Skip to main content
Glama

Genkit MCP

Official
by firebase
index.ts4.16 kB
/** * Copyright 2025 Google LLC * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ import { GenkitError, ModelReference, z } from 'genkit'; import { genkitPluginV2, type GenkitPluginV2 } from 'genkit/plugin'; import { ActionType } from 'genkit/registry'; import { getDerivedParams } from '../../common/index.js'; import * as anthropic from './anthropic.js'; import * as llama from './llama.js'; import * as mistral from './mistral.js'; import type { PluginOptions } from './types.js'; export type { PluginOptions }; async function initializer(pluginOptions?: PluginOptions) { const clientOptions = await getDerivedParams(pluginOptions); return [ ...anthropic.listKnownModels(clientOptions, pluginOptions), ...mistral.listKnownModels(clientOptions, pluginOptions), ...llama.listKnownModels(clientOptions, pluginOptions), ]; } async function resolver( actionType: ActionType, actionName: string, pluginOptions?: PluginOptions ) { const clientOptions = await getDerivedParams(pluginOptions); switch (actionType) { case 'model': if (anthropic.isAnthropicModelName(actionName)) { return anthropic.defineModel(actionName, clientOptions, pluginOptions); } else if (mistral.isMistralModelName(actionName)) { return mistral.defineModel(actionName, clientOptions, pluginOptions); } else if (llama.isLlamaModelName(actionName)) { return llama.defineModel(actionName, clientOptions, pluginOptions); } break; } return undefined; } async function listActions(options?: PluginOptions) { try { const clientOptions = await getDerivedParams(options); return [ ...anthropic.listActions(clientOptions), ...mistral.listActions(clientOptions), ...llama.listActions(clientOptions), ]; } catch (e: unknown) { return []; } } /** * Add Google Cloud Vertex AI Model Garden to Genkit. */ export function vertexModelGardenPlugin( options: PluginOptions ): GenkitPluginV2 { let listActionsCache; return genkitPluginV2({ name: 'vertex-model-garden', init: async () => await initializer(options), resolve: async (actionType: ActionType, actionName: string) => await resolver(actionType, actionName, options), list: async () => { if (listActionsCache) return listActionsCache; listActionsCache = await listActions(options); return listActionsCache; }, }); } export type VertexModelGardenPlugin = { (pluginOptions?: PluginOptions): GenkitPluginV2; model( name: anthropic.KnownModels | (anthropic.AnthropicModelName & {}), config?: anthropic.AnthropicConfig ): ModelReference<anthropic.AnthropicConfigSchemaType>; model( name: mistral.KnownModels | (mistral.MistralModelName & {}), config: mistral.MistralConfig ): ModelReference<mistral.MistralConfigSchemaType>; model( name: llama.KnownModels | (llama.LlamaModelName & {}), config: llama.LlamaConfig ): ModelReference<llama.LlamaConfigSchemaType>; model(name: string, config?: any): ModelReference<z.ZodTypeAny>; }; export const vertexModelGarden = vertexModelGardenPlugin as VertexModelGardenPlugin; (vertexModelGarden as any).model = ( name: string, config?: any ): ModelReference<z.ZodTypeAny> => { if (anthropic.isAnthropicModelName(name)) { return anthropic.model(name, config); } if (mistral.isMistralModelName(name)) { return mistral.model(name, config); } if (llama.isLlamaModelName(name)) { return llama.model(name, config); } throw new GenkitError({ status: 'INVALID_ARGUMENT', message: `model '${name}' is not a recognized model name`, }); };

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/firebase/genkit'

If you have feedback or need assistance with the MCP directory API, please join our Discord server