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InfluxDB Cloud Dedicated

Use the InfluxDB 3 MCP server

InfluxDB provides two Model Context Protocol (MCP) servers for integrating with AI assistants:

Manage your InfluxDB instance with the database MCP server

The InfluxDB database MCP server lets you interact with InfluxDB Cloud Dedicated using natural language with large language model (LLM) agents. It enables database management, token handling, and SQL query generation in plain English—no coding required.

This section walks you through configuring your LLM agent to run and use the InfluxDB database MCP server to interact with your InfluxDB Cloud Dedicated cluster .

Prerequisites

  • Node.js v18+ (if using npx to run the MCP server)
  • Docker (if using Docker to run the MCP server)
  • A running and reachable InfluxDB Cloud Dedicated

cluster .

Configure the database MCP server

Use environment variables to configure the InfluxDB 3 MCP server and connect it to your InfluxDB Cloud Dedicated

cluster . Set the following environment variables when you start the MCP server:

Required InfluxDB connection variables

  • INFLUX_DB_PRODUCT_TYPE: cloud-dedicated
  • INFLUX_DB_ACCOUNT_ID: Your InfluxDB Cloud Dedicated account ID
  • INFLUX_DB_CLUSTER_ID: Your InfluxDB Cloud Dedicated cluster ID
  • INFLUX_DB_TOKEN: An InfluxDB Cloud Dedicated database token
  • INFLUX_DB_MANAGEMENT_TOKEN: An InfluxDB Cloud Dedicated management token

Optional tokens

You can include one or both of INFLUX_DB_TOKEN and INFLUX_DB_MANAGEMENT_TOKEN, but omitting either limits the type of operations your LLM agents can perform on your InfluxDB Cloud Dedicated cluster.

Configure your LLM agent to run the database MCP server

To run the MCP server, use either Node.js and npm or Docker. Some LLM agents, like Claude Desktop, start, run, and connect to the MCP server for you.

The following instructions show how to configure Claude Desktop to use the InfluxDB database MCP server.

Node.js Docker

  1. Clone the influxdata/influxdb3_mcp_server repository from GitHub.

  2. Navigate to the influxdb3_mcp_server project directory:

    cd influxdb3_mcp_server/

  3. Install dependencies:

    npm install

  4. Build the MCP server:

    npm run build

This builds the files necessary to run the MCP server and stores them in ./build. The ./build/index.js file starts the MCP server.

Configure your LLM Agent to use the Node.js-based MCP server

In Claude Desktop, go to Settings > Developer and edit your configuration. Enter the following JSON configuration:

{
  "mcpServers": {
    "influxdb": {
      "command": "node",
      "args": ["/
path/to
/influxdb3_mcp_server/build/index.js"],
      "env": {
        "INFLUX_DB_PRODUCT_TYPE": "cloud-dedicated",
        "INFLUX_DB_CLUSTER_ID": "
DEDICATED_CLUSTER_ID
",
        "INFLUX_DB_ACCOUNT_ID": "
DEDICATED_ACCOUNT_ID
",
        "INFLUX_DB_TOKEN": "
DEDICATED_DATABASE_TOKEN
",
        "INFLUX_DB_MANAGEMENT_TOKEN": "
DEDICATED_MANAGEMENT_TOKEN
"
      }
    }
  }
}

Replace the following:

  • path/to: The absolute path to your influxdb3_mcp_server project directory.
  • DEDICATED_ACCOUNT_ID: Your InfluxDB Cloud Dedicated account ID
  • DEDICATED_CLUSTER_ID: Your InfluxDB Cloud Dedicated cluster ID
  • DEDICATED_DATABASE_TOKEN: A database token with permissions that grant access to all databases you would like your LLM agent to be able to write data to and query data from
  • DEDICATED_MANAGEMENT_TOKEN: A management token that lets your LLM agent perform administrative tasks on your InfluxDB Cloud Dedicated cluster

Configure your LLM Agent to use the Docker-based MCP server

In Claude Desktop, go to Settings > Developer and edit your configuration. Enter the following JSON configuration:

{
  "mcpServers": {
    "influxdb": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "--interactive",
        "--env",
        "INFLUX_DB_PRODUCT_TYPE",
        "--env",
        "INFLUX_DB_ACCOUNT_ID",
        "--env",
        "INFLUX_DB_CLUSTER_ID",
        "--env",
        "INFLUX_DB_TOKEN",
        "--env",
        "INFLUX_DB_MANAGEMENT_TOKEN",
        "influxdata/influxdb3-mcp-server"
      ],
      "env": {
        "INFLUX_DB_PRODUCT_TYPE": "cloud-dedicated",
        "INFLUX_DB_ACCOUNT_ID": "
DEDICATED_ACCOUNT_ID
",
        "INFLUX_DB_CLUSTER_ID": "
DEDICATED_CLUSTER_ID
",
        "INFLUX_DB_TOKEN": "
DEDICATED_DATABASE_TOKEN
",
        "INFLUX_DB_MANAGEMENT_TOKEN": "
DEDICATED_MANAGEMENT_TOKEN
"
      }
    }
  }
}

Replace the following:

  • DEDICATED_ACCOUNT_ID: Your InfluxDB Cloud Dedicated account ID
  • DEDICATED_CLUSTER_ID: Your InfluxDB Cloud Dedicated cluster ID
  • DEDICATED_DATABASE_TOKEN: A database token with permissions that grant access to all databases you would like your LLM agent to be able to write data to and query data from
  • DEDICATED_MANAGEMENT_TOKEN: A management token that lets your LLM agent perform administrative tasks on your InfluxDB Cloud Dedicated cluster

Supported features

Once connected, you can use your LLM agent to perform tasks on your InfluxDB Cloud Dedicated cluster , including:

  • Create, update, and delete databases
  • List tables and inspect schemas
  • Create and manage tokens
  • Query data without writing SQL or InfluxQL
  • Check server health and connection status

Examples of supported prompts

“List all tables in the production database.”

“Create a read-only token for the metrics database.”

“Analyze last week’s sensor data for anomalies.”

“Create a new database called iot_sensors with a 30-day retention policy.”

“Show me the schema for the sensor_data table.”

Query documentation from your IDE

The InfluxDB documentation MCP server lets AI tools and agents search InfluxDB InfluxDB Cloud Dedicated documentation directly from your development environment. Use it to find answers, code examples, and configuration details without leaving your IDE.

Why use the documentation MCP server?

When you connect the documentation MCP server to your AI coding assistant, the assistant can search InfluxDB and related tool documentation to answer your questions with accurate, up-to-date information. Instead of switching to a browser or guessing at syntax, you can ask questions in your IDE and get responses grounded in official documentation.

Common use cases:

  • Get help writing queries, client library code, or CLI commands
  • Look up configuration options and environment variables
  • Find code examples for specific tasks
  • Troubleshoot errors with documentation-backed answers

Install the documentation MCP server

The documentation MCP server is a hosted service—you don’t need to install or run anything locally. Add the server URL to your AI assistant’s MCP configuration.

On first use, you’ll be prompted to sign in with Google. This authentication is used only for rate limiting—no personal data is collected.

MCP server URL:

https://influxdb-docs.mcp.kapa.ai

The server uses SSE (Server-Sent Events) transport.

Configure your AI assistant to use the documentation MCP server

The following instructions show how to configure popular AI assistants to use the InfluxDB documentation MCP server.

Claude Desktop ChatGPT Desktop GitHub Copilot (VS Code) Cursor OpenCode

In Claude Desktop, go to Settings > Developer and edit your configuration. Add the following JSON configuration:

{
  "mcpServers": {
    "influxdb-docs": {
      "url": "https://influxdb-docs.mcp.kapa.ai"
    }
  }
}

Save the file and restart Claude Desktop for the changes to take effect.

In ChatGPT Desktop, go to Settings > Integrations > Enable MCP and add a new server. Add the following JSON configuration:

{
  "mcpServers": {
    "influxdb-docs": {
      "url": "https://influxdb-docs.mcp.kapa.ai",
      "transport": "sse"
    }
  }
}

Save the configuration and restart ChatGPT Desktop.

In VS Code, configure GitHub Copilot to use the MCP server:

  1. Create or edit .vscode/mcp.json in your workspace or project directory
  2. Add the following configuration:
{
  "servers": {
    "influxdb-docs": {
      "type": "http",
      "url": "https://influxdb-docs.mcp.kapa.ai"
    }
  }
}
  1. Restart or reload VS Code
  2. Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P)
  3. Run MCP: List Servers to verify the server is registered

The InfluxDB documentation MCP server will now be available through GitHub Copilot Chat.

In Cursor, add the MCP server configuration to your MCP settings file.

  1. Open Settings and navigate to MCP Servers
  2. Click Add MCP Server or edit the configuration file directly
  3. Add the following configuration to .cursor/mcp.json (project-level) or ~/.cursor/mcp.json (global):
{
  "mcpServers": {
    "influxdb-docs": {
      "url": "https://influxdb-docs.mcp.kapa.ai",
      "transport": "streamableHttp"
    }
  }
}

Save the file and restart Cursor.

In OpenCode, configure the MCP server in your configuration file:

  1. Create or edit opencode.json (or opencode.jsonc) in your workspace
  2. Add the following configuration:
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "influxdb-docs": {
      "type": "remote",
      "url": "https://influxdb-docs.mcp.kapa.ai",
      "enabled": true
    }
  }
}
  1. Start OpenCode and use the /init command to verify the MCP server is accessible

The InfluxDB documentation search tools will be available in your OpenCode sessions.

Authentication and rate limits

When you connect to the documentation MCP server for the first time, a Google sign-in window opens to complete an OAuth/OpenID Connect login.

The hosted MCP server:

  • Requests only the openid scope from Google
  • Receives an ID token (JWT) containing a stable, opaque user ID
  • Does not request email or profile scopes—your name, email address, and other personal data are not collected

The anonymous Google ID enforces per-user rate limits to prevent abuse:

  • 40 requests per user per hour
  • 200 requests per user per day

On Google’s consent screen, this appears as “Associate you with your personal info on Google.” This is Google’s generic wording for the openid scope—it means the app can recognize that the same Google account is signing in again. It does not grant access to your email, name, contacts, or other data.

Search documentation with the MCP tool

The documentation MCP server exposes a semantic search tool:

search_influxdb_knowledge_sources

This tool lets AI agents perform semantic retrieval over InfluxDB documentation and related knowledge sources.

What the tool does:

  • Searches all InfluxDB documentation for a given query
  • Returns the most relevant chunks in descending order of relevance
  • Each chunk is a self-contained snippet from a single documentation page

Response format:

Each result includes:

  • source_url: URL of the original documentation page
  • content: The chunk content in Markdown
MCP tool search results showing InfluxDB documentation

Use the documentation MCP server

After you install the documentation MCP server, your AI assistant can search InfluxDB documentation to help you with tasks. Ask questions naturally—the assistant uses the MCP server to find relevant documentation and provide accurate answers.

Example prompts

“How do I write data to InfluxDB using Python?”

“What’s the syntax for a SQL query with a WHERE clause in InfluxDB?”

“Show me how to configure Telegraf to collect CPU metrics.”

“What environment variables does the InfluxDB CLI use?”

“How do I create a database token with read-only permissions?”

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