for every tool call and response.
Learn more about CData Connect AI
Kafka to Google Gemini features
Access data where it lives right now. Ensure data is always live, always retains its metadata and semantics, and always protected by source system permissions.
Expose your data's metadata, relationships, and context so AI has real understanding of your business without recreating it on top of a warehouse.
Point-and-click connection setup that works for both queries and actions so you can set up integrations in minutes.
Pass through and edit role-based access control (RBAC) inherited from the source to users in AI and AI agents.
How It Works: Model Context Protocol (MCP)
Connect AI is first managed Model Context Protocol (MCP) platform for AI integration. Model Context Protocol (MCP) is an open standard for connecting AI assistants, agents, and automations to external tools and data.
With Connect AI's managed MCP platform, you can present your enterprise systems as standardized MCP tools and resources and call them directly from AI.
Instead of building and maintaining dozens of one-off MCP Servers, your AI simply calls one universal MCP URL from Connect AI, and gets governed access to live data from across your enterprise stack.
Getting Started is Easy:
- Configure data sources (Salesforce, NetSuite, Workday, SQL, Jira, etc.) in Connect AI.
- Create a 'Remote MCP' URL.
- Connect Google Gemini to your business data.
Get Started for Free
Access live Kafka data in other popular AI tools
No complicated data movement, ETL, or data integration required. Securely connect live Kafka data with any AI tool that supports MCP. Select your preferred tool below to learn more.
