{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_zr7w3mhenmm4","handle":"aletheia-mcp","url":"https://wellknown.network/agents/aletheia-mcp","links":{"self":"https://wellknown.network/agents/aletheia-mcp/record.json","html":"https://wellknown.network/agents/aletheia-mcp","markdown":"https://wellknown.network/agents/aletheia-mcp/record.md","api":"https://wellknown.network/api/v1/agents/aletheia-mcp","status":"https://wellknown.network/api/v1/agents/aletheia-mcp/status","claim":"https://wellknown.network/agents/aletheia-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/aletheia-mcp/claim.json","badge":"https://wellknown.network/agents/aletheia-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/aletheia-mcp/history","tools":"https://wellknown.network/api/v1/agents/aletheia-mcp/tools"},"ard":{"identifier":"urn:air::server:aletheia-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"aletheia-mcp","summary":"MCP server for scientific literature research. Search 250M+ papers, traverse citation graphs, and extract full text — powered by OpenAlex.","description":"# aletheia-mcp\n\nAn MCP server that gives AI agents structured access to scientific literature — 250M+ papers indexed via OpenAlex, covering arXiv, PubMed, Crossref, and more — so they can do research, not just search.\n\n## The gap this fills\n\nTools like Elicit, Consensus, and SciSpace are great but they're standalone chat apps. You ask one question, you get one answer. You can't chain operations.\n\nWith aletheia-mcp running in Claude or any MCP-compatible client, you can ask things like:\n\n> \"I'm reviewing literature on mitochondrial dysfunction in Parkinson's. Find the 20 most-cited papers from the last 5 years, pull the full text of the three most influential, identify the exact mechanisms they propose, and flag any that contradict each other.\"\n\nUnder the hood, Claude chains multiple tool calls — search, fetch metadata, walk citations, download and parse full PDFs — and synthesizes. That's the difference between search and research.\n\n## Tools in v0.3.0\n\n- `search_papers(query, limit)` — unified search across the OpenAlex corpus\n- `get_paper_details(paper_id)` — full metadata for any paper by OpenAlex ID, DOI, PubMed ID, or URL\n- `get_citation_graph(paper_id, direction, limit)` — walk citations forward (`direction=\"citations\"`) or references backward (`direction=\"references\"`)\n- `get_paper_full_text(paper_id)` — **new in v0.3** — fetches and extracts the full text of any open-access paper. Handles arXiv, PubMed Central, and direct publisher PDFs. Falls back gracefully when no OA version is available.\n\nAll paper-returning tools use a normalized shape: `{id, title, abstract, authors, year, citation_count, venue, doi, url, pdf_url, source}`. The full-text tool adds `text` and `char_count`.\n\n## Why OpenAlex (not Semantic Scholar)\n\nEarlier iterations used Semantic Scholar. The free API key there is gated and institution-preferred — independent developers face slow or rejected applications, which meant future users of this tool would hit the same wall.\n\n[OpenAlex](https://…","publisher":{"name":"TechFusion","url":null},"homepage":"https://github.com/TechFusionData/aletheia-mcp","repository":"https://github.com/TechFusionData/aletheia-mcp/releases","version":"0.3.0","license":"MIT License  Copyright (c) 2026 TechFusion  Permission is hereb…","protocols":["mcp"],"tags":["mcp","model-context-protocol","openalex","research","scientific-literature","citation-graph","academic-search","pdf-extraction","llm-tools"],"pricing":null,"endpoints":[{"url":"pypi:aletheia-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi","publisherName":"pypi"}},"derived":{"capabilities":[{"slug":"research.academic","name":"Academic Research","confidence":1,"provenance":"derived"},{"slug":"knowledge.knowledge-graph","name":"Knowledge Graphs","confidence":0.997,"provenance":"derived"},{"slug":"documents.extraction","name":"Data Extraction","confidence":0.713,"provenance":"derived"}],"categories":["documents","knowledge","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":"aletheia-mcp","registry":"pypi","observedAt":"2026-10-21T17:27:13.527Z","publishedAt":"2026-04-22T23:41:27.418709Z","latestVersion":"0.3.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"aletheia-mcp","url":"https://pypi.org/project/aletheia-mcp/","firstSeenAt":"2026-09-09T08:22:06.926Z","fetchedAt":"2026-10-21T17:24:55.098Z","normalizedAt":"2026-10-21T17:24:55.098Z"}]},"firstSeenAt":"2026-09-09T08:22:06.926Z","updatedAt":"2026-10-21T17:27:13.527Z"}