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by lourencomaciel • Uncategorized
A reliability gateway that ensures schema-stable, secret-safe, and pagination-complete JSON output for AI tool and MCP client outputs.
Handle large and paginated JSON outputs reliably without losing data or context.
Run exact structured queries over stored tool outputs using Python code.
Secret-safe, schema-stable, and reproducible AI tool output management.
Sift acts as a drop-in reliability layer for MCP and CLI tool outputs by persisting full JSON payloads as artifacts and returning either inline payloads or compact schema references. It enables agents to query stored data precisely using Python code, improving accuracy and reducing input token usage significantly. Sift also handles pagination explicitly, secret redaction, and schema-aware references without changing upstream servers, enhancing reliability and reproducibility in multi-step AI workflows.
Gateway health and configuration snapshot.
Inspect one registered tool and return its full description, tools/list description, and optional input schema.
Interact with stored artifacts. Actions: query, next_page, blob_list, blob_materialize, blob_cleanup, blob_manifest. Use action="query" with query_kind="code" to run Python over stored artifacts. Code-query packages: stdlib-only. Use action="next_page" to fetch additional upstream pages for a paginated artifact. Use action="blob_list" to discover linked blobs without returning bytes. Use action="blob_materialize" to stage one blob as a local file path for downstream tools. Use action="blob_cleanup" to remove staged blob files from allowed local staging roots. Use action="blob_manifest" to export blob metadata to local CSV/JSON files. Do not claim completeness until pagination.retrieval_status == COMPLETE.
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