semblekit
MCP server for the Semble practice-management API, enabling AI agents to search for patients, contacts, and users, as well as retrieve patient relationships via read-only tools.
README
semblekit (@burrows99/semblekit)
CLI, library & MCP server for the Semble practice-management API — usable by any agent, human, or script.
semblekit drives Semble over its public GraphQL API. It models Semble's own
concepts (contacts, patients & relationships, users) rather than any one organisation's usage of them, and
ships four ways to use it: a semble CLI, an importable library, an MCP server, and a Claude Code plugin.
Not affiliated with, endorsed by, or supported by Semble Ltd. "Semble" names the API this tool interoperates with.
Design principle. Commands map to Semble resources, not workflows. A "Responsible Clinician", for example, is not a first-class Semble thing — it is just a patient relationship with a label pointing at a contact. So the tool exposes
semble patient relationship …and leaves the meaning to the consumer.
Naming. The repo and CLI command are
semblekit/semble; the published package is@burrows99/semblekiton the GitHub Packages registry (the bare namesemblekitis taken on npmjs). The Claude plugin issemble@semblekit.
Table of Contents
Security
Semble is a practice-management / EHR system, so treat everything it returns as sensitive.
- De-identification (on by default). Output is pseudonymised before any agent, CLI, or MCP client sees
it: direct identifiers — name, email, date of birth, phone, address, NHS number — are redacted, and
free-text is scrubbed for embedded emails / phone / NHS numbers, while Semble's opaque ids and clinical
values are kept. Per the ICO,
pseudonymised data is still personal data — this reduces what agents read, it does not anonymise.
Disable with the CLI
--no-deidflag orSEMBLE_DEID=false(honoured by the CLI and the MCP server; for MCP it is set at launch, so an agent cannot turn it off itself). - Health data.
patientdata is likely special-category personal data under UK GDPR / the Data Protection Act. You remain the controller or processor for anything you move with this tool. Prefer the sandbox for development. - Credentials. Supplied via flags, environment variables, or
~/.config/semble/config.json— never hardcoded. Keep them out of version control; the tool never logs credential values. - Tracing & data on disk. Every command appends request metadata (no bodies) to
.semble/trace.jsonl.--trace/--trace-fulladditionally persist full request and response bodies — which may contain patient data — to that file. Secrets (tokens) are redacted, patient data is not..semble/is git-ignored by default; avoid full tracing against production data unless your obligations allow it.
Background
Credentials and API URLs come from flags, environment variables, or a config file — never hardcoded — so
semblekit is not coupled to any deployment. It runs on plain Node (built-in fetch, Node ≥ 18); no Docker.
It talks to Semble's public GraphQL API (x-token). The design is object-oriented: typed entities own
their behaviour, thin resources do I/O, and a single fetch chokepoint makes request tracing a one-line wrap.
Install
Requires Node ≥ 18. semblekit is published to the GitHub Packages npm registry, which needs a
one-time scope + token setup (a GitHub token with the read:packages scope):
printf '@burrows99:registry=https://npm.pkg.github.com\n//npm.pkg.github.com/:_authToken=YOUR_GITHUB_TOKEN\n' >> ~/.npmrc
npm install -g @burrows99/semblekit # global: the `semble` CLI + `semble-mcp` MCP server
# or, as a library in a project:
npm install @burrows99/semblekit
Dependencies
Node ≥ 18 only (uses the built-in fetch). No Docker, no database.
Usage
Credentials resolve flags > environment > config file > built-in presets, and are auto-discovered from
the nearest .env / .claude/.env walking up from the working directory. See .env.example.
For the public API the relevant variables are SEMBLE_OPEN_URL and SEMBLE_TOKEN.
CLI
semble patient search "smith" --limit 5 # find a patient id
semble patient get <patientId> --json
semble contact search "clinic" --json # find a contact/clinician id
semble user list
semble patient relationship add <patientId> <contactId> --label "Responsible Clinician"
semble help
--json for machine output, --trace for a DevTools-style request log, --limit to cap paginated results.
stdout is data, stderr is messages; exit 0 success · 1 runtime error · 2 usage error.
Library
import { SembleClient, SembleTracer, loadConfig } from "@burrows99/semblekit";
const client = new SembleClient(loadConfig({ profile: "sandbox" }));
const [patient] = await client.patients.search("smith");
const rels = await client.patients.listRelationships(patient.id);
new SembleTracer(client, (record) => console.error(record)); // optional: trace every HTTP exchange
Methods return data or throw SembleError; they never call process.exit or print. search / list
paginate automatically and accept { limit }.
MCP server
semblekit ships a stdio MCP server so an AI host can drive Semble as
tools — run it with npx, no install needed (uses the .npmrc set up in Install):
npx -p @burrows99/semblekit semble-mcp
Point an MCP host at it:
{
"mcpServers": {
"semblekit": { "command": "npx", "args": ["-y", "-p", "@burrows99/semblekit", "semble-mcp"] }
}
}
Inspect it with the MCP Inspector:
npx @modelcontextprotocol/inspector npx -p @burrows99/semblekit semble-mcp
Read-only tools: semble_patient_search, semble_patient_get, semble_patient_relationships,
semble_contact_search, semble_contact_get, semble_user_list, semble_user_get.
Claude Code plugin
claude plugin marketplace add /path/to/semblekit
claude plugin install semble@semblekit
API
new SembleClient(config?)— composes the transport and resources; buildconfigwithloadConfig(options).client.patients—search(query?, { limit? }),get(id),listRelationships(patientId).client.contacts—search(query?, { limit? }),get(id).client.users—list({ limit? }),get(id).SembleTracer(client, sink, options?)— decorates the client's fetch chokepoint;sink(record)fires per request, with secrets redacted.SembleConfig/loadConfig/PRESETS— profile resolution; presets namesandboxandprod.- Entities —
Patient,Contact,User,RelatedAccount; eachJSON.stringifys to its API shape. - Errors —
SembleErrorand its subclassesSembleConfigError,SembleAuthError,SembleApiError,SembleNotFoundError,SembleValidationError.
Maintainers
@burrows99 (Raunak Burrows).
Contributing
Questions and bugs: open an issue at github.com/burrows99/semblekit/issues.
PRs are welcome and target main. Keep org-specific meaning out of the library — expose the generic Semble
operation.
npm install # installs deps, builds via `prepare`
npm run build # tsc → dist/ + .d.ts
npm run typecheck # tsc --noEmit
npm test # placeholder suite
Source is TypeScript (ESM, NodeNext) in src/**/*.ts, compiled to dist/. Add a resource by creating its
entity in src/entities/, a src/resources/<resource>.ts, wiring it onto the client in src/client.ts,
and a matching src/commands/<resource>.ts.
License
MIT © Raunak Burrows.
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。