Duckdb Iceberg
БесплатноНе проверенEnables AI assistants to query Apache Iceberg tables on S3 via AWS Glue Data Catalog using DuckDB as the embedded query engine, supporting columnar Arrow reads
Описание
Enables AI assistants to query Apache Iceberg tables on S3 via AWS Glue Data Catalog using DuckDB as the embedded query engine, supporting columnar Arrow reads with no data movement.
README
An MCP server that lets AI assistants query Apache Iceberg tables on S3 via AWS Glue Data Catalog. DuckDB is the embedded query engine — Apache Arrow columnar format, vectorized execution, direct S3 reads with no data movement.
Built on the official Python MCP SDK.
This MCP server is complementary to telemetry-iceberg-adaptor, which ingests telemetry data into Apache Iceberg. Use that project to write data and this project to query it through MCP-enabled AI clients.
Architecture
+----------------------+
| MCP Clients |
| - OpenAI Codex |
| - Claude Desktop |
| - OpenCode |
| - LibreChat |
+----------------------+
|
| MCP Protocol (tools/list · tools/call)
v
+--------------------------------------------------------------------------------------------+
| duckdb-iceberg-mcp |
| |
| +----------------------------------------------------------------------------------------+ |
| | MCP Protocol Layer | |
| | stdio · Streamable HTTP · SSE | |
| | JWT auth · write guard · row/char limits | |
| +----------------------------------------------------------------------------------------+ |
| <--> |
| +----------------------------------------------------------------------------------------+ |
| | ⚡ DuckDB | |
| | Apache Arrow columnar engine | |
| | Vectorized execution · Direct S3 reads | |
| | httpfs · iceberg · aws extensions | |
| +----------------------------------------------------------------------------------------+ |
+--------------------------------------------------------------------------------------------+
| |
| httpfs extension | boto3
| columnar Parquet reads | metadata · schema
| | Iceberg manifest resolution
v v
+--------------------------------------------------------------------------------------------+
| AWS |
| +-------------- Amazon S3 --------------+ +------------ AWS Glue Data Catalog ----------+ |
| | Apache Iceberg tables | | Databases · Tables · Schema | |
| | Parquet data files | | Iceberg metadata | |
| +---------------------------------------+ +---------------------------------------------+ |
+--------------------------------------------------------------------------------------------+
Features
- Query Iceberg tables on S3 via AWS Glue Data Catalog
- Three transports:
stdio, Streamable HTTP, SSE - Easy mode — single-tenant, optional static API key, no IdP required
- Full mode — JWT/JWKS token validation (Auth0, Cognito, Keycloak, Okta, …)
- Writes disabled by default; only available in full mode with explicit opt-in
- Configurable row and character limits to prevent runaway responses
Requirements
- Python 3.12+
- AWS credentials with access to Glue Data Catalog and S3
Installation
git clone <repo>
cd duckdb-iceberg-mcp
python -m venv .venv
source .venv/bin/activate
pip install -e .
Quick Start
stdio (local AI client)
Copy the example config and fill in your AWS details:
cp config/easy.env.example .env
# .env
MCP_MODE=easy
MCP_TRANSPORT=stdio
CATALOG_TYPE=glue
AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID=AKIA...
AWS_SECRET_ACCESS_KEY=...
Run directly:
duckdb-iceberg-mcp
Or configure in your MCP client (Claude Desktop, OpenAI Codex):
{
"mcpServers": {
"duckdb-iceberg-mcp": {
"command": "/path/to/.venv/bin/duckdb-iceberg-mcp",
"env": {
"MCP_MODE": "easy",
"CATALOG_TYPE": "glue",
"AWS_REGION": "us-east-1",
"AWS_ACCESS_KEY_ID": "AKIA...",
"AWS_SECRET_ACCESS_KEY": "..."
}
}
}
}
Streamable HTTP (network clients, e.g. LibreChat in Docker)
MCP_MODE=easy
MCP_TRANSPORT=http
MCP_HOST=0.0.0.0
MCP_PORT=8766
MCP_ALLOWED_HOSTS=host.docker.internal:*,localhost:*
CATALOG_TYPE=glue
AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID=AKIA...
AWS_SECRET_ACCESS_KEY=...
env $(grep -v '^#' .env | grep -v '^$' | xargs) .venv/bin/duckdb-iceberg-mcp
MCP client URL: http://localhost:8766/mcp
LibreChat (librechat.yaml):
mcpServers:
duckdb-iceberg-mcp:
type: streamable-http
url: 'http://host.docker.internal:8766/mcp'
timeout: 60000
initTimeout: 20000
OpenAI Codex: add via the Codex UI — Streamable HTTP, URL http://localhost:8766/mcp.
AWS Authentication
Configure credentials using one of these methods (key/secret takes priority if both are set):
| Method | Env vars |
|---|---|
| Explicit credentials | AWS_ACCESS_KEY_ID + AWS_SECRET_ACCESS_KEY |
| Named profile | AWS_PROFILE=my-profile |
| Default chain | Set neither — falls back to env vars, ~/.aws/credentials, instance role |
MCP Tools
list_tables(database?)
Lists Glue catalog tables. Optionally filter by database name.
describe_table(table_name)
Returns column names, types, and partition keys. Use database.table format.
glue_table(table_name)
Registers a Glue Iceberg table as a queryable DuckDB view. Required for tables where data files live outside the Glue-registered table root (a common layout with shared S3 prefixes).
glue_table('mydb.mytable')
→ Registered view 'mydb__mytable'. Query with: SELECT * FROM mydb__mytable
query_lakehouse(sql)
Executes a SQL query against registered views or direct S3 paths (read_parquet(), iceberg_scan()).
Configuration Reference
| Variable | Default | Description |
|---|---|---|
MCP_MODE |
easy |
easy or full |
MCP_TRANSPORT |
stdio |
stdio, http (Streamable HTTP), sse |
MCP_HOST |
127.0.0.1 |
Bind address for HTTP/SSE |
MCP_PORT |
8000 |
Port for HTTP/SSE |
MCP_ALLOWED_HOSTS |
(empty) | Comma-separated allowed Host headers (e.g. host.docker.internal:*,localhost:*). Empty = SDK default |
MCP_API_KEY |
(empty) | Static bearer token for easy mode HTTP. Empty = no auth |
JWKS_URL |
(required in full mode) | JWKS endpoint for JWT validation |
JWT_AUDIENCE |
duckdb-iceberg-mcp |
Expected aud claim in JWTs |
CATALOG_TYPE |
glue |
Only glue supported |
AWS_REGION |
us-east-1 |
AWS region |
AWS_PROFILE |
(empty) | Named AWS profile |
AWS_ACCESS_KEY_ID |
(empty) | AWS access key |
AWS_SECRET_ACCESS_KEY |
(empty) | AWS secret key |
WRITE_MODE |
disabled |
disabled or enabled. Always disabled in easy mode |
MAX_ROWS |
250 |
Maximum rows returned per query |
MAX_CHARS |
40000 |
Maximum characters in a query response |
Full Mode (JWT Auth)
Full mode validates a JWT bearer token on every request. All authenticated users share one DuckDB connection — per-user session isolation is deferred to a future release.
MCP_MODE=full
MCP_TRANSPORT=http
MCP_HOST=0.0.0.0
MCP_PORT=8766
JWKS_URL=https://your-idp.example.com/.well-known/jwks.json
JWT_AUDIENCE=duckdb-iceberg-mcp
AWS_REGION=us-east-1
AWS_ACCESS_KEY_ID=AKIA...
AWS_SECRET_ACCESS_KEY=...
The client passes a JWT as Authorization: Bearer <token>. The server validates it against the JWKS endpoint. Any IdP that issues standard JWTs works (Auth0, AWS Cognito, Keycloak, Okta).
See config/full.env.example for a full template.
Smoke Test
Run a quick end-to-end check against your real Glue catalog:
cp config/easy.env.example .env # fill in AWS credentials
.venv/bin/python scripts/smoke_test.py
Run Tests
pip install -e ".[dev]"
pytest
Установка Duckdb Iceberg
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/ys1173/duckdb-iceberg-mcpFAQ
Duckdb Iceberg MCP бесплатный?
Да, Duckdb Iceberg MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Duckdb Iceberg?
Нет, Duckdb Iceberg работает без API-ключей и переменных окружения.
Duckdb Iceberg — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Duckdb Iceberg в Claude Desktop, Claude Code или Cursor?
Открой Duckdb Iceberg 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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