Genkit MCP

This plugin provides integration between Genkit and the Model Context Protocol (MCP). MCP is an open standard allowing developers to build "servers" which provide tools, resources, and prompts to clients. Genkit MCP allows Genkit developers to:

Consume MCP tools, prompts, and resources as a client using createMcpHost or createMcpClient.
Provide Genkit tools and prompts as an MCP server using createMcpServer.

Installation

To get started, you'll need Genkit and the MCP plugin:

npm i genkit @genkit-ai/mcp

MCP Host

To connect to one or more MCP servers, you use the createMcpHost function. This function returns a GenkitMcpHost instance that manages connections to the configured MCP servers.

import { googleAI } from '@genkit-ai/google-genai';
import { createMcpHost } from '@genkit-ai/mcp';
import { genkit } from 'genkit';

const mcpHost = createMcpHost({
  name: 'myMcpClients', // A name for the host plugin itself
  mcpServers: {
    // Each key (e.g., 'fs', 'git') becomes a namespace for the server's tools.
    fs: {
      command: 'npx',
      args: ['-y', '@modelcontextprotocol/server-filesystem', process.cwd()],
    },
    memory: {
      command: 'npx',
      args: ['-y', '@modelcontextprotocol/server-memory'],
    },
  },
});

const ai = genkit({
  plugins: [googleAI()],
});

(async () => {
  // Provide MCP tools to the model of your choice.
  const { text } = await ai.generate({
    model: googleAI.model('gemini-2.0-flash'),
    prompt: `Analyze all files in ${process.cwd()}.`,
    tools: await mcpHost.getActiveTools(ai),
    resources: await mcpHost.getActiveResources(ai),
  });

  console.log(text);

  await mcpHost.close();
})();

The createMcpHost function initializes a GenkitMcpHost instance, which handles the lifecycle and communication with the defined MCP servers.

`createMcpHost()` Options

name: (optional, string) A name for the MCP host plugin itself. Defaults to 'genkitx-mcp'.
version: (optional, string) The version of the MCP host plugin. Defaults to "1.0.0".
rawToolResponses: (optional, boolean) When true, tool responses are returned in their raw MCP format; otherwise, they are processed for Genkit compatibility. Defaults to false.
mcpServers: (required, object) An object where each key is a client-side name (namespace) for an MCP server, and the value is the configuration for that server.Each server configuration object can include:
- disabled: (optional, boolean) If true, this server connection will not be attempted. Defaults to false.
- One of the following server connection configurations:
  - Parameters for launching a local server process using the stdio MCP transport.
    - command: (required, string) Shell command path for launching the MCP server (e.g., npx, python).
    - args: (optional, string[]) Array of string arguments to pass to the command.
    - env: (optional, Record<string, string>) Key-value object of environment variables.
  - url: (string) The URL of a remote server to connect to using the Streamable HTTP MCP transport.
  - transport: An existing MCP transport object for connecting to the server.

MCP Client (Single Server)

For scenarios where you only need to connect to a single MCP server, or prefer to manage client instances individually, you can use createMcpClient.

import { googleAI } from '@genkit-ai/google-genai';
import { createMcpClient } from '@genkit-ai/mcp';
import { genkit } from 'genkit';

const myFsClient = createMcpClient({
  name: 'myFileSystemClient', // A unique name for this client instance
  mcpServer: {
    command: 'npx',
    args: ['-y', '@modelcontextprotocol/server-filesystem', process.cwd()],
  },
  // rawToolResponses: true, // Optional: get raw MCP responses
});

// In your Genkit configuration:
const ai = genkit({
  plugins: [googleAI()],
});

(async () => {
  await myFsClient.ready();

  // Retrieve tools from this specific client
  const fsTools = await myFsClient.getActiveTools(ai);

  const { text } = await ai.generate({
    model: googleAI.model('gemini-2.0-flash'), // Replace with your model
    prompt: 'List files in ' + process.cwd(),
    tools: fsTools,
  });
  console.log(text);

  await myFsClient.disable();
})();

`createMcpClient()` Options

The createMcpClient function takes an McpClientOptions object:

name: (required, string) A unique name for this client instance. This name will be used as the namespace for its tools and prompts.
version: (optional, string) Version for this client instance. Defaults to "1.0.0".
Additionally, it supports all options from McpServerConfig (e.g., disabled, rawToolResponses, and transport configurations), as detailed in the createMcpHost options section.

Using MCP Actions (Tools, Prompts)

Both GenkitMcpHost (via getActiveTools()) and GenkitMcpClient (via getActiveTools()) discover available tools from their connected and enabled MCP server(s). These tools are standard Genkit ToolAction instances and can be provided to Genkit models.

MCP prompts can be fetched using McpHost.getPrompt(serverName, promptName) or mcpClient.getPrompt(promptName). These return an ExecutablePrompt.

All MCP actions (tools, prompts, resources) are namespaced.

For createMcpHost, the namespace is the key you provide for that server in the mcpServers configuration (e.g., localFs/read_file).
For createMcpClient, the namespace is the name you provide in its options (e.g., myFileSystemClient/list_resources).

Tool Responses

MCP tools return a content array as opposed to a structured response like most Genkit tools. The Genkit MCP plugin attempts to parse and coerce returned content:

If the content is text and valid JSON, it is parsed and returned as a JSON object.
If the content is text but not valid JSON, the raw text is returned.
If the content contains a single non-text part (e.g., an image), that part is returned directly.
If the content contains multiple or mixed parts (e.g., text and an image), the full content response array is returned.

MCP Server

You can also expose all of the tools and prompts from a Genkit instance as an MCP server using the createMcpServer function.

import { googleAI } from '@genkit-ai/google-genai';
import { createMcpServer } from '@genkit-ai/mcp';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';
import { genkit, z } from 'genkit/beta';

const ai = genkit({
  plugins: [googleAI()],
});

ai.defineTool(
  {
    name: 'add',
    description: 'add two numbers together',
    inputSchema: z.object({ a: z.number(), b: z.number() }),
    outputSchema: z.number(),
  },
  async ({ a, b }) => {
    return a + b;
  }
);

ai.definePrompt(
  {
    name: 'happy',
    description: 'everybody together now',
    input: {
      schema: z.object({
        action: z.string().default('clap your hands').optional(),
      }),
    },
  },
  `If you're happy and you know it, {{action}}.`
);

ai.defineResource(
  {
    name: 'my resouces',
    uri: 'my://resource',
  },
  async () => {
    return {
      content: [
        {
          text: 'my resource',
        },
      ],
    };
  }
);

ai.defineResource(
  {
    name: 'file',
    template: 'file://{path}',
  },
  async ({ uri }) => {
    return {
      content: [
        {
          text: `file contents for ${uri}`,
        },
      ],
    };
  }
);

// Use createMcpServer
const server = createMcpServer(ai, {
  name: 'example_server',
  version: '0.0.1',
});
// Setup (async) then starts with stdio transport by default
server.setup().then(async () => {
  await server.start();
  const transport = new StdioServerTransport();
  await server!.server?.connect(transport);
});

The createMcpServer function returns a GenkitMcpServer instance. The start() method on this instance will start an MCP server (using the stdio transport by default) that exposes all registered Genkit tools and prompts. To start the server with a different MCP transport, you can pass the transport instance to the start() method (e.g., server.start(customMcpTransport)).

`createMcpServer()` Options

name: (required, string) The name you want to give your server for MCP inspection.
version: (optional, string) The version your server will advertise to clients. Defaults to "1.0.0".

Known Limitations

MCP prompts are only able to take string parameters, so inputs to schemas must be objects with only string property values.
MCP prompts only support user and model messages. system messages are not supported.
MCP prompts only support a single "type" within a message so you can't mix media and text in the same message.

Testing your MCP server

You can test your MCP server using the official inspector. For example, if your server code compiled into dist/index.js, you could run:

npx @modelcontextprotocol/inspector dist/index.js

Once you start the inspector, you can list prompts and actions and test them out manually.

Deploy Server

HTTP connection URL

security – no known vulnerabilities

license - permissive license

quality - confirmed to work

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Tools

Provides integration between Genkit and the Model Context Protocol (MCP).

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