find-research-papers-mcp

MCP server for scientific grounding: search and discover open-source research papers and scholarly literature across five sources, and pull references/citations from paywalled journals (Nature, Elsevier, IEEE, ACM…) even when the full text is not readable — DOI/abstract/reference metadata is public.

Built to the house pattern (local stdio Python/FastMCP — same architecture as music-mcp).

Sources

¹ Semantic Scholar's shared pool 429s without a key. Set FIND_RESEARCH_PAPERS_MCP_S2_API_KEY in the server's environment to lift the limit. All sources degrade gracefully: a failing/rate-limited source is skipped and reported in the response's skipped list, never a crash.

Related MCP server: Academic Paper MCP HTTP/SSE Server

Tools

• search_papers(query, sources, limit, year_from, year_to, sort, open_access_only) — aggregate search across all (or chosen) sources with a unified hit schema: id, title, authors, year, venue, abstract, doi, url, pdf_url, citations_count, open_access, retracted, type, source. OpenAlex hits carry the known-retraction flag (retracted); other sources leave it null.

• get_paper(identifier, id_type, include_references, include_citations, verify) — resolve one paper by DOI / arXiv ID / PMID / OpenAlex ID / S2 ID (auto-detected from the identifier), plus its references and citations — this is how a paywalled Nature paper still yields a browsable bibliography: Crossref provides the reference list, OpenAlex the citing works. With verify=true (default) the response adds verification: {resolves, retracted, checked_at} — a HEAD liveness check of the landing page (doi.org / arxiv.org / pubmed.ncbi.nlm.nih.gov) plus an OpenAlex retraction cross-check. A target that won't answer reports resolves: null (unknown, never "dead").

• get_research_method() — the house method: tool tiers, rules for interpreting results, per-source quirks, verification steps. Call it before interpreting search results.

• list_sources() — discovery: what is searchable and from where.

Install & run

uv venv .venv --python 3.11
uv pip install --python .venv/bin/python -e .
.venv/bin/python -m papers_mcp          # stdio server

Published installs: uvx find-research-papers-mcp or npx -y find-research-papers-mcp (npm bridge wrapper).

Optional: export FIND_RESEARCH_PAPERS_MCP_S2_API_KEY=... to enable full-rate Semantic Scholar.

Telemetry & Privacy

find-research-papers-mcp collects anonymous usage telemetry (SUR-86 Phase 2), on by default, matching the house pattern:

• What is sent: event names + an anonymous installation UUID + coarse environment signals (OS, Python version, agent name like claude_code/cursor, run context, discovery channel) + tool outcome counts (hits found, sources used, skipped reasons, retracted hits, verification results, latency). Never search queries, paper results, file paths, emails, URLs, or client metadata values.

• Events: server_first_install, package_download (once per version), mcp_started, tools_listed, tool_executed (tool name only), tool_search, tool_get_paper, tool_list_sources, tool_get_research_method.

• Where: a Cloudflare worker gateway (FIND_RESEARCH_PAPERS_MCP_TELEMETRY_URL, defaults to the deployed worker). Opt-out or a dead URL simply means events are dropped — telemetry never blocks or slows the server.

• Opt out any of: FIND_RESEARCH_PAPERS_MCP_TELEMETRY=false, DISABLE_TELEMETRY=1, DO_NOT_TRACK=1, NO_TELEMETRY=1. The install ID lives in ~/.find_research_papers_mcp/installation_id; delete the folder to reset it.

The first run prints a short disclosure to stderr before anything is sent.

Wire into Hermes

Add to ~/.hermes/config.yaml under mcp_servers: (see AGENTS.md), then restart the gateway. search_papers / get_paper / list_sources then appear as native tools.

Tests

.venv/bin/python -m pytest tests/test_sources.py          # offline unit tests
.venv/bin/python -m pytest tests/e2e/test_e2e.py          # native MCP protocol
.venv/bin/python -m pytest -m live tests/e2e/             # live third-party APIs

Playbook status

• Phase 0 — brand scouting (scripts/scout_mcp_brand.py; PyPI/npm/GitHub clear on find-research-papers-mcp)

• Phase 1 — core server (merged to main)

• Phase 2 — telemetry (anonymous, opt-out, e2e-verified against a local capture gateway; gateway worker deployed)

• Wave A — retraction flag, liveness verification, get_research_method, tool-level telemetry events

• Phase 3 — CI + PyPI/npm distribution (release pipeline)

• Phase 7 — dogfood in ≥2 harnesses before v0.1.0