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Yandex Cloud MCP servers for AI agents and IDEs

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Model Context Protocol (MCP) is an open standard for connecting AI applications to external systems. External systems fall into three categories:

  • Data sources, e.g., databases or file storages.
  • Tools, such as APIs or scripts.
  • Workflows, e.g., automated scripts.

Without MCP, any individual pair of AI applications and external systems would require a separate integration. MCP provides a unified interface that allows any MCP client to access external tools in a standardized way.
Yandex Cloud features a number of specialized MCP servers for managing cloud infrastructure, serverless resources, and data. With the help of these servers, AI agents can:

  • Create VMs.
  • Deploy functions and containers.
  • Configure triggers and workflows.
  • Search for metadata within a data catalog.
  • Access Yandex Cloud and web search.

Available MCP servers

Category

MCP server

Description

Infrastructure

Toolkit MCP server

Deploys simple apps using Yandex Compute Cloud, Yandex Virtual Private Cloud, Yandex Identity and Access Management, Yandex Object Storage, and Yandex Managed Service for YDB

Search and knowledge

Documentation MCP server

Provides real-time access to official Yandex Cloud documentation via generative search

Search and knowledge

Search MCP server

Performs classic and generative web search using Yandex Search API

Serverless

Functions MCP server

Creates and deploys Yandex Cloud Functions functions, manages their versions, tags, and scaling policies

Serverless

Serverless Containers MCP server

Manages Yandex Serverless Containers containers: deploys revisions, configures scaling, and works with image registries

Serverless

Triggers MCP server

Creates function and container triggers activated by timer or events in other services

Serverless

Workflows MCP server

Creates and executes Yandex Workflows workflows described in the YAML specification and manages their execution schedule

Serverless

API Gateway MCP server

Manages Yandex API Gateway gateways: OpenAPI specifications, custom domains, and WebSocket connections

Serverless

MCP Gateway MCP server

Creates MCP gateways and sets up tools for calling functions, containers, HTTP endpoints, and workflows

Data

Data Catalog Consumer MCP server

Allows searching for tables, views, and queries, as well as build lineage graphs in Yandex Data Catalog.

Connection

Yandex Cloud MCP servers support two connection methods: locally via the npm client (stdio transport) with automatic authentication, and remotely via Streamable HTTP.

Prerequisites

To connect a Yandex Cloud MCP server, you need:

  • Yandex Cloud role for the specific service, such as editor or functions.admin. For a full list of roles, see the Server configurations table.
  • Node.js version 18.0.0 or higher, if connecting via the npm client.
  • Yandex Cloud CLI. This is optional, required only for authentication via a CLI profile.

NPM client (stdio)

The @yandex-cloud/mcp npm client starts the MCP server locally and handles authentication in Yandex Cloud in one of the following ways:

  • OAuth: Authentication via the browser without additional flags. It is used by default.
  • OAuth with explicit account selection: -S <user_or_service_account_ID> or -u <email> parameter.
  • Authentication via Yandex Cloud CLI: -p <profile> parameter uses a pre-configured CLI profile. This method requires the Yandex Cloud CLI to be installed.
  • Without authentication: --no-auth parameter. This is suitable only for servers that do not require authorization (e.g., the Documentation MCP server).

Configuration example:

{
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y", "@yandex-cloud/mcp",
        "-s", "toolkit"
      ]
    }
  }
}

Where:

  • -s, --server: Name of the MCP server, e.g., toolkit, search, or functions. For a full list of server names, see Server configurations.
  • -r, --region <REGION>: Yandex Cloud region for OAuth authentication. It can be either ru or kz. The default value is ru.
  • -H, --header <Key:Value>: Additional header for each MCP server tool call. You can specify this parameter multiple times, e.g., to provide a Folder-Id.

Streamable HTTP

To connect via Streamable HTTP, use an IAM token, which you can obtain using the Yandex Cloud CLI:

yc iam create-token

To authenticate as a service account:

yc iam create-token --impersonate-service-account-id <service_account_ID>

Note

IAM tokens are valid for a maximum of 12 hours. After it expires, you need to reissue the token.

Configuration example:

{
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "streamableHttp",
      "url": "https://toolkit.mcp.cloud.yandex.net/mcp",
      "headers": {
        "Authorization": "Bearer <IAM_token>"
      }
    }
  }
}

Server configurations

Parameters for connecting MCP servers:

MCP server

Server name for an npm client (-s)

URL for Streamable HTTP

Required role

Toolkit

toolkit

https://toolkit.mcp.cloud.yandex.net/mcp

editor or compute.admin

Documentation

docs

https://docs.mcp.cloud.yandex.net/mcp

Not required

Search

search

https://search.mcp.cloud.yandex.net/mcp

search-api.webSearch.user

Functions

functions

https://functions.mcp.cloud.yandex.net/mcp

editor or functions.admin

Serverless Containers

containers

https://containers.mcp.cloud.yandex.net/mcp

editor or serverless-containers.admin

Triggers

triggers

https://triggers.mcp.cloud.yandex.net/mcp

editor or functions.admin

Workflows

workflows

https://workflows.mcp.cloud.yandex.net/mcp

editor or serverless.workflows.admin

API Gateway

apigateway

https://apigateway.mcp.cloud.yandex.net/mcp

editor or api-gateway.admin

MCP Gateway

mcpgateway

https://mcpgateway.mcp.cloud.yandex.net/mcp

editor or serverless.mcpGateways.admin

Data Catalog Consumer

datacatalog-consumer

https://datacatalog-consumer.mcp.cloud.yandex.net/mcp

data-catalog.viewer

For servers that access catalog resources (Toolkit, Search, Functions, Serverless Containers, Triggers, Workflows, API Gateway, MCP Gateway), you can provide default values via headers:

  • Cloud-Id: Cloud ID for the cloud_id field in MCP server tools.
  • Folder-Id: Folder ID for the folder_id field in MCP server tools.

Here is an example for the npm client:

npx @yandex-cloud/mcp -s toolkit -H "Folder-Id:<folder_ID>"

Connection examples

Connect an MCP server manually or using an AI agent.

Connecting via an AI agent

To configure and connect an MCP server, instruct your AI agent as follows:

Connect the Yandex Cloud MCP server via `npx @yandex-cloud/mcp -s <server_name>`.

Where <server_name> is the Server name for npm client (-s) column value from the table.

The AI agent will locate the configuration file and add the MCP server settings to it. To do this, it needs access to the file system and terminal.

Connecting popular IDEs

Below is an example of connecting the Toolkit MCP server via the npm client. To connect another server, replace the toolkit server name in the -s parameter with a different name from this table. If using Streamable HTTP, also replace the server URL.

SourceCraft Code Assistant supports configuration at two levels: global and project. For more information, see this Code Assistant guide.

  1. Click in the chat's top panel and select MCP servers.

  2. Select the appropriate option:

    • Edit Global MCP: Opens the global file named mcp_settings.json.
    • Edit Project MCP: Opens the project file named .codeassistant/mcp.json. If there is no such file, Code Assistant will create it automatically.

  3. Add the following configuration to the file:

    {
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y", "@yandex-cloud/mcp",
        "-s", "toolkit"
      ]
    }
  }
}

  4. Save the file.

Claude Code supports configuration at two levels: global and project. Read more in this Claude Code guide.

  1. Open the .mcp.json file in the project root (for project configuration) or ~/.mcp.json in the home directory (for global configuration).

  2. Add the following configuration to the file:

    {
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y", "@yandex-cloud/mcp",
        "-s", "toolkit"
      ]
    }
  }
}

  3. Save the file.

Test the connection:

claude mcp get yandex-cloud-toolkit

Cursor supports MCP servers via the mcp.json file. For more information, see this Cursor guide.

  1. Create the .cursor/mcp.json file in the project root (for project configuration) or ~/.cursor/mcp.json in the home directory (for global configuration).

  2. Add the following configuration to the file:

    {
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y", "@yandex-cloud/mcp",
        "-s", "toolkit"
      ]
    }
  }
}

  3. Save the file and restart Cursor or refresh the list of MCP servers in the settings.

Codex configures MCP servers in the ~/.codex/config.toml file. For more information, see this Codex guide.

  1. Open the ~/.codex/config.toml file.

  2. Add the following configuration to the file:

    [mcp_servers.yandex-cloud-toolkit]
command = "npx"
args = ["-y", "@yandex-cloud/mcp", "-s", "toolkit"]

  3. Save the file and restart Codex.

Zoo Code supports configuration at two levels: global and project. Read more in this Zoo Code guide.

  1. Click in the chat's top panel.

  2. In the left-hand panel, select MCP Servers.

  3. Select the appropriate option:

    • Edit Global MCP: Opens the global file named mcp_settings.json.
    • Edit Project MCP: Opens the project file named .roo/mcp.json. If there is no such file, Zoo Code will create it automatically.

  4. Add the following configuration to the file:

    {
  "mcpServers": {
    "yandex-cloud-toolkit": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y", "@yandex-cloud/mcp",
        "-s", "toolkit"
      ]
    }
  }
}

  5. Save the file.

Yandex Cloud CLI as an alternative for agents

An AI agent with terminal access can manage Yandex Cloud resources directly via the Yandex Cloud CLI without connecting an MCP server. This is helpful when the agent needs commands that are not yet available among the MCP server tools, or when the terminal is already the agent's primary tool.

To enable your agent to use the CLI:

  1. Install the Yandex Cloud CLI in the environment where the agent is running.

  2. Create a profile. Log in as a user or service account.

  3. Add the --format json parameter to CLI commands so the agent can deliver structured output, like this:

    yc compute instance list --format json

The roles required for specific CLI operations match the corresponding MCP server roles. For a full list of roles, see the Server configurations table.

Testing

Once the MCP server is connected, ask the AI agent to call one of the server tools.

Prompt examples:

Deploy a VM in Yandex Cloud with a public IP address.

Search the Yandex Cloud docs for instructions on how to configure a Terraform provider.

Create an Object Storage bucket for a static website.

If the connection is working properly, the AI agent will call the relevant MCP server tool and return you the operation result.

Useful links

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