DataHub Agent Context
MCP tools for AI agents to search and query your DataHub metadata catalog — works with Claude, Cursor, Copilot, and any MCP-compatible AI assistant.
What you can do
- Search datasets, dashboards, pipelines, and other data assets by name or description
- Retrieve entity details — schema, lineage, ownership, tags, glossary terms, and more
- Trace lineage upstream and downstream across your data assets
- Mutate metadata — update descriptions, tags, owners, domains, and glossary terms
- Build LangChain or Google ADK agents with pre-built tool bindings
- Set up Snowflake AI agents with one CLI command
Installation
pip install datahub-agent-context
# With LangChain support
pip install "datahub-agent-context[langchain]"
Quickstart
LangChain agent
from datahub.sdk.main_client import DataHubClient
from datahub_agent_context.langchain_tools import build_langchain_tools
client = DataHubClient.from_env()
# Read-only tools (search, lineage, entity details)
tools = build_langchain_tools(client, include_mutations=False)
# Include write tools (tags, descriptions, owners, etc.)
tools = build_langchain_tools(client, include_mutations=True)
# DataHub Cloud: add Ask DataHub AI assistant
from datahub_agent_context.langchain_tools import build_langchain_cloud_tools
tools += build_langchain_cloud_tools(client, ask_datahub=True)
Snowflake AI agent setup
datahub agent create snowflake \
--datahub-url https://your-datahub-instance \
--datahub-token your-token
Available tools
Search — search(), search_documents(), grep_documents()
Entities — get_entities(), list_schema_fields()
Lineage — get_lineage(), get_lineage_paths_between()
Queries — get_dataset_queries()
Mutations — add_tags(), remove_tags(), update_description(), set_domains(), add_owners(), add_glossary_terms(), add_structured_properties(), save_document()
Cloud-only — ask_datahub_chat() (DataHub Cloud AI assistant)
Links
Metadata
Release files for datahub-agent-context 1.7.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| datahub_agent_context-1.7.0.5.tar.gz | 106.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datahub_agent_context-1.7.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 252.5 kB
Release files / datahub_agent_context-1.7.0.5.tar.gz
| Download URL | datahub_agent_context-1.7.0.5.tar.gz |
|---|---|
| Size | 106.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
308033fb2ad8f1c48933fa629d27364b5d66f832a5d7c3032303020baba2e5f0
|
|
BLAKE2b-256 checksum How to use checksums |
de69b9d9a8702e4a7b691f3fdd2719df9f070f71ff062af81f616e7bdbebed11
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
|
Release files / datahub_agent_context-1.7.0.5-py3-none-any.whl
| Download URL | datahub_agent_context-1.7.0.5-py3-none-any.whl |
|---|---|
| Size | 146.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8c07c683426c861e720e59c15881750c37e680f83f23cf8a5b5deec7967c86a0
|
|
BLAKE2b-256 checksum How to use checksums |
f46f287144a3f1a269bf86e3f1924de3f9b4502533240f7f55ad593dc7553740
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
|