This release is a pre-release and may not be stable for production use.
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()
Incidents — list_incidents()
Mutations — add_tags(), remove_tags(), update_description(), set_domains(), add_owners(), add_glossary_terms(), add_structured_properties(), save_document(), raise_incident(), resolve_incident()
Cloud-only — ask_datahub_chat() (DataHub Cloud AI assistant)
Links
1 maintainer
Metadata
1 maintainer
Release files for datahub-agent-context 1.7.0.15rc4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| datahub_agent_context-1.7.0.15rc4.tar.gz | 111.4 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| datahub_agent_context-1.7.0.15rc4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 263.1 kB
Release files / datahub_agent_context-1.7.0.15rc4.tar.gz
| Download URL | datahub_agent_context-1.7.0.15rc4.tar.gz |
|---|---|
| Size | 111.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f47ace9a84d1acf13401c2811f0b59234f750a6705eb0b37deed583f0bb0e4bf
|
|
BLAKE2b-256 checksum How to use checksums |
77de70fae27480672da8b67c20e6fb62e764f8c861972b706f84d235518b2e3f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.22
|
Release files / datahub_agent_context-1.7.0.15rc4-py3-none-any.whl
| Download URL | datahub_agent_context-1.7.0.15rc4-py3-none-any.whl |
|---|---|
| Size | 151.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b3d7f5c788db0d6762d91ad2eeaddd17d0423121517cf084845ffef184f36d00
|
|
BLAKE2b-256 checksum How to use checksums |
762df5cfdf2c6a2433939950ffa62e8de8f53af33548115f1f4e882e63c5f4c6
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.22
|
Security for datahub-agent-context 1.7.0.15rc4
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
