Install
$ agentstack add mcp-sankeerthnagapuri-apache-polaris-iceberg-ai-mcp ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Polaris Catalog & Iceberg Governance MCP Server
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 revenuedaily 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 serviceadmin?", "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
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: sankeerthnagapuri
- Source: sankeerthnagapuri/apache-polaris-iceberg-ai-mcp
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.