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Academic research MCP server — search, extract, and manage papers

Project description

GRaDOS

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Graduate Research and Document Operating System

The enrichment-grade MCP server for academic paper workflows. For science.

GRaDOS gives AI agents (Claude, Codex, Cursor, and similar clients) a single stdio MCP server that can search academic databases, fetch papers through paywalls, parse PDFs into canonical Markdown, and revisit saved papers for citation-grounded writing.

Architecture 🧭

GRaDOS is designed to sit inside an agent research workflow:

  1. Check the local paper library first with search_saved_papers, get_saved_paper_structure, or grados://papers/{safe_doi}
  2. Search remote academic sources in configured priority order
  3. Resolve optional Unpaywall OA locations, then fetch full text through the configured api, browser, optional codex, and scihub routes
  4. Parse PDFs through Docling -> MinerU -> PyMuPDF by default
  5. Save raw PDFs to downloads/, canonical Markdown to papers/, parser provenance sidecars to papers/_parsed/, parser assets to papers/_assets/, semantic search to database/chroma/, lexical FTS fallback to database/fts.sqlite3, and remote metadata to database/remote_metadata/
  6. Re-open saved papers with low-token structure cards and deep-reading windows before citing them

Host agents may use their own reasoning model to plan queries, screen candidates, rerank anchors, judge support, and synthesize prose. GRaDOS does not call that model directly: snippets, scores, evidence grids, comparisons, and audits are navigation material until the agent rereads the canonical paragraph window with read_saved_paper.

For handoff-safe citation work, prepare_evidence_pack materializes canonical blocks from papers/*.md into a persisted pack. A pack becomes current citation evidence only when verify_evidence_pack reports current_valid=true; strict pack audits never search the whole library to silently patch missing evidence.

When external synthesis is enabled, GRaDOS can turn a current-valid evidence pack into a compact host-side ChatGPT Pro packet, save the returned advisory response, and audit it back against the saved packet when linked, otherwise the source pack. The Pro response remains recovery/review material until accepted claims are reread through canonical GRaDOS paragraph windows.

For run-level recovery, a research_run_manifest is a lightweight directory page for one research run. It can link search queries, candidates, extraction/parser receipts, paper_summary, research_checkpoint, evidence_checkpoint, evidence_pack, audit result IDs, canonical anchors, and failure records. It may keep an append-only event ledger plus a redacted config/provenance snapshot; append correction events instead of rewriting past events, and never store secrets. The run manifest is navigation/provenance only and must never replace canonical rereading of papers/*.md or current-valid evidence packs for final citation support.

For evidence-grounded writing, the bundled skill includes references/paper_writing.md as the workflow router. It points host agents to task-specific profiles for experiment/simulation protocols, literature reviews, experiment reports, and manuscripts, plus a mechanics/elastic-metamaterials domain profile. These profiles guide planning, claim matrices, section gates, and delivery checks; they do not create a second evidence source or a separate MCP runtime.

MCP Tools 🔧

Server Tool Description
GRaDOS search_academic_papers Search remote academic databases for paper metadata, DOI deduplication, resumable continuation tokens, and local saved/full-text/summary state. Optional indepth=true materializes returned candidates with the same limit; default config is off.
GRaDOS search_saved_papers Search the local saved-paper library with semantic retrieval, SQLite FTS/BM25 fallback, exact lookup, metadata filters, and hybrid RRF. Returned snippets and Evidence Anchor JSON blocks are screening/reranking material, not citation evidence.
GRaDOS extract_paper_full_text Fetch, parse, QA-check, and save one paper's canonical full text by DOI. If the DOI is already saved, default force_refresh=false returns an already-saved receipt; set force_refresh=true to refetch/reparse.
GRaDOS read_saved_paper Read paragraph windows from one saved paper for canonical deep reading and citation verification. Accepts a DOI, safe DOI, or grados://papers/... URI.
GRaDOS get_saved_paper_structure Return a low-token structure card for one saved paper with preview text, headings, asset summary, and parser provenance summary when available. Use it for screening before deep reading, not as the final citation source.
GRaDOS read_paper_asset List or read parser-generated figures, tables, formulas, page images, and debug/source assets for a saved paper. Images are returned inline only on request and within configured size limits.
GRaDOS import_local_pdf_library Import a local PDF file or directory into the canonical paper store and retrieval index. Returns an import summary plus the first 25 item results.
GRaDOS parse_pdf_file Parse a local PDF into markdown. Without a DOI it returns a truncated preview; with a DOI it saves the paper into the canonical library, materializes the managed PDF when copy_to_library=true, and may return parse_in_progress while GRaDOS continues a durable background parse attempt.
GRaDOS ingest_codex_downloaded_pdf Complete a codex Chrome-extension handoff by validating either downloaded_file_path or one scanned watch-dir candidate, then reuse the same canonical parse/save path. Ambiguous, missing, or invalid candidates are recorded as recoverable failures; long parser runs return in-progress rather than parse failure.
GRaDOS plan_library_pdf_cleanup Dry-run duplicate PDF cleanup under downloads/, reporting noncanonical publisher-name PDFs that have the same hash as a DOI's managed downloads/{safe_doi}.pdf. It never deletes files.
GRaDOS save_paper_to_zotero Save one paper to the configured Zotero library through the Web API, typically for papers that actually support the final answer.
GRaDOS save_research_artifact Persist reusable intermediate outputs such as search snapshots, extraction receipts, evidence grids, compression-safe evidence checkpoints, and run-linked artifacts in the local SQLite state store. Include metadata.research_run_id to attach an artifact to a run manifest.
GRaDOS query_research_artifacts Query previously saved research artifacts by id, kind, or keyword. detail=true returns the full stored content.
GRaDOS prepare_evidence_pack Retrieve candidate anchors, reread canonical blocks from papers/*.md, and persist a minimal evidence_pack artifact with pack hash, block hashes, answerability, and scoped DOI coverage.
GRaDOS read_evidence_pack Restore a persisted evidence pack by pack id or artifact id.
GRaDOS verify_evidence_pack Rebuild canonical block manifests from current papers/*.md and report snapshot/current validity, missing papers, document changes, relocation, and hash mismatches.
GRaDOS preview_external_synthesis_packet Dry-run a compact external-synthesis packet from one current-valid evidence pack without saving artifacts or contacting external services.
GRaDOS prepare_external_synthesis_packet Persist an external_synthesis_packet artifact with verified anchor ids, canonical paragraph coordinates, excerpts, candidate claims, limitations, and prompt hash, returning the host prompt as a regenerable view.
GRaDOS prepare_external_synthesis_from_topic Prepare a fresh evidence pack from a topic and persist a verified external-synthesis packet in one route, returning both pack and packet ids plus the host prompt.
GRaDOS run_external_synthesis Run the default GRaDOS-native ChatGPT Pro browser route: prepare or verify a packet, use the private ChatGPT profile, confirm GRaDOS-validated Pro model and Pro Extended thinking route, capture the advisory response, save it, and audit it before canonical reread. Long generations return a recoverable session receipt.
GRaDOS save_external_synthesis_result Save a host-provided ChatGPT Pro response as advisory external_synthesis_result state linked to its source pack, optional packet, prompt hash, and session metadata. Defaults to audit=true.
GRaDOS audit_external_synthesis_result Audit a saved external synthesis result against its linked packet when available, otherwise its source pack, using structured claims[].anchor_ids as the primary handoff contract while still reporting prose risks.
GRaDOS audit_answer_against_pack Audit draft claims using only evidence items inside one verified pack. It returns verified, minor_distortion, major_distortion, unverifiable, or unverifiable_access verdicts and does not search the full library to fill gaps. Optional include_suggestions=true attaches follow-up planning.
GRaDOS suggest_missing_evidence Suggest follow-up evidence or revision work for non-verified pack-audit claims without changing strict audit results.
GRaDOS manage_failure_cases Record, inspect, and summarize failed fetch, parse, search, or citation attempts. Can also suggest conservative retry steps from local failure memory.
GRaDOS get_citation_graph Return lightweight local citation relationships, including citation neighbors, common references, and reverse citing-paper lookups.
GRaDOS get_papers_full_context Return structured full-context material for context-budgeted saved-paper batches, with token estimates or actual section content for CAG-style deep reading.
GRaDOS build_evidence_grid Build topic- or subquestion-centered evidence grids from the local paper library before drafting. Rows carry reread anchors for agent-side reranking before citation verification, and scoped DOI calls report requested/covered/missing coverage.
GRaDOS compare_papers Extract aligned comparison material across multiple saved papers, focused on methods, results, or full text. Returned excerpts carry per-axis reread anchors and avoid backmatter sections by default.
GRaDOS audit_draft_support Audit draft claims against the local paper library and return first-pass verified, minor_distortion, major_distortion, unverifiable, or unverifiable_access verdicts with candidate evidence snippets, issue types, revision actions, and anchors. candidate_limit controls candidates per claim.

MCP Resources 📚

Resource Description
grados://papers/index Low-token index of all saved papers.
grados://papers/{safe_doi} Canonical overview card for one saved paper.

safe_doi is an opaque GRaDOS paper ID returned by save receipts, search results, or resource URIs. New saves include a short normalized-DOI hash suffix to avoid filename collisions; older IDs such as 10_1234_demo still resolve. Prefer passing the DOI itself or the returned URI instead of deriving a paper ID by replacing DOI punctuation.

Local Paper Library 🗂️

After extraction or import, GRaDOS keeps papers in a visible on-disk layout:

Directory Content Purpose
config.json Runtime configuration One config file for the whole install
papers/ Canonical Markdown papers with YAML front-matter Deep reading, structure cards, and retrieval
papers/_parsed/ Parser provenance sidecars keyed by safe DOI PDF/parser provenance, source/canonical hashes, block mapping, and asset manifest pointers; not citation content
papers/_assets/ Parser-generated assets and manifests Figures, tables, formulas, page images, and source/debug assets fetched with read_paper_asset; not indexed as text
downloads/ Raw .pdf files Archival copies of fetched or imported papers
database/chroma/ ChromaDB collections Built-in semantic retrieval store
database/fts.sqlite3 Rebuildable SQLite FTS5/BM25 index Deterministic lexical fallback and hybrid retrieval candidate generation
database/remote_metadata/ ChromaDB collection Remote paper metadata, fetch status, and browser-resume cache
database/research.sqlite3 Research artifacts and failure memory Evidence packs, run manifests, checkpoints, extraction receipts, and recoverable failure records
research_checkpoints/ checkpoint.json and rendered checkpoint.md files Recoverable indepth research workflow state
paper_summaries/ Query-independent derived paper summaries Navigation and context recovery, never citation evidence
browser/ Managed Chromium, publisher/ChatGPT profiles, session records Browser strategy assets for publisher PDF access and gated ChatGPT external synthesis
models/ Embedding and OCR model caches Runtime assets warmed by setup

Repository Map 🗺️

  • README.md / README.zh-CN.md: primary installation and usage guides
  • .mcp.json: repo-local MCP wiring example
  • .claude-plugin/: native Claude Code plugin manifests
  • .agents/plugins/marketplace.json: repo-hosted Codex marketplace manifest
  • plugin.mcp.json: root plugin-scoped MCP config used by the Claude Code plugin
  • plugins/grados/.codex-plugin/: self-contained Codex plugin bundle used by the marketplace
  • plugins/grados/plugin.mcp.json: plugin-scoped MCP config copied into the Codex bundle
  • skills/grados/SKILL.md: structured research workflow built on top of the MCP tools
  • skills/grados/references/paper_writing.md: evidence-grounded writing workflow router
  • skills/grados/references/writing_profiles/: task profiles for protocols, reviews, reports, and manuscripts
  • skills/grados/references/domain_profiles/: domain-specific writing guardrails, currently including mechanics and elastic metamaterials

Installation 🚀

Option A: uv tool install (recommended)

uv tool install grados
grados setup
grados client install all

This creates ~/GRaDOS/config.json, prepares the visible directory layout, installs managed browser assets, and warms the default Harrier embedding runtime. docling is now included in the default install because the canonical parsing pipeline is Docling-first. MinerU is an optional authenticated cloud parser in the same waterfall; it runs only when MINERU_API_KEY is configured. Use grados auth set <provider> to store API keys in the OS keychain. Plaintext keys placed in config.json are treated as a one-time import path and are cleared after a successful migration.

Option B: extras, zero-install, or pip

# Default install (includes Docling)
uv tool install grados

# Zero-install run
uvx grados version

# Traditional Python install
pip install grados

Extras in the current package:

  • grados: core MCP server, CLI, ChromaDB storage, Docling-first parser, optional MinerU cloud fallback, PyMuPDF fallback, browser automation, and built-in Zotero save support
  • grados[docling]: compatibility alias for the built-in Docling runtime
  • grados[marker]: compatibility alias only; Marker is no longer bundled because the current marker-pdf release pins vulnerable parser dependencies
  • grados[full]: compatibility alias only

Option C: from source

git clone https://github.com/STSNaive/GRaDOS.git
cd GRaDOS
uv sync --all-extras
uv run grados setup
uv run grados client install all
uv run grados status

Quick Start ⚡

  1. Install GRaDOS with uv tool install grados (this now includes Docling by default)
  2. Run grados setup
  3. Run grados client install all to register Claude Code and Codex in one step
  4. Run grados auth set elsevier (and any other providers you need)
  5. Run grados status to confirm dependencies, browser assets, keychain health, and API-key sources
  6. If you already have a PDF library, run grados import-pdfs --from /path/to/papers --recursive
  7. If you are upgrading from an older MiniLM-backed index, run grados reindex once before semantic search

Configure your clients 🔌

Recommended:

grados client install all

This currently installs GRaDOS into both Claude Code and Codex:

  • registers the grados MCP server through each client's own CLI
  • copies the bundled grados skill into the user's skills directory

You can also target a single client:

grados client install claude
grados client install codex
grados client list
grados client doctor

Manual MCP wiring (fallback)

Claude Code / Claude Desktop:

{
  "mcpServers": {
    "grados": {
      "command": "uvx",
      "args": ["grados"]
    }
  }
}

Codex:

[mcp_servers.grados]
command = "uvx"
args = ["grados"]

Use uvx when you want zero-install MCP launching. For long-lived local use, uv tool install grados plus the grados executable remains the primary path, and now brings Docling with it by default. If you want a custom data root, set GRADOS_HOME in your MCP client's environment.

Native Plugin Install 🧩

GRaDOS now ships native plugins for Codex and Claude Code.

Claude Code:

/plugin marketplace add STSNaive/GRaDOS
/plugin install grados@grados-plugins
/reload-plugins

Codex:

codex plugin marketplace add STSNaive/GRaDOS
codex
/plugins

Then choose the GRaDOS Plugins marketplace, install the GRaDOS plugin, and start a new thread. You can call @grados explicitly or just describe the research task directly.

Companion Skill 🤖

GRaDOS still ships a repo-local skill in skills/grados/. The grados client install ... flow above is now the preferred path for local use. Plugin install remains the alternative when you specifically want the native plugin packaging.

  • skills/grados/SKILL.md contains the current search -> structure -> deep read -> cite -> verify workflow
  • skills/grados/references/tools.md documents the current MCP tools and 2 resources
  • skills/grados/references/paper_writing.md routes evidence-grounded writing tasks to focused profiles for protocols, reviews, reports, and manuscripts
  • skills/grados/agents/openai.yaml describes the OpenAI / Codex-facing dependency on the grados MCP server

Codex and Claude Code use the same skill directory shape, <skills-root>/grados/SKILL.md, with the same supporting files under that directory. Only the skills root differs:

  • Codex personal skills: ~/.agents/skills
  • Claude Code personal skills: ~/.claude/skills
  • Claude Code project skills: .claude/skills

Install it by copying the entire skills/grados/ directory into the appropriate skills root:

mkdir -p "<skills-root>"
cp -R skills/grados "<skills-root>/"
  • For Codex, set <skills-root> to ~/.agents/skills
  • For Claude Code personal skills, set <skills-root> to ~/.claude/skills
  • For Claude Code project skills, set <skills-root> to .claude/skills

This fallback assumes the grados MCP server is already registered in your client. This repository's .mcp.json is the minimal repo-local example; after copying the skill, reload your client so it can discover the new skill files.

Configuration ⚙️

Keep grados-config.example.json as the commented reference; edits take effect on the next CLI run or MCP server restart.

Research Workflow Knobs

  • research.indepth: disabled by default; controls whether remote search immediately materializes returned candidates for checkpointed full-text review.
  • research.external_synthesis: disabled by default; a GRaDOS-native ChatGPT Pro browser reviewer/synthesizer with only enabled. Gate automation with grados external-synthesis is-enabled --quiet; inspect details with grados external-synthesis status --json; initialize the private profile with grados external-synthesis setup-browser. When enabled, GRaDOS can prepare verified external-synthesis packets, use its private ChatGPT browser profile, save returned advisory responses, and audit them against the linked packet or source pack. When this is off, GRaDOS does not call ChatGPT, open Chrome, or change evidence reading.

Timeout / Retry Knobs

  • search: connect_timeout, read_timeout
  • extract: fetch_connect_timeout, fetch_read_timeout, pdf_read_timeout
  • extract.headless_browser: legacy-named config section for the browser strategy (deadline_seconds, networkidle_timeout, pdf_backfill_timeout, poll_min_seconds, poll_max_seconds)
  • extract.codex_handoff: watch-dir ingest controls used only after a codex Chrome-extension handoff (download_watch_dir, download_max_age_seconds, download_settle_seconds, download_settle_max_wait_seconds, download_scan_recursive)
  • retry_policy: max_attempts, max_wait, respect_retry_after

Size Guards

  • extract.security: byte ceilings for remote PDFs, remote text/XML/HTML responses, local PDFs, browser PDF captures, MinerU result zips, and MinerU full.md. Defaults are intentionally generous for normal paper PDFs; raise them only for trusted oversized inputs.
  • extract.assets: controls parser asset bundles under papers/_assets/{safe_doi}/ (mode=all|referenced|none), Docling image scale, per-file/total asset size ceilings, inline image ceiling, and max asset count. Asset bytes are stored beside canonical Markdown and are fetched with read_paper_asset, not indexed into Chroma.

Commands 🧰

Command Purpose
grados Start the MCP stdio server
grados setup Create directories, write config.json, install browser assets, and warm models
grados client install claude Register GRaDOS in Claude Code and install bundled skills into ~/.claude/skills
grados client install codex Register GRaDOS in Codex and install bundled skills into ~/.agents/skills
grados client install all Install GRaDOS into both Claude Code and Codex
grados client list Show which supported clients currently have GRaDOS installed
grados client doctor Run a lightweight health check for supported clients
`grados client remove claude codex
grados auth set/status/migrate/clear Manage provider API keys in the OS keychain
grados browser status --json Inspect the publisher PDF browser runtime, managed executable, profile status, lock, and session directory
grados browser doctor [--live --doi DOI] Check publisher browser prerequisites; --live runs a PDF-acquisition probe without saving papers/*.md
grados external-synthesis is-enabled --quiet Predicate gate for the optional external synthesis protocol; exit 0 means enabled, exit 1 means disabled
grados external-synthesis status --json Show the same external synthesis gate plus config path details as structured diagnostics; profile initialization means Chrome profile markers only, not ChatGPT login readiness
grados external-synthesis setup-browser [--keep-open] Open the private GRaDOS ChatGPT profile for first-time ChatGPT login; closes after stable login detection by default, while --keep-open keeps the command and profile lock alive until the setup browser closes
grados external-synthesis doctor [--live] Check external synthesis browser prerequisites; --live also probes ChatGPT login
grados import-pdfs --from /path/to/papers --recursive Import an existing local PDF library into the canonical paper store
grados eval-retrieval --fixture cases.jsonl Evaluate saved-paper retrieval against local golden cases using dense, FTS/BM25, exact lookup, and RRF unless --dense-only is set
grados status Show config, dependency, runtime-asset, and API-key health
grados paths Show the resolved GRaDOS filesystem layout
grados update-db Incrementally refresh the ChromaDB index from papers/ when the active indexing config is unchanged
grados reindex Rebuild the semantic index from scratch after embedding-model or chunking changes
grados version Show package versions

If you change indexing.model_id, indexing.max_length, or the section-aware chunking settings in config.json, use grados reindex instead of grados update-db.

Changing only indexing.batch_size is a runtime-only tuning knob and does not require a rebuild.

Indexing Defaults 🧠

  • Default model: microsoft/harrier-oss-v1-270m
  • Heavier opt-in model: microsoft/harrier-oss-v1-0.6b
  • Default indexing.max_length: 4096
  • Default indexing.batch_size: 0 (auto, conservative on CPU/MPS and wider on CUDA)
  • Overlong single paragraphs are re-split by sentence or clause before embedding so grados reindex does not send giant chunks into SentenceTransformer.encode()

GRaDOS does not assume FlashAttention is available on local macOS / CPU setups. If your runtime says it can use SDPA, that still does not guarantee a fused CUDA FlashAttention path; the safer default is smaller chunks, a shorter indexing length, and conservative batching.

Filesystem Layout 🗄️

By default, GRaDOS keeps everything in a visible directory:

~/GRaDOS/
├── config.json
├── papers/
├── downloads/
├── browser/
│   ├── chromium/
│   ├── profile/
│   ├── pdf-sessions/
│   ├── chatgpt-profile/
│   ├── chatgpt-sessions/
│   └── extensions/
├── models/
├── database/
│   ├── chroma/
│   └── remote_metadata/
├── logs/
└── cache/

Root selection priority:

  1. GRADOS_HOME
  2. ~/GRaDOS

Local PDF tools such as parse_pdf_file, ingest_codex_downloaded_pdf(downloaded_file_path=...), and import_local_pdf_library read host file paths from a trusted local MCP/CLI session and enforce extract.security.max_local_pdf_bytes before and while loading the file.

API Keys 🔑

Key Source Required
ELSEVIER_API_KEY Elsevier Developer Portal No
PUBMED_API_KEY NCBI E-utilities API key No
WOS_API_KEY Clarivate Developer Portal No
SPRINGER_meta_API_KEY Springer Nature Metadata API No
SPRINGER_OA_API_KEY Springer Nature Open Access API No
MINERU_API_KEY MinerU API token No
ZOTERO_API_KEY Zotero Settings -> Keys No

Crossref works without an API key. PubMed also works without one, but PUBMED_API_KEY is available as an optional pacing upgrade for E-utilities. GRaDOS will use whichever services are configured and skip the rest; the default remote search flow still works with the free sources, and the local paper workflow works without any third-party key.

The preferred path is grados auth set <provider>, which stores the secret in the OS keychain. If you temporarily place a plaintext key in ~/GRaDOS/config.json, GRaDOS will import it into the keychain on the next run and then clear the plaintext value from the file.

Runtime Order 🌊

Search priority:

{
  "search": {
    "order": ["Elsevier", "Springer", "WebOfScience", "Crossref", "PubMed"]
  }
}

Full-text fetch priority:

{
  "extract": {
    "fetch_strategy": {
      "order": ["api", "browser", "codex", "scihub"],
      "enabled": {
        "api": true,
        "browser": true,
        "codex": false,
        "scihub": true
      }
    },
    "unpaywall": {
      "enabled": true
    }
  }
}

Unpaywall is an optional DOI-to-OA-location resolver, not a download strategy. When extract.unpaywall.enabled=true, GRaDOS resolves best_oa_location / oa_locations before codex or browser runs and uses the best url_for_pdf or url_for_landing_page as that route's start URL. It does not affect the api or scihub routes. Legacy oa entries left in old fetch_strategy.order or enabled maps are ignored.

Legacy fetch-strategy aliases such as TDM, SciHub, and Headless are still accepted while existing configs migrate. The current scihub runtime uses extract.sci_hub.endpoints as an ordered access list: the first endpoint is tried first, and later entries are fallbacks. The legacy extract.sci_hub.fallback_mirror value is still accepted when endpoints is omitted or empty.

The browser strategy is a first-class path for institutional publisher access. It uses the GRaDOS-managed publisher profile (browser/profile), profile locking, operational PDF browser session records under browser/pdf-sessions, and response/download/CDP/backfill PDF capture. Browser acquisition never writes papers/*.md directly: it returns PDF bytes or a challenge plus browser capture metadata, then extract_paper_full_text sends the PDF through the normal materialization, parser, QA, and canonical Markdown persistence pipeline. Retained browser windows keep manual/challenge pages open while each DOI gets a job-owned page. If a publisher verification page blocks PDF capture, GRaDOS records a challenge with manual-resume metadata in remote_metadata; complete the verification in the managed browser profile, then call extract_paper_full_text again with resume_browser=true to continue from the saved browser URL/profile instead of restarting at api.

codex is disabled by default. When enabled and placed in extract.fetch_strategy.order, it acts as a Codex Chrome extension host-agent handoff at that exact point in the order: extract_paper_full_text returns a Chrome download receipt, then the host agent uses the Codex @chrome plugin / Codex Chrome extension as the acquisition route. If the host knows the absolute PDF path, call ingest_codex_downloaded_pdf(doi=..., downloaded_file_path=...) or parse_pdf_file(file_path=..., doi=..., copy_to_library=true, acquisition_via="codex"); otherwise ingest_codex_downloaded_pdf scans extract.codex_handoff.download_watch_dir. That watch dir is scan-only: it does not configure Chrome, and an empty scan means pass the real path rather than click the publisher download button again. If a DOI-bound local parse exceeds extract.parsing.foreground_wait_seconds, GRaDOS returns a parse_in_progress receipt, keeps the background parse attempt running, and later reconciles repeated calls by DOI plus PDF hash; do not redownload the PDF just because the foreground call returned before MinerU or another parser finished. If Unpaywall finds an OA URL, the receipt starts from that URL instead of https://doi.org/{doi}.

All PDF acquisition routes that copy into the library now share one materialization boundary. The managed raw PDF for a DOI is downloads/{safe_doi}.pdf; publisher filenames and external local PDFs are acquisition inputs. Same-DOI same-hash candidates reuse, rename, or copy to the managed path. Same-DOI different-hash candidates return a conflict receipt that keeps both the existing canonical PDF and the candidate input. PDF fetches are parsed and QA-checked before ordinary fulltext success; parser QA failures continue through configured parser/fetch fallbacks, and unresolved QA failures are saved only as partial_success. New papers/*.md frontmatter keeps only reading metadata and pointers such as parsed_manifest_path / assets_manifest_path; PDF paths, hashes, acquisition route, and parser/materialization provenance live in the receipt, remote_metadata.fetch_via, and papers/_parsed/{safe_doi}.json.

If research.external_synthesis.enabled=true, GRaDOS may use ChatGPT Pro only after it has prepared and verified an evidence pack. The default tool is run_external_synthesis: from a topic it prepares the evidence pack and packet, from an existing pack id it verifies and packets that pack, then it opens the dedicated GRaDOS ChatGPT profile, verifies GRaDOS-validated Pro model route (gpt-5.5-pro) and Pro Extended thinking route before sending, captures the response, saves it with save_external_synthesis_result(audit=true), and returns the audit and canonical reread next action. If ChatGPT generation exceeds the foreground wait, the tool returns recoverable=true with browser_session_id so a later call can pass recover_session_id. preview_external_synthesis_packet, prepare_external_synthesis_from_topic, prepare_external_synthesis_packet, save_external_synthesis_result, and audit_external_synthesis_result remain available for dry runs, recovery, and explicit reruns. When a packet id is linked, audit accepts only anchors, DOIs, block ids, and canonical URIs from that saved packet; structured claims[].anchor_ids are the primary claim contract, and prose audit output is retained as a risk scan. Model and thinking choices are fixed protocol defaults, not configurable GRaDOS keys. In localized ChatGPT UIs, GRaDOS records the raw labels it confirmed. This does not remove the separate extract.fetch_strategy.codex PDF acquisition route.

PDF parsing priority:

{
  "extract": {
    "parsing": {
      "order": ["Docling", "MinerU", "PyMuPDF"],
      "enabled": {
        "Docling": true,
        "MinerU": true,
        "PyMuPDF": true
      },
      "foreground_wait_seconds": 90.0,
      "attempt_stale_seconds": 1800.0
    }
  }
}

MinerU is an authenticated cloud parser. When enabled and MINERU_API_KEY is present, GRaDOS uploads the local PDF through MinerU's signed upload API, polls for the extraction zip, reads full.md as the parser output, and saves allowed images, tables, formulas, page/debug files, and source JSON into the paper's asset bundle. GRaDOS enforces extract.security.max_mineru_zip_bytes, extract.security.max_mineru_full_md_bytes, and extract.assets.* size/count limits before exposing assets. Use grados auth set mineru to store the token in the OS keychain.

extract.parsing.foreground_wait_seconds controls how long parse_pdf_file(file_path=..., doi=...) waits for canonical save before returning parse_in_progress; the parser keeps running in a GRaDOS-owned background attempt. extract.parsing.attempt_stale_seconds controls when an inactive running attempt or retryable failed attempt can be restarted from the same local PDF path. These settings do not change individual parser timeouts such as mineru_timeout.

Importing Existing PDF Libraries ♻️

If you already have a local PDF library, use grados import-pdfs to parse and copy those files into the canonical papers/ + downloads/ layout:

grados import-pdfs --from /path/to/papers --recursive
grados status

Development 🛠️

uv sync --all-extras
uv run grados version
uv run pytest
uv build

Project Docs 📚

  • ADR.md
    • Records accepted architectural decisions and why the project chose them.
  • CHANGELOG.md
    • Records completed, user-visible changes across releases and unreleased work.

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