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Genkit plugin that provides interoperability between Genkit and Model Context Protocol (MCP). Both client and server use cases are supported.","maintainers":[{"name":"pavelgj","email":"pavelgj@gmail.com"},{"name":"i2amsam","email":"samphillips@google.com"},{"name":"apascal07","email":"apascal07@gmail.com"},{"name":"google-wombot","email":"node-team-npm+wombot@google.com"}],"readme":"# Genkit MCP\n\nSee [Genkit MCP documentation](https://genkit.dev/docs/model-context-protocol/).\n\nThis plugin provides integration between Genkit and the [Model Context Protocol](https://modelcontextprotocol.io) (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:\n- Consume MCP tools, prompts, and resources as a client using `createMcpHost` or `createMcpClient`.\n- Provide Genkit tools and prompts as an MCP server using `createMcpServer`.\n\n## Installation\n\nTo get started, you'll need Genkit and the MCP plugin:\n\n```bash\nnpm i genkit @genkit-ai/mcp\n```\n\n## MCP Host\n\nTo 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.\n\n```ts\nimport { googleAI } from '@genkit-ai/google-genai';\nimport { createMcpHost } from '@genkit-ai/mcp';\nimport { genkit } from 'genkit';\n\nconst mcpHost = createMcpHost({\n  name: 'myMcpClients', // A name for the host plugin itself\n  mcpServers: {\n    // Each key (e.g., 'fs', 'git') becomes a namespace for the server's tools.\n    fs: {\n      command: 'npx',\n      args: ['-y', '@modelcontextprotocol/server-filesystem', process.cwd()],\n    },\n    memory: {\n      command: 'npx',\n      args: ['-y', '@modelcontextprotocol/server-memory'],\n    },\n  },\n});\n\nconst ai = genkit({\n  plugins: [googleAI()],\n});\n\n(async () => {\n  // Provide MCP tools to the model of your choice.\n  const { text } = await ai.generate({\n    model: googleAI.model('gemini-2.0-flash'),\n    prompt: `Analyze all files in ${process.cwd()}.`,\n    tools: await mcpHost.getActiveTools(ai),\n    resources: await mcpHost.getActiveResources(ai),\n  });\n\n  console.log(text);\n\n  await mcpHost.close();\n})();\n```\n\nThe `createMcpHost` function initializes a `GenkitMcpHost` instance, which handles the lifecycle and communication with the defined MCP servers.\n\n### `createMcpHost()` Options\n\n-   **`name`**: (optional, string) A name for the MCP host plugin itself. Defaults to 'genkitx-mcp'.\n-   **`version`**: (optional, string) The version of the MCP host plugin. Defaults to \"1.0.0\".\n-   **`rawToolResponses`**: (optional, boolean) When `true`, tool responses are returned in their raw MCP format; otherwise, they are processed for Genkit compatibility. Defaults to `false`.\n-   **`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.\n\n    Each server configuration object can include:\n    -   **`disabled`**: (optional, boolean) If `true`, this server connection will not be attempted. Defaults to `false`.\n    -   One of the following server connection configurations:\n        -   Parameters for launching a local server process using the stdio MCP transport.\n            -   **`command`**: (required, string) Shell command path for launching the MCP server (e.g., `npx`, `python`).\n            -   **`args`**: (optional, string[]) Array of string arguments to pass to the command.\n            -   **`env`**: (optional, Record<string, string>) Key-value object of environment variables.\n        -   **`url`**: (string) The URL of a remote server to connect to using the Streamable HTTP MCP transport.\n        -   **`transport`**: An existing MCP transport object for connecting to the server.\n\n\n## MCP Client (Single Server)\n\nFor scenarios where you only need to connect to a single MCP server, or prefer to manage client instances individually, you can use `createMcpClient`.\n\n```ts\nimport { googleAI } from '@genkit-ai/google-genai';\nimport { createMcpClient } from '@genkit-ai/mcp';\nimport { genkit } from 'genkit';\n\nconst myFsClient = createMcpClient({\n  name: 'myFileSystemClient', // A unique name for this client instance\n  mcpServer: {\n    command: 'npx',\n    args: ['-y', '@modelcontextprotocol/server-filesystem', process.cwd()],\n  },\n  // rawToolResponses: true, // Optional: get raw MCP responses\n});\n\n// In your Genkit configuration:\nconst ai = genkit({\n  plugins: [googleAI()],\n});\n\n(async () => {\n  await myFsClient.ready();\n\n  // Retrieve tools from this specific client\n  const fsTools = await myFsClient.getActiveTools(ai);\n\n  const { text } = await ai.generate({\n    model: googleAI.model('gemini-2.0-flash'), // Replace with your model\n    prompt: 'List files in ' + process.cwd(),\n    tools: fsTools,\n  });\n  console.log(text);\n\n  await myFsClient.disable();\n})();\n```\n\n### `createMcpClient()` Options\n\nThe `createMcpClient` function takes an `McpClientOptions` object:\n-   **`name`**: (required, string) A unique name for this client instance. This name will be used as the namespace for its tools and prompts.\n-   **`version`**: (optional, string) Version for this client instance. Defaults to \"1.0.0\".\n-   Additionally, it supports all options from `McpServerConfig` (e.g., `disabled`, `rawToolResponses`, and transport configurations), as detailed in the `createMcpHost` options section.\n\n### Using MCP Actions (Tools, Prompts)\n\nBoth `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.\n\nMCP prompts can be fetched using `McpHost.getPrompt(serverName, promptName)` or `mcpClient.getPrompt(promptName)`. These return an `ExecutablePrompt`.\n\nAll MCP actions (tools, prompts, resources) are namespaced.\n- For `createMcpHost`, the namespace is the key you provide for that server in the `mcpServers` configuration (e.g., `localFs/read_file`).\n- For `createMcpClient`, the namespace is the `name` you provide in its options (e.g., `myFileSystemClient/list_resources`).\n\n### Tool Responses\n\nMCP 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:\n\n1. If the content is text and valid JSON, it is parsed and returned as a JSON object.\n2. If the content is text but not valid JSON, the raw text is returned.\n3. If the content contains a single non-text part (e.g., an image), that part is returned directly.\n4. If the content contains multiple or mixed parts (e.g., text and an image), the full content response array is returned.\n\n## MCP Server\n\nYou can also expose all of the tools and prompts from a Genkit instance as an MCP server using the `createMcpServer` function.\n\n```ts\nimport { googleAI } from '@genkit-ai/google-genai';\nimport { createMcpServer } from '@genkit-ai/mcp';\nimport { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';\nimport { genkit, z } from 'genkit/beta';\n\nconst ai = genkit({\n  plugins: [googleAI()],\n});\n\nai.defineTool(\n  {\n    name: 'add',\n    description: 'add two numbers together',\n    inputSchema: z.object({ a: z.number(), b: z.number() }),\n    outputSchema: z.number(),\n  },\n  async ({ a, b }) => {\n    return a + b;\n  }\n);\n\nai.definePrompt(\n  {\n    name: 'happy',\n    description: 'everybody together now',\n    input: {\n      schema: z.object({\n        action: z.string().default('clap your hands').optional(),\n      }),\n    },\n  },\n  `If you're happy and you know it, {{action}}.`\n);\n\nai.defineResource(\n  {\n    name: 'my resouces',\n    uri: 'my://resource',\n  },\n  async () => {\n    return {\n      content: [\n        {\n          text: 'my resource',\n        },\n      ],\n    };\n  }\n);\n\nai.defineResource(\n  {\n    name: 'file',\n    template: 'file://{path}',\n  },\n  async ({ uri }) => {\n    return {\n      content: [\n        {\n          text: `file contents for ${uri}`,\n        },\n      ],\n    };\n  }\n);\n\n// Use createMcpServer\nconst server = createMcpServer(ai, {\n  name: 'example_server',\n  version: '0.0.1',\n});\n// Setup (async) then starts with stdio transport by default\nserver.setup().then(async () => {\n  await server.start();\n  const transport = new StdioServerTransport();\n  await server!.server?.connect(transport);\n});\n```\n\nThe `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)`).\n\n### `createMcpServer()` Options\n- **`name`**: (required, string) The name you want to give your server for MCP inspection.\n- **`version`**: (optional, string) The version your server will advertise to clients. Defaults to \"1.0.0\".\n\n### Known Limitations\n\n- MCP prompts are only able to take string parameters, so inputs to schemas must be objects with only string property values.\n- MCP prompts only support `user` and `model` messages. `system` messages are not supported.\n- MCP prompts only support a single \"type\" within a message so you can't mix media and text in the same message.\n\n### Testing your MCP server\n\nYou can test your MCP server using the official inspector. For example, if your server code compiled into `dist/index.js`, you could run:\n\n    npx @modelcontextprotocol/inspector dist/index.js\n\nOnce you start the inspector, you can list prompts and actions and test them out manually.\n","readmeFilename":"README.md"}