lex-scholar-api
Single-endpoint MCP server federating nine open-access legal scholarship indexes, enabling federated search, multi-jurisdiction comparison, and full-text retrieval via tools like search_legal_scholarship and compare_jurisdictions.
README
lex-scholar-api
Dependency-free Python client + single-endpoint MCP server federating nine open-access legal scholarship indexes, for the SOCAR L&C agents (Copilot Studio Digital Twin and the Claude Assistant).
Status (2026-07-25): working, 20/20 live tests passing. One
/mcpendpoint, ten upstream indexes, no authentication anywhere, pure Python standard library on a stock Python 3.9+. Built to the same template as the siblingeqanun-apiandresourcecontracts-api.
Why this exists
Peer-reviewed legal scholarship is scattered across national indexes that do not talk to each other: Brazilian doctrine is in SciELO, French in HAL, Spanish in Dialnet, Indonesian and Iranian in DOAJ, US law reviews in Law Review Commons. Asking one comparative-law question meant nine different searches.
This server makes it one call — and, critically, does not fan out blindly. A deterministic router reads the question and picks the 2-3 indexes that can actually answer it.
Two design commitments
One endpoint, many sources. source is a tool parameter, not a deployment.
Adding a tenth index later changes nothing for the agent or the connector.
Multi-jurisdiction by construction. compare_jurisdictions runs one question
across several countries and returns the answers grouped, each routed to its
own native index — the contrast is the deliverable, not a merged ranking.
Sources (all verified live, no auth)
| Source | Law filter | Peer review | Full text | Volume (law) |
|---|---|---|---|---|
| DOAJ — the spine | bibjson.subject.term:law |
guaranteed (review_process) |
abstract + link | 268,222 articles / 1,265 journals |
| Law Review Commons | 67 OAI subject sets | ✗ student-edited | PDF link | 351,887 (oil-gas 845, energy 1,305, arbitration 2,082) |
| SciELO | v440 ⊃ DIREITO/DERECHO |
curated | real body text | 26,003 articles, 36 collections |
| HAL (FR) | domainAllCode_s:shs.droit |
peerReviewing_s flag |
PDF + TEI | 236,486 / 26,422 OA |
| Dialnet (ES) | set=18 Ciencias jurídicas |
mixed | ✗ discovery only | 95,402 |
| DergiPark (TR) | 19 verified law-journal setSpecs | unknown (mostly hakemli) | abstract + link | 19 Turkish law journals |
| OpenAIRE | fos=0505 law |
isPeerReviewed flag |
link | 582,820 |
| Crossref | — | — | — | DOI resolver |
| Unpaywall | — | — | locator | DOI → open copy |
| OpenAlex ⚠ metered | subfields/3308 |
inferred | link | 2,244,618 / 362,231 OA |
peer_reviewed is tri-state on every record: true (source guarantees it),
false (known not to be — preprints, US student-edited law reviews), null
(unknown). Never assume; peer_reviewed_only=true keeps only true.
Install / requirements
None. Pure standard library, Python 3.9+. Optionally set OPENALEX_API_KEY to
raise OpenAlex's metered budget ~100x — everything works without it, and the
router simply holds OpenAlex back when its anonymous budget runs low.
Library
from lexscholar import LexScholarClient
c = LexScholarClient()
# Federated search — the router picks the sources
res = c.search("force majeure", peer_reviewed_only=True, limit=10)
print(res["sources_queried"], res["routing_reasons"])
# One question, several jurisdictions, grouped answers
cmp = c.compare_jurisdictions("stabilization clause", ["FR", "BR", "ID", "TR"])
# Real body text (SciELO), paginated
ft = c.get_fulltext("scielo", "S1806-64452007000100004", collection="scl")
c.resolve_doi("10.1093/jiel/jgaa002")
c.list_sources()
CLI
python3 -m lexscholar search "force majeure" --peer-reviewed --brief -n 10
python3 -m lexscholar search "arbitraje de inversiones" --jurisdiction ES
python3 -m lexscholar compare "stabilization clause" FR BR ID TR
python3 -m lexscholar fulltext scielo S1806-64452007000100004 --out article.txt
python3 -m lexscholar doi 10.1093/jiel/jgaa002
python3 -m lexscholar sources
MCP server
python3 server.py # stdio
python3 server.py --transport http --host 0.0.0.0 --port 8000 # http://<host>:8000/mcp
Env fallbacks: LEXSCHOLAR_MCP_TRANSPORT, LEXSCHOLAR_MCP_HOST, LEXSCHOLAR_MCP_PORT.
Tools
| Tool | Purpose |
|---|---|
search_legal_scholarship |
routed federated search; reports sources_queried, sources_skipped, routing_reasons |
compare_jurisdictions |
one question across N countries, grouped per jurisdiction |
get_scholarship_article |
full normalized metadata by source + id |
get_scholarship_fulltext |
body text, paginated; says so when only a PDF link exists |
resolve_doi |
Crossref metadata + Unpaywall open copy |
list_sources |
capability cards incl. live OpenAlex budget |
Public HTTPS in one command
./run-public.sh # macOS / Linux
.\run-public.ps1 # Windows (PowerShell has no && and cannot run .sh)
Prints a https://<random>.trycloudflare.com/mcp URL. Quick-tunnel hostnames
rotate every run; use a named Cloudflare tunnel for a stable URL.
How routing works
| Signal | Route |
|---|---|
| DOI in the query | Crossref + Unpaywall only — discovery skipped |
jurisdiction= |
that country's native index (BR→SciELO, FR→HAL, ES→Dialnet, AZ→OpenAlex) |
| query language | es/pt→SciELO+Dialnet, fr→HAL, de→OpenAIRE, tr→DergiPark+DOAJ, ru→DOAJ+OpenAlex |
| energy/arbitration vocabulary | + Law Review Commons (suppressed if the query is scoped to a non-US country) |
peer_reviewed_only=true |
drops preprint and student-edited sources |
| OpenAlex budget low | OpenAlex skipped before it 429s, with the reason reported |
| always | DOAJ anchors — except where it demonstrably has nothing (AZ, IN, JP, AE) |
Override with source="doaj,hal" or source="all".
Smoke test
python3 examples/smoke_test.py
20 assertions across routing, federation, peer-review filtering, record shape, multi-jurisdiction comparison, full text, DOI resolution and capability cards.
Verification highlights (2026-07-25)
search_legal_scholarship("stabilization clause", peer_reviewed_only=true)→ top hit "The Stabilization Clause of the Baku-Tbilisi-Ceyhan Pipeline", 0.4s, DOAJ only.compare_jurisdictions("arbitration", [FR,BR,ID,AZ])→ all four answered, each via its own index (hal,scielo,doaj,openalex).- SciELO full text → 57,021 chars of clean article body.
- Five upstreams in parallel = 0.96s wall clock.
Governance
Read-only research over public open-access content. Two obligations travel with
the data and are surfaced on every record via license and citation:
- DOAJ
robots.txtsignalsai-train=no. The API/OAI are separate documented machine interfaces and the metadata is CC0, so retrieve-and-cite is consistent with that signal — model training is not. - Dialnet
dc:rightsrequires express written consent for reproduction, so it is wired as discovery only: citations yes, redistribution no.
Law Review Commons is US student-edited (peer_reviewed=false) — authoritative
practice literature, but never to be presented as peer-reviewed scholarship.
Cite the citation field; it carries source attribution by construction.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。