AI Skill Hub 强烈推荐：生物医学模型 是一款优质的MCP工具。AI 综合评分 8.0 分，在同类工具中表现稳健。如果你正在寻找可靠的MCP工具解决方案，这是一个值得深入了解的选择。
生物医学模型 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
生物医学模型 是一款遵循 MCP（Model Context Protocol）标准协议的 AI 工具扩展。通过 MCP 协议，它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务，实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用，都可以通过自然语言在 AI 对话中直接触发，极大提升生产效率。
# 方式一：通过 Claude Code CLI 一键安装
claude skill install https://github.com/genomoncology/biomcp
# 方式二：手动配置 claude_desktop_config.json
{
"mcpServers": {
"------": {
"command": "npx",
"args": ["-y", "biomcp"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例： 用户: 请帮我用 生物医学模型 执行以下任务... Claude: [自动调用 生物医学模型 MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入："列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"______": {
"command": "npx",
"args": ["-y", "biomcp"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
One binary. One grammar. Evidence from the biomedical sources you already trust.
BioMCP cuts through the usual biomedical data maze: one query reaches the sources that normally live behind different APIs, identifiers, and search habits. Researchers, clinicians, and agents use the same command grammar to search, focus, and pivot without rebuilding the workflow for each source. You get compact, evidence-oriented results across live public data plus local study analytics.
User prompt: Give me a low-noise overview of BRAF in melanoma.
Expected tool call: biomcp search all --gene BRAF --disease melanoma --counts-only
Expected behavior: Returns a cross-entity counts summary that orients the next command instead of dumping long detail tables.
Expected output: Counts-first summary with suggested next commands for the highest-yield entity follow-ups.
- Search the literature: search article fans out across PubTator3 and Europe PMC, deduplicates PMID/PMCID/DOI identifiers, and can add a Semantic Scholar leg when your filters support it. - Pivot without rework: move from a gene, variant, drug, disease, pathway, protein, or article straight into the next built-in view instead of rebuilding filters by hand. - Choose a playbook: biomcp suggest "<question>" routes a biomedical question to a shipped worked example and two starter commands. - Analyze studies locally: study commands cover local query, cohort, survival, compare, and co-occurrence workflows with native terminal, SVG, and PNG charts for downloaded cBioPortal-style datasets. - Follow the paper trail: article citations, article references, article recommendations, and article entities turn one known paper into a broader evidence map. - Enrich and batch: use biomcp enrich for top-level g:Profiler enrichment and biomcp batch for up to 10 focused get calls in one command.
curl -fsSL https://biomcp.org/install.sh | bash```bash uv tool install biomcp-cli
```
This installs the biomcp binary on your PATH.
Install guided investigation workflows into your agent directory:
biomcp skill install ~/.claude --forceBioMCP rate limiting is process-local. For many concurrent workers, run one shared Streamable HTTP biomcp serve-http endpoint so all workers share a single limiter budget:
biomcp serve-http --host 0.0.0.0 --port 8080By default, serve-http accepts any HTTP Host header. Add --allowed-hosts example.com,internal.example.com when you want to restrict accepted Host header values.
Remote clients should connect to http://<host>:8080/mcp. Lightweight process probes are available at GET /health, GET /readyz, and GET /.
First useful query in under 30 seconds:
uv tool install biomcp-cli
biomcp health --apis-only
biomcp suggest "What drugs treat melanoma?"
biomcp list gene
biomcp search all --gene BRAF --disease melanoma # unified cross-entity discovery
biomcp get gene BRAF pathways hpaUser prompt: Show OncoKB therapy evidence for BRAF V600E.
Expected tool call: biomcp variant oncokb "BRAF V600E"
Expected behavior: Uses ONCOKB_TOKEN when configured and otherwise returns helpful guidance about the missing credential.
Expected output: Therapy and level evidence when ONCOKB_TOKEN is set, or a clear setup hint when it is not.
User prompt: Show scored DisGeNET associations for TP53.
Expected tool call: biomcp get gene TP53 disgenet
Expected behavior: Uses DISGENET_API_KEY to retrieve the scored gene-disease association section.
Expected output: Ranked disease-association table with evidence counts and scores when DISGENET_API_KEY is configured.
The directory bundle exposes only the optional settings needed for the first reviewer-facing build:
| Claude Desktop field | Runtime env var | Purpose |
|---|---|---|
| OncoKB Token | ONCOKB_TOKEN | Enables biomcp variant oncokb "<gene> <variant>" therapy and level evidence |
| DisGeNET API Key | DISGENET_API_KEY | Enables scored DisGeNET sections on gene and disease lookups |
| Semantic Scholar API Key | S2_API_KEY | Improves reliability for article TLDR, citation, reference, and recommendation helpers |
The first directory build exposes only those three optional settings. Advanced CLI-only env vars remain documented in API Keys for the general BioMCP CLI path.
Most commands work without credentials. Optional keys improve rate limits or unlock optional enrichments:
export NCBI_API_KEY="..." # PubTator, PubMed/efetch, PMC OA, NCBI ID converter
export S2_API_KEY="..." # Optional Semantic Scholar auth; dedicated quota at 1 req/sec
export OPENFDA_API_KEY="..." # OpenFDA rate limits
export NCI_API_KEY="..." # NCI CTS trial search (--source nci)
export ONCOKB_TOKEN="..." # OncoKB variant helper
export ALPHAGENOME_API_KEY="..." # AlphaGenome variant effect predictionsearch article, get article, article batch, get article ... tldr, and the explicit Semantic Scholar helpers all work without S2_API_KEY. With the key, BioMCP sends authenticated requests and uses a dedicated rate limit at 1 req/sec. Without it, BioMCP uses the shared unauthenticated pool at 1 req/2sec. search article --source supports all, pubtator, europepmc, pubmed, semanticscholar, and litsense2. The default compatible article federation uses PubTator3, Europe PMC, PubMed, and automatic Semantic Scholar; use --source semanticscholar or --source litsense2 explicitly when you want one of those sources alone. References and recommendations can be empty for paywalled papers because of publisher elision in Semantic Scholar upstream coverage.
Install the biomcp binary first, then add the hosted plugin marketplace and install the BioMCP plugin in Claude Code:
/plugin marketplace add genomoncology/biomcp
/plugin install biomcp@biomcpThe plugin wires Claude Code to the local stdio MCP server with biomcp serve. For guided BioMCP workflows, also install the skill assets below.
Install BioMCP from the Anthropic Directory in Claude Desktop when that path is available for your environment. For local/manual setups, use the JSON MCP config below.
高质量的开源MCP工具，具有较高的实用价值
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
总体来看，生物医学模型 是一款质量优秀的MCP工具，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | biomcp |
| Topics | aibioinformaticsgenomicsllm |
| GitHub | https://github.com/genomoncology/biomcp |
| License | MIT |
| 语言 | Rust |
收录时间：2026-07-01 · 更新时间：2026-07-01 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型，复制安装指令后粘贴到对应客户端