Apache Polaris Iceberg Ai
FreeNot checkedModel Context Protocol (MCP) server for Apache Polaris. Enables AI agents and LLMs to interact with Polaris Catalog Management, audit data governance and access
About
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:9000orhttps://s3.amazonaws.com)AWS_ACCESS_KEY_ID: Your AWS or MinIO access keyAWS_SECRET_ACCESS_KEY: Your AWS or MinIO secret key
Override parameters
The inspect_request tool also accepts optional overrides:
s3_endpointaws_access_key_idaws_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
Installing Apache Polaris Iceberg Ai
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/sankeerthnagapuri/apache-polaris-iceberg-ai-mcpFAQ
Is Apache Polaris Iceberg Ai MCP free?
Yes, Apache Polaris Iceberg Ai MCP is free — one-click install via Unyly at no cost.
Does Apache Polaris Iceberg Ai need an API key?
No, Apache Polaris Iceberg Ai runs without API keys or environment variables.
Is Apache Polaris Iceberg Ai hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Apache Polaris Iceberg Ai in Claude Desktop, Claude Code or Cursor?
Open Apache Polaris Iceberg Ai on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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