Research Deposition MCP
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- FlicenseNot gradedqualityAmaintenanceEnables deterministic, harness-neutral research workflows by unifying research object identity, evidence receipts, claim-evidence graphs, and append-only decision logs, along with specialized scholarly skills for literature analysis, reproducibility audits, and multi-agent review.1-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to operate DSpace repositories through a typed interface, including SAF package building, metadata editing, scientometric harvesting, open-access PDF downloads, and repository administration.MIT
- AlicenseAqualityCmaintenanceEnables searching HAL and preparing, validating, and submitting publication deposits via SWORD, with dry-run validation and explicit submission control.14MIT
- AlicenseNot gradedqualityAmaintenanceEnables searching Zenodo records, resolving DOIs and URLs, tracing version series and funding, listing files, and previewing text file contents (including inside ZIP archives) over MCP.47 npm1Apache 2.0
- FlicenseNot gradedqualityBmaintenanceEnables AI agents to validate deliverables (JSON, ZIP, PDF, DOCX) against signed contracts, generating verifiable receipts with Ed25519 signatures.-
- AlicenseAqualityAmaintenanceEnables AI agents and MCP clients to run research as an explicit scientific process: forming hypotheses, designing and executing sealed experiments, capturing observations and artifacts, linking claims to supporting evidence, and reviewing provenance. Exposes coordinated MCP services so users can inspect, reproduce, and audit every step from question to conclusion rather than trusting an opaque final answer.462,530 PyPI2Apache 2.0
TDQS
Scored across 10 tools
Each tool has a clearly distinct responsibility in the deposition lifecycle—status, validation, manifest building, package building, draft creation, retrieval, update, file upload, review, and publication. Even the two validation-related tools (validate_deposition and create_draft) are separated by action, and descriptions clarify their boundaries.
Most tools follow a consistent verb_noun pattern (validate_deposition, build_file_manifest, create_draft, upload_file, publish_draft), but a few use noun-first names (deposition_status, publication_review) that break the pattern slightly. This is a minor deviation and does not impede understanding.
With 10 tools covering the complete deposition workflow, the count is well within the ideal 3-15 range. Each tool serves a necessary, non-redundant role in the pipeline, and none feel extraneous.
The tool set covers the full deposition lifecycle: validation, manifest/package building, draft creation/retrieval/update, file upload, review, and publication. There are no obvious gaps for the stated purpose—only minor absent operations like listing or deleting drafts, which are not critical to the core workflow.