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Apache Polaris Iceberg Ai

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Model Context Protocol (MCP) server for Apache Polaris. Enables AI agents and LLMs to interact with Polaris Catalog Management, audit data governance and access

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Описание

Model Context Protocol (MCP) server for Apache Polaris. Enables AI agents and LLMs to interact with Polaris Catalog Management, audit data governance and access control (RBAC) policies, and perform Iceberg table inspections using PyIceberg.

README

A FastMCP server that gives AI assistants (and data engineers) conversational access to Apache Polaris catalog management, Iceberg REST Catalog APIs, and PyIceberg table storage/health inspection tools.

It is designed to enable AI agents (like Cursor, Windsurf, or Claude Desktop) to audit data governance, check access control roles, query namespaces, and inspect Iceberg metadata.


What it does

12 tools across 10 categories:

Category Tool Name Operations What you can ask
Connection connect N/A "Connect to Polaris"
disconnect N/A "Disconnect from the Polaris server"
get_server_config N/A "What endpoints does the server support?"
Catalogs catalog_request list, get "What catalogs exist?", "Show me the storage config for catalog X"
Namespaces namespace_request list, get, exists "List all namespaces in catalog X", "Does namespace Y exist?"
Tables table_request list, get, exists "List tables in prod.analytics", "Show me the schema and snapshots for table Z"
Views view_request list, get, exists "List views", "Load the revenue_daily view metadata"
Principals principal_request list, get, roles_assigned "Who has access?", "What roles does Alice have?"
Roles & Grants role_request list_principal_roles, get_principal_role, list_principals_for_role, list_catalog_roles, get_catalog_role, list_catalog_roles_for_principal_role, list_principal_roles_for_catalog_role, list_grants_for_catalog_role "What roles exist?", "Which catalog roles map to service_admin?", "What privileges does the analyst role have?"
Policies policy_request list, get, get_applicable "What policies apply to this table?", "Show the compaction policy"
Generic Tables generic_table_request list, get "What Delta/CSV tables are registered?"
Metadata Inspection inspect_request snapshots, files, manifests, partitions, health "Check snapshot history", "List raw Parquet data/delete files", "Show partition health/delete file overhead"

Quick Start

Install

cd apache-polaris-iceberg-ai-mcp
pip install -e .

Run the server

# Via FastMCP CLI
fastmcp run server.py

# Or directly
python -m server

Configure in Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "polaris-catalog": {
      "command": "fastmcp",
      "args": ["run", "/path/to/apache-polaris-iceberg-ai-mcp/server.py"]
    }
  }
}

Configure in VS Code (Copilot / Cline / etc.)

Add to your .vscode/mcp.json or MCP settings:

{
  "servers": {
    "polaris-catalog": {
      "command": "fastmcp",
      "args": ["run", "/path/to/apache-polaris-iceberg-ai-mcp/server.py"]
    }
  }
}

Authentication

The server supports three authentication modes via the connect tool:

1. Client Credentials (default)

connect(uri="http://localhost:8181", client_id="admin", client_secret="password")

2. Bearer Token

connect(uri="http://localhost:8181", token="eyJhbGciOiJSUzI1NiIs...")

3. Keycloak / OIDC Password Credentials

Use this to exchange username/password credentials for a token from Keycloak or another OIDC provider first, and then authenticate to Polaris with that token:

connect(
  uri="http://localhost:8181",
  oauth_token_url="http://localhost:8080/realms/polaris-realm/protocol/openid-connect/token",
  client_id="polaris-client",
  client_secret="sBbUvTG7qWGbmgwgxKmnEuzqpuE3uGAu",
  username="sankeerth",
  password="nagapuri"
)

Storage & Inspection Configuration

Since the inspect_request tool reads the underlying Avro metadata and Parquet data/delete files directly from your object storage, you should configure your S3/MinIO environment variables or pass options dynamically.

S3 / MinIO Environment Variables

By default, the inspection tools look for these environment variables or fallback to local MinIO dev defaults (admin / password / http://localhost:9000):

  • S3_ENDPOINT: S3 endpoint URL (e.g., http://localhost:9000 or https://s3.amazonaws.com)
  • AWS_ACCESS_KEY_ID: Your AWS or MinIO access key
  • AWS_SECRET_ACCESS_KEY: Your AWS or MinIO secret key

Override parameters

The inspect_request tool also accepts optional overrides:

  • s3_endpoint
  • aws_access_key_id
  • aws_secret_access_key

Architecture

apache-polaris-iceberg-ai-mcp/
├── server.py              # FastMCP server — registers consolidated tools
├── client.py              # Async HTTP client (httpx) with OAuth2 + password grant auth
├── requirements.txt       # Dependencies (fastmcp, httpx, pydantic, pyiceberg, pyarrow, s3fs)
└── tools/                 # Tool implementations by domain
    ├── connection.py      # connect, disconnect, get_server_config
    ├── catalogs.py        # catalog_request (list, get)
    ├── principals.py      # principal_request (list, get, roles_assigned)
    ├── roles.py           # role_request (principal/catalog roles, mapping, grants)
    ├── namespaces.py      # namespace_request (list, get, exists)
    ├── tables.py          # table_request (list, get, exists)
    ├── views.py           # view_request (list, get, exists)
    ├── policies.py        # policy_request (list, get, get_applicable)
    ├── generic_tables.py  # generic_table_request (list, get)
    └── inspect.py         # inspect_request (snapshots, files, manifests, partitions, health)

License

MIT License

from github.com/sankeerthnagapuri/apache-polaris-iceberg-ai-mcp

Установка Apache Polaris Iceberg Ai

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/sankeerthnagapuri/apache-polaris-iceberg-ai-mcp

FAQ

Apache Polaris Iceberg Ai MCP бесплатный?

Да, Apache Polaris Iceberg Ai MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Apache Polaris Iceberg Ai?

Нет, Apache Polaris Iceberg Ai работает без API-ключей и переменных окружения.

Apache Polaris Iceberg Ai — hosted или self-hosted?

Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.

Как установить Apache Polaris Iceberg Ai в Claude Desktop, Claude Code или Cursor?

Открой Apache Polaris Iceberg Ai на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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