Genkit MCP

# Firebase Genkit + Anthropic AI <h1 align="center">Firebase Genkit <> Anthropic AI Plugin</h1> <h4 align="center">Anthropic AI plugin for Google Firebase Genkit</h4> `@genkit-ai/anthropic` is the official Anthropic plugin for [Firebase Genkit](https://github.com/firebase/genkit). It supersedes the earlier community package `genkitx-anthropic` and is now maintained by Google. ## Supported models The plugin supports the most recent Anthropic models: **Claude Sonnet 4.5**, **Claude Opus 4.1**, **Claude Haiku 4.5**, **Claude Sonnet 4**, **Claude Opus 4**, **Claude 3.5 Haiku**, and **Claude 3 Haiku**. ## Installation Install the plugin in your project with your favorite package manager: - `npm install @genkit-ai/anthropic` - `yarn add @genkit-ai/anthropic` - `pnpm add @genkit-ai/anthropic` ## Usage ### Initialize ```typescript import { genkit } from 'genkit'; import { anthropic } from '@genkit-ai/anthropic'; const ai = genkit({ plugins: [anthropic({ apiKey: process.env.ANTHROPIC_API_KEY })], // specify a default model for generate here if you wish: model: anthropic.model('claude-sonnet-4-5'), }); ``` ### Basic examples The simplest way to generate text is by using the `generate` method: ```typescript const response = await ai.generate({ model: anthropic.model('claude-3-haiku'), prompt: 'Tell me a joke.', }); console.log(response.text); ``` ### Multi-modal prompt ```typescript // ...initialize Genkit instance (as shown above)... const response = await ai.generate({ prompt: [ { text: 'What animal is in the photo?' }, { media: { url: imageUrl } }, ], config: { // control of the level of visual detail when processing image embeddings // Low detail level also decreases the token usage visualDetailLevel: 'low', }, }); console.log(response.text); ``` ### Extended thinking Claude 4 models can expose their internal reasoning. Enable it per-request with the Anthropic thinking config and read the reasoning from the response: ```typescript const response = await ai.generate({ prompt: 'Walk me through your reasoning for Fermat’s little theorem.', config: { thinking: { enabled: true, budgetTokens: 4096, // Must be >= 1024 and less than max_tokens }, }, }); console.log(response.text); // Final assistant answer console.log(response.reasoning); // Summarized thinking steps ``` When thinking is enabled, request bodies sent through the plugin include the `thinking` payload (`{ type: 'enabled', budget_tokens: … }`) that Anthropic's API expects, and streamed responses deliver `reasoning` parts as they arrive so you can render the chain-of-thought incrementally. ### Beta API Limitations The beta API surface provides access to experimental features, but some server-managed tool blocks are not yet supported by this plugin. The following beta API features will cause an error if encountered: - `web_fetch_tool_result` - `code_execution_tool_result` - `bash_code_execution_tool_result` - `text_editor_code_execution_tool_result` - `mcp_tool_result` - `mcp_tool_use` - `container_upload` Note that `server_tool_use` and `web_search_tool_result` ARE supported and work with both stable and beta APIs. ### Within a flow ```typescript import { z } from 'genkit'; // ...initialize Genkit instance (as shown above)... export const jokeFlow = ai.defineFlow( { name: 'jokeFlow', inputSchema: z.string(), outputSchema: z.string(), }, async (subject) => { const llmResponse = await ai.generate({ prompt: `tell me a joke about ${subject}`, }); return llmResponse.text; } ); ``` ### Direct model usage (without Genkit instance) The plugin supports Genkit Plugin API v2, which allows you to use models directly without initializing the full Genkit framework: ```typescript import { anthropic } from '@genkit-ai/anthropic'; // Create a model reference directly const claude = anthropic.model('claude-sonnet-4-5'); // Use the model directly const response = await claude({ messages: [ { role: 'user', content: [{ text: 'Tell me a joke.' }], }, ], }); console.log(response); ``` You can also create model references using the plugin's `model()` method: ```typescript import { anthropic } from '@genkit-ai/anthropic'; // Create model references const claudeSonnet45 = anthropic.model('claude-sonnet-4-5'); const claudeOpus41 = anthropic.model('claude-opus-4-1'); const claude35Haiku = anthropic.model('claude-3-5-haiku'); // Use the model reference directly const response = await claudeSonnet45({ messages: [ { role: 'user', content: [{ text: 'Hello!' }], }, ], }); ``` This approach is useful for: - Framework developers who need raw model access - Testing models in isolation - Using Genkit models in non-Genkit applications ## Acknowledgements This plugin builds on the community work published as [`genkitx-anthropic`](https://github.com/BloomLabsInc/genkit-plugins/blob/main/plugins/anthropic/README.md) by Bloom Labs Inc. Their Apache 2.0–licensed implementation provided the foundation for this maintained package. ## Contributing Want to contribute to the project? That's awesome! Head over to our [Contribution Guidelines](CONTRIBUTING.md). ## Need support? > [!NOTE] > This repository depends on Google's Firebase Genkit. For issues and questions related to Genkit, please refer to instructions available in [Genkit's repository](https://github.com/firebase/genkit). ## Credits This plugin is maintained by Google with acknowledgement to the community contributions from [Bloom Labs Inc](https://github.com/BloomLabsInc). ## License This project is licensed under the [Apache 2.0 License](https://github.com/BloomLabsInc/genkit-plugins/blob/main/LICENSE).