About mcp
mcp is an MCP server published by git+firebase in the Developer Tools category: a Genkit plugin that provides interoperability between Genkit and Model Context Protocol (MCP). Both client and server use cases are supported. It has been installed 0 times through Conduid.
Install
npx @genkit-ai/mcpclaude mcp add genkit -- npx -y @genkit-ai/mcpnpx -y @genkit-ai/mcpThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
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README

Genkit is an open-source framework for building full-stack AI-powered applications, built and used in production by Google's Firebase. It provides SDKs for multiple programming languages with varying levels of stability:
- JavaScript/TypeScript: Production-ready with full feature support
- Go: Production-ready with full feature support
- Python (Alpha): Early development with core functionality
It offers a unified interface for integrating AI models from providers like Google, OpenAI, Anthropic, Ollama, and more. Rapidly build and deploy production-ready chatbots, automations, and recommendation systems using streamlined APIs for multimodal content, structured outputs, tool calling, and agentic workflows.
Get started with just a few lines of code:
import { genkit } from 'genkit';
import { googleAI } from '@genkit-ai/google-genai';
const ai = genkit({ plugins: [googleAI()] });
const { text } = await ai.generate({
model: googleAI.model('gemini-2.5-flash'),
prompt: 'Why is Firebase awesome?'
});
Explore & build with Genkit
Play with AI sample apps, with visualizations of the Genkit code that powers them, at no cost to you.
Key capabilities
How does it work?
Genkit simplifies AI integration with an open-source SDK and unified APIs that work across various model providers and programming languages. It abstracts away complexity so you can focus on delivering great user experiences.
Some key features offered by Genkit include:
- Text and image generation
- Type-safe, structured data generation
- Tool calling
- Prompt templating
- Persisted chat interfaces
- AI workflows
- AI-powered data retrieval (RAG)
Genkit is designed for server-side deployment in multiple language environments, and also provides seamless client-side integration through dedicated helpers and client SDKs.
Implementation path
Get started
Development tools
Genkit provides a CLI and a local UI to streamline your AI development workflow.
CLI
The Genkit CLI includes commands for running and evaluating your Genkit functions (flows) and collecting telemetry and logs.
- Install:
npm install -g genkit-cli - Run a command, wrapped with telemetry, a interactive developer UI, etc:
genkit start -- <command to run your code>
Developer UI
The Genkit developer UI is a local interface for testing, debugging, and iterating on your AI application.
Key features:
- Run: Execute and experiment with Genkit flows, prompts, queries, and more in dedicated playgrounds.
- Inspect: Analyze detailed traces of past executions, including step-by-step breakdowns of complex flows.
- Evaluate: Review the results of evaluations run against your flows, including performance metrics and links to relevant traces.
Connect with us
- Follow us on X/Twitter – Get the latest news, updates, releases, tips and samples from the Genkit team.
- Join us on Discord – Get help, share ideas, and chat with other developers.
- Contribute on GitHub – Report bugs, suggest features, or explore the source code.
- Contribute to Documentation and Samples – Report issues in Genkit's documentation, or contribute to the samples.
Contributing
Contributions to Genkit are welcome and highly appreciated! See our Contribution Guide to get started.
Authors
Genkit is built by Google with contributions from the Open Source Community.
README mirrored from the source repository 4 months ago. The original is authoritative.