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Import and Export

Import and export are complementary extensions that bridge Directory and external systems. Import brings agent records into Directory from heterogeneous external sources — remote registries as well as local files (JSON A2A Cards, MCP server definitions, Agent Skills directories) — while export transforms stored records out into formats consumed by external tools and agentic CLIs.

Import

Import extends Directory's synchronization capabilities beyond Directory-to-Directory sync to support heterogeneous external sources. It aggregates agent records into the local Directory instance from remote registries as well as local files such as A2A AgentCards, MCP server definitions, and Agent Skills.

How import works

The import system uses source-specific adapters to fetch records from external sources — remote registries or local files — and transform them into OASF-compliant records. Each source kind has its own import logic that handles authentication, pagination, filtering, and data transformation. Records are automatically deduplicated and can be enriched with LLM-powered skill and domain mapping to ensure consistency with the OASF schema.

Translation and enrichment

Records are transformed from external registry data into OASF-compliant format, which directly impacts how records are indexed and discovered across the network. Three methods are available:

  • Basic translation uses OASF-SDK basic translation with rule-based mapping. It is fast and deterministic but produces a record without any skills or domains, requiring manual or LLM-based enrichment afterwards.
  • Static enrichment assigns fixed skills and domains to every record by setting skip_enricher: true in the --config file and listing the taxonomy entries explicitly. No LLM or API credentials are required.
  • Local LLM enrichment runs an LLM locally for intelligent skill and domain mapping, requiring a local LLM runtime.
  • Remote LLM enrichment uses external LLM services for skill and domain mapping, requiring API credentials.

LLM enrichment runs automatically by default (azure:gpt-4o, 2 RPM) and can be customised or skipped entirely via the --config YAML file. Both LLM methods require access to an LLM with tool-calling support and the corresponding provider credentials (for example, Azure OpenAI, or a local model via Ollama). The enrichment pipeline is built into dirctl — it runs the OASF schema tools exposed by dirctl mcp serve against the model. See CLI Reference — Enrichment for provider setup and configuration details.

Supported import kinds

Kind Description Required flag
mcp-registry Model Context Protocol registry v0.1 --url
mcp Local MCP server JSON --file-path
a2a Local A2A AgentCard JSON --file-path
agent-skill Local Agent Skills directory with SKILL.md --file-path

Export

Export is the inverse of import: it pulls stored OASF records and transforms them into formats that external tools and agentic CLIs can consume directly, such as A2A AgentCards, SKILL.md artifacts, or MCP configuration. This lets records published to Directory feed back into the broader agent ecosystem without manual conversion.

How export works

Export retrieves a record by CID or name and runs it through a format-specific transformer. Records can be exported one at a time, or in batches driven by the same search filters used for discovery (--name, --version, --module, --skill, --author, and so on). By default only the latest semver version per name is exported; --all-versions exports every version.

Supported export formats

Format Output Description
oasf .json Raw OASF record JSON (default)
a2a .json A2A AgentCard JSON for Agent-to-Agent protocol interop
agent-skill .md SKILL.md artifact for agentic CLIs (Cursor, Claude Code, etc.)
mcp-ghcopilot .json GitHub Copilot MCP configuration JSON
mcp-claudecode .json Claude Code MCP configuration JSON (.mcp.json mcpServers shape)
mcp-cursor .json Cursor IDE MCP configuration JSON (.cursor/mcp.json mcpServers shape)

Batch behaviour varies by format: a2a and oasf produce one file per record, agent-skill produces one subdirectory per skill, and mcp-ghcopilot / mcp-claudecode / mcp-cursor merge all matched MCP servers into a single configuration file.