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generate-connector-spec

17
databrickslabsdatabrickslabs

Generate the connector spec YAML file defining connection parameters and external options allowlist.

195 days ago

validate-incremental-sync

17
databrickslabsdatabrickslabs

Validate that a connector's CDC/incremental sync implementation correctly tracks offsets and filters records.

195 days ago

test-and-fix-connector

17
databrickslabsdatabrickslabs

Validate a connector by running the test suite, diagnosing failures, and applying fixes until all tests pass.

195 days ago

create-connector-document

17
databrickslabsdatabrickslabs

Generate public-facing documentation for a connector targeted at end users.

195 days ago

write-back-testing

17
databrickslabsdatabrickslabs

Implement test utilities that write test data to the source system and validate end-to-end read cycles.

195 days ago

implement-connector

17
databrickslabsdatabrickslabs

Implement a Python connector that conforms to the LakeflowConnect interface for data ingestion.

195 days ago

FAQ

AgentCC is a discovery hub for AI agent capabilities. We index Agent Skills as the primary dataset, and also organize MCP servers and selected AI tools so developers can quickly find, compare, and evaluate what to integrate into their workflows.
An Agent Skill is a reusable capability package for an AI agent. It can define workflows, tool usage patterns, domain knowledge, or execution rules that help the agent perform more reliably in a specific task or environment.
AgentCC is a resource and discovery layer, not a one-click installer. On each skill page, you should review the repository, file tree, install command, and usage notes, then integrate it according to the runtime or client you are using.
No. AgentCC primarily indexes external repositories and metadata. We help you understand what a skill is, where it comes from, and how it may be used, but execution and security decisions still belong to your own runtime environment.
No directory can guarantee absolute safety. AgentCC can help surface repository links, file structures, and metadata, but you should still verify permissions, external dependencies, API usage, and code quality before using a skill in production or on sensitive machines.
Yes. AgentCC is designed to be an evolving resource graph. As the submission and curation workflow matures, contributors will be able to recommend high-quality skills, MCP servers, and AI tools into the directory.
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