S
sanikacentric/biolit-mcp
无 SECURITY.md
在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
- 复制上面的命令
- 粘成
claude_desktop_config.json里mcpServers的一项(本地服务器用 command + args,示例见 客户端接法) - 重启客户端
客户端配置(取自该仓库的安装命令)
{
"mcpServers": {
"sanikacentric-biolit-mcp": {
"command": "uvx",
"args": ["--from", "git+https://github.com/sanikacentric/biolit-mcp", "biolit-mcp"]
}
}
}解析自我们于 2026-10-26 抓取的该仓库 README;我们未执行过。
command/args 来自仓库写明的安装命令;不确定时请以该项目 README 为准。
VS Code(.vscode/mcp.json —— 键名是 servers)
{
"servers": {
"sanikacentric-biolit-mcp": {
"command": "uvx",
"args": ["--from", "git+https://github.com/sanikacentric/biolit-mcp", "biolit-mcp"]
}
}
}VS Code 顶层键是 <code>servers</code>,其余与上面那份相同。
Claude Code(命令行)
claude mcp add --transport stdio sanikacentric-biolit-mcp -- uvx --from git+https://github.com/sanikacentric/biolit-mcp biolit-mcp
Claude Code 不收 JSON 文件,用这条命令直接加。
配置项的键名以你的客户端为准:客户端与 CLI
- ★ 数取值
- 0 ★ · sanikacentric/biolit-mcp · 取自 GitHub 搜索 API · (2026-11-13 20:00:50 核对)
- 来源明细
- 收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
- 收录与活跃
- 收录于 2026-10-23 · 最近见到 2026-11-14 · 共见到 26 次 · 被 23 个来源列出
- 评分构成
- 综合分 2,300 · 23 个来源 · mcp
- 安装
uvx --from git+https://github.com/sanikacentric/biolit-mcp biolit-mcp
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是
uvx --from git+https://github.com/sanikacentric/biolit-mcp biolit-mcp。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库
sanikacentric/biolit-mcp;我们收录于 2026-10-23;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。# BioLit MCP
以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →
Citation-grounded biomedical literature review for Claude. An MCP server over PubMed, Europe PMC, NCBI Gene and UniProt, an Evidence Review agent skill, and a 50-question benchmark that measures whether answers can be trusted.
Scientists don't adopt AI research assistants that invent citations. BioLit is built around one rule: Claude may only cite papers it has actually retrieved and read in the session, and the benchmark checks that every cited PMID exists and supports its claim.
mermaid
flowchart LR
U[Scientist] --> C[Claude + Evidence Review skill]
C -- MCP --> S[BioLit server]
S --> P[PubMed E-utilities search]
S --> E[Europe PMC abstracts + citation check]
S --> G[NCBI Gene]
S --> UP[UniProt Swiss-Prot]
C --> A[Answer: claims → PMIDs]
A --> B[Benchmark: PMID exists? claim supported?]
## Tools
| Tool | Source | Returns |
| searchpubmed(query, maxresults, minyear) | NCBI E-utilities | PMIDs, titles, journals, years, publication types |
| getabstracts(pmids) | Europe PMC | Abstracts + metadata; non-existent PMIDs listed in notfound |
| lookupgene(symbol, taxonid) | NCBI Gene | Official name, chromosome, cytogenetic location, aliases, summary |
| lookupprotein(genesymbol, taxonid) | UniProt | Reviewed accession, protein name, length, function |
All tools are read-only. Production details: request timeouts, retry with exponential backoff on 429/5xx, NCBI rate limiting (3 req/s, or 10 req/s with NCBIAPIKEY), input validation, and error messages that are safe to show the model.
## Quick start
Requires Python 3.11+ and uv.
Claude Code
bash
claude mcp add biolit -- uvx --from git+https://github.com/sanikacentric/biolit-mcp biolit-mcp
mkdir -p ~/.claude/skills && cp -r skills/evidence-review ~/.claude/skills/
Claude Desktop (claudedesktopconfig.json)
json
"mcpServers": {
"biolit": {
"command": "uvx",
"args": ["--from", "git+https://github.com/sanikacentric/biolit-mcp", "biolit-mcp"],
"env": { "NCBIEMAIL": "you@example.com" }
Remote (Streamable HTTP): biolit-mcp --transport streamable-http
Optional environment variables: NCBIAPIKEY (higher rate limit), NCBIEMAIL (recommended by NCBI).
Then ask: "What is the evidence that lecanemab slows cognitive decline in early Alzheimer's disease?"
## Evidence Review skill
skills/evidence-review/SKILL.md gives Claude a scientist's workflow: resolve entities → run focused searches → read abstracts → write one claim per sentence with PMIDs → self-check every citation before answering. The output separates the bottom line, evidence, strength & gaps, and references.
## Benchmark
evals/ runs 50 questions with and without the BioLit tools:
30 fact questions: UniProt accession + chromosome for well-characterized human genes, scored exactly.
20 literature questions: across oncology, cardiometabolic, neuro, gene therapy and structural biology. Every cited PMID is checked live against PubMed, and an LLM judge decides whether the cited abstracts support each claim.
Scientists don't adopt AI research assistants that invent citations. BioLit is built around one rule: Claude may only cite papers it has actually retrieved and read in the session, and the benchmark checks that every cited PMID exists and supports its claim.
mermaid
flowchart LR
U[Scientist] --> C[Claude + Evidence Review skill]
C -- MCP --> S[BioLit server]
S --> P[PubMed E-utilities search]
S --> E[Europe PMC abstracts + citation check]
S --> G[NCBI Gene]
S --> UP[UniProt Swiss-Prot]
C --> A[Answer: claims → PMIDs]
A --> B[Benchmark: PMID exists? claim supported?]
## Tools
| Tool | Source | Returns |
| searchpubmed(query, maxresults, minyear) | NCBI E-utilities | PMIDs, titles, journals, years, publication types |
| getabstracts(pmids) | Europe PMC | Abstracts + metadata; non-existent PMIDs listed in notfound |
| lookupgene(symbol, taxonid) | NCBI Gene | Official name, chromosome, cytogenetic location, aliases, summary |
| lookupprotein(genesymbol, taxonid) | UniProt | Reviewed accession, protein name, length, function |
All tools are read-only. Production details: request timeouts, retry with exponential backoff on 429/5xx, NCBI rate limiting (3 req/s, or 10 req/s with NCBIAPIKEY), input validation, and error messages that are safe to show the model.
## Quick start
Requires Python 3.11+ and uv.
Claude Code
bash
claude mcp add biolit -- uvx --from git+https://github.com/sanikacentric/biolit-mcp biolit-mcp
mkdir -p ~/.claude/skills && cp -r skills/evidence-review ~/.claude/skills/
Claude Desktop (claudedesktopconfig.json)
json
"mcpServers": {
"biolit": {
"command": "uvx",
"args": ["--from", "git+https://github.com/sanikacentric/biolit-mcp", "biolit-mcp"],
"env": { "NCBIEMAIL": "you@example.com" }
Remote (Streamable HTTP): biolit-mcp --transport streamable-http
Optional environment variables: NCBIAPIKEY (higher rate limit), NCBIEMAIL (recommended by NCBI).
Then ask: "What is the evidence that lecanemab slows cognitive decline in early Alzheimer's disease?"
## Evidence Review skill
skills/evidence-review/SKILL.md gives Claude a scientist's workflow: resolve entities → run focused searches → read abstracts → write one claim per sentence with PMIDs → self-check every citation before answering. The output separates the bottom line, evidence, strength & gaps, and references.
## Benchmark
evals/ runs 50 questions with and without the BioLit tools:
30 fact questions: UniProt accession + chromosome for well-characterized human genes, scored exactly.
20 literature questions: across oncology, cardiometabolic, neuro, gene therapy and structural biology. Every cited PMID is checked live against PubMed, and an LLM judge decides whether the cited abstracts support each claim.
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
[](https://anclum.com/zh/s/sanikacentric-biolit-mcp/)
- 来源
- awesome · https://github.com/sanikacentric/biolit-mcp
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- MCP 服务
- 收录来源
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SECURITY.md(这不代表不安全)
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所属领域与标签
每个标签都能点进去看同类的全部条目。数字是当前库里的真实条数。