{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_a9wnjfevh363","handle":"research-papers-mcp","url":"https://wellknown.network/agents/research-papers-mcp","links":{"self":"https://wellknown.network/agents/research-papers-mcp/record.json","html":"https://wellknown.network/agents/research-papers-mcp","markdown":"https://wellknown.network/agents/research-papers-mcp/record.md","api":"https://wellknown.network/api/v1/agents/research-papers-mcp","status":"https://wellknown.network/api/v1/agents/research-papers-mcp/status","claim":"https://wellknown.network/agents/research-papers-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/research-papers-mcp/claim.json","badge":"https://wellknown.network/agents/research-papers-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json"},"ard":{"identifier":"urn:air::server:research-papers-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"research-papers-mcp","summary":"MCP server for research paper discovery, citation analysis, and trend detection across arXiv, PubMed, and Semantic Scholar","description":"<div align=\"center\">\n\n# research-papers-mcp\n\n**Research paper intelligence for LLMs**\n\nSearch, analyze, and track 200M+ papers from arXiv, PubMed, and Semantic Scholar -- right from Claude, Cursor, or any MCP client.\n\n[![PyPI](https://img.shields.io/pypi/v/research-papers-mcp?style=flat-square&color=blue)](https://pypi.org/project/research-papers-mcp/)\n[![Python](https://img.shields.io/pypi/pyversions/research-papers-mcp?style=flat-square)](https://pypi.org/project/research-papers-mcp/)\n[![License: MIT](https://img.shields.io/badge/License-MIT-green?style=flat-square)](LICENSE)\n[![Tests](https://img.shields.io/github/actions/workflow/status/barissozudogru/deep-research-digest/tests.yml?style=flat-square&label=tests)](https://github.com/barissozudogru/deep-research-digest/actions)\n\n**Live demo:** <https://huggingface.co/spaces/barissozudogru/research-papers-mcp>\n\n</div>\n\n---\n\n- **Federated Search** -- Query arXiv, PubMed, and Semantic Scholar in a single call\n- **Self-Growing Corpus** -- Local SQLite cache grows with every search, enabling richer analysis over time\n- **Zero Config** -- No database servers, no API keys required, no background workers\n- **10 Research Tools** -- From paper discovery to real citation graphs to BibTeX export\n\n## Quick Start\n\n```bash\npip install research-papers-mcp\n```\n\nAdd to your MCP client config (Claude Desktop, Claude Code, Cursor, etc.):\n\n```json\n{\n  \"mcpServers\": {\n    \"research-papers\": {\n      \"command\": \"research-papers-mcp\",\n      \"args\": []\n    }\n  }\n}\n```\n\nThat's it. Start asking your AI about research papers.\n\n> [!TIP]\n> No API keys are required to get started. All three sources work without authentication.\n> A Semantic Scholar API key is optional and only needed for higher rate limits.\n\n## See It in Action\n\n> **You**: Find recent papers on transformer efficiency and model compression\n>\n> **Claude** *(using `search_papers`)*: Found 34 papers across arXiv and Semantic Scholar.\n> 12 new papers cached. Here are the top results …","publisher":null,"homepage":"https://bsozudogru.com","repository":"https://github.com/barissozudogru/deep-research-digest/issues","version":"1.0.0","license":null,"protocols":["mcp"],"tags":["academic-search","arxiv","bibtex","citations","federated-search","mcp","mcp-server","pubmed","research-papers","semantic-scholar"],"pricing":null,"endpoints":[{"url":"pypi:research-papers-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"data.database","name":"Databases","confidence":1,"provenance":"derived"},{"slug":"research.academic","name":"Academic Research","confidence":1,"provenance":"declared"},{"slug":"ai.model-access","name":"Model Access","confidence":0.905,"provenance":"derived"}],"categories":["ai","data","research"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"research-papers-mcp","registry":"pypi","observedAt":"2026-09-10T11:28:26.525Z","publishedAt":"2026-06-01T17:33:05.419243Z","latestVersion":"1.0.0"}},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"research-papers-mcp","url":"https://pypi.org/project/research-papers-mcp/","firstSeenAt":"2026-09-10T11:26:54.095Z","fetchedAt":"2026-09-10T11:26:54.095Z","normalizedAt":"2026-09-10T11:26:54.095Z"}]},"firstSeenAt":"2026-09-10T11:26:54.095Z","updatedAt":"2026-09-10T11:28:26.525Z"}