MCP service · curated database · soon-open-source extraction toolchain. Built for serious CV/ML researchers. Plug into Claude Code; survey a field in 5 minutes, drill into any paragraph in any paper, compare methods and experimental data across 100+ papers in one call.
Venues covered: CVPR · ICCV · ECCV · ICLR · ICML · NeurIPS · AAAI · ACL · EMNLP · NAACL · IJCAI · WACV · BMVC · 3DV · SIGGRAPH · TPAMI · IJCV · Refreshed weekly.
Designed for the way researchers actually work in 2026: an LLM agent at your fingertips, doing the reading. We give that agent the knowledge base — pre-distilled, structured, cite-locked.
One MCP connection grants your agent search, quote, compare_methods, find_baselines, survey, trends, narrative_threads, get_figure, bibtex and 8 more — designed per Anthropic's tool-design guidelines with defer_loading.
21K papers from CV/ML top venues, distilled with GPT-5.5 and Opus-4.7 against open schema v1.2 — 7-class contribution taxonomy + 6-field narrative arc + dataset/metric grids + figure metadata. Hybrid retrieval: BGE-1024 dense + BM25 + RRF + Qwen3 cross-encoder reranking.
Schema spec, distillation prompts (Opus / GPT-vision), Marker/PyMuPDF figure extraction, LanceDB + SQLite FTS5 index builder, citation graph resolver, FastMCP server — all releasing Apache 2.0. Cards as CC-BY-SA dataset (Hugging Face). Ingest your lab's private papers, expose to your team.
Optimized for agent consumption per Anthropic best practices: every tool has explicit "when to use" + "when NOT to use" clauses, deferred tools auto-discovered via discover_tools.
Connect from Claude Code (or any MCP-compatible agent). Replace YOUR_KEY after requesting access.
Other MCP clients (Codex, custom LangChain agent): plain HTTP + JSON-RPC over streamable-http transport. Auth via X-API-Key header or Authorization: Bearer.
# in your terminal claude mcp add \ --transport http \ -s user \ litscan-rag \ https://mcp.acceptpaper.com/mcp \ -H "X-API-Key: YOUR_KEY"
# in a Claude Code session > Survey sparse-view 3D human reconstruction > papers from 2024–2026. Identify dominant > method families, anchor papers, key > benchmarks, and emerging directions. # Claude internally: # 1. calls survey(topic, k=50) → field map # 2. trends(topic) → temporal signal # 3. quote(...) on contested claims # 4. find_baselines(top-3) for comparison # → returns synthesized answer with cites
Existing tools were designed for human eyes on a webpage. acceptpaper was designed for an LLM agent acting on your behalf.
| Capability | acceptpaper | PaperQA2 | Elicit | OpenScholar |
|---|---|---|---|---|
| MCP-native (agent interface) | ✓ | — | — | — |
| Pre-distilled structured schema | v1.2 (7-class + 6-field) | flat text | semi-struct | flat |
| Paragraph-level retrieval | 1.15M chunks | ✓ | ✓ | ✓ |
| Figure retrieval (hero JPG) | 16K | v3 only | — | — |
| Citation graph (resolved) | 365K edges | tool | partial | via S2 |
| Venue-tier-aware ranking | ✓ | — | — | — |
| Cost per query (retrieval) | $0 | $0.05–2 | $0.01–.50 | ~$0.10 |
| Domain focus | CV/ML top-tier | biology-heavy | broad | broad |
| Open source license | Apache 2.0 (in prep) | ✓ Apache | closed | ✓ Apache |
| Self-hostable for lab corpus | soon | ✓ | — | partial |
A paper is more than text. Our distillation produces 30+ structured fields per paper — 7-class contribution taxonomy, 6-field narrative arc, eval datasets with numeric values + SOTA flags, baseline comparison strings, key modules, hero figure metadata. Agents read exactly the slice they need without re-parsing PDFs every query.
// excerpt of one L2 card { "source_id": "cvf:CVPR.2026:1024", "title": "DiHuR: Diffusion-Guided Generalizable Human Reconstruction", "contribution_type": { "primary": "combination", "secondary": ["empirical_study", "ablation_heavy"] }, "narrative": { "problem": "Reconstructing detailed 3D humans from ~3 sparse cameras…", "insight": "SMPL vertices map to consistent semantic regions…", "evidence": "CD 1.117 vs GP-NeRF 3.876 on THuman; gains hold on ZJU-MoCap" }, "eval_data": [ {"name":"THuman","metric":"Chamfer Distance","value":1.117,"is_sota":true}, // + 9 more entries ], "compares_with": ["NeuS", "SparseNeuS", "PIFuHD", "GP-NeRF", "SIFU"], "hero_figure": {"page":1, "caption":"Given 3 views with minimal overlap…"} }
The hosted service stays free for academic use. The toolchain ships open-source so any lab can self-host their own corpus.
Free API key for academic / research use. We ask only that you tell us briefly who you are and what you're working on — to prioritize features and venue coverage.
Request an API keyTypical reply within 24h.