
Md Md
io.github.kedarvartak由 GitHub 账号 kedarvartak 发布v1.0.0更新于 Oct 24, 2026
MCP server for md.md - provides team knowledge context to AI assistants
概览
md.md 的 MCP 服务器,把团队已发布的 Markdown 知识块解析为可直接注入 AI 的上下文,并管理知识块生命周期。
- 可以做什么
- 按任务解析并附加团队知识块,生成可直接注入 AI 的上下文
- 列出并读取知识块,包括其中的 Markdown 文件与版本
- 创建、更新、发布和归档知识块及其文件
- 检查后端健康状态与身份,并查看注入日志以便观测
- 适用场景
- 适合把工程规范、架构决策和工作流程以版本化 Markdown 维护的团队,希望 AI 助手自动获取正确的已发布上下文,而不必每次重复说明。
- 运行要求
- 以 npm 包 md-md-mcp-server 通过 stdio 在本机运行,需要 Node.js 18+ 和 npm。需要可访问的 md.md 后端(MD_MD_API_URL)以及 API 密钥 MD_MD_API_KEY(格式 mdmd_...)。可选 MD_MD_TEAM_ID 和 MD_MD_WORKSPACE_ID 用于覆盖作用域。后端本身需要 PostgreSQL 数据库。
安装
在 SourceWeft 中
- 打开 控制台中的 Md Md,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
md.md
md.md is a team intelligence platform that turns internal engineering knowledge into versioned Markdown blocks, then injects the right context into AI-assisted development workflows.
It combines:
- A backend registry and policy engine
- A React dashboard for authoring and publishing knowledge blocks
- An MCP server for IDE and assistant integrations
- Integration docs and product design docs
What Problem This Solves
AI coding assistants are strong at general coding but weak on team-specific context. Without shared context, teams repeatedly re-explain standards, architecture decisions, and workflows.
md.md solves this by letting teams:
- Author knowledge once
- Publish stable versions
- Resolve the right context at task time
- Reuse the same context across IDEs and AI tools
Repository Structure
app-backend/: NestJS API for auth, block lifecycle, policy resolution, and observabilityapp-client/: React + Vite dashboard for block authoring, publishing, and resolve previewmcp-server/: Model Context Protocol server that exposes md.md tools over stdioide-integrations/: IDE integration documentation (currently Cursor-focused)docs/: Product vision, phase plan, and resolution model design docs
High-Level Architecture
- Teams author Markdown files inside blocks.
- Blocks are versioned and published.
- IDE/assistant integrations call resolve tools or APIs with task context.
- The backend selects relevant published blocks and composes a payload.
- The payload is injected into AI context.
- Resolution and usage metadata are logged for observability.
Integration Path
- IDE or AI client
- MCP protocol over stdio
mcp-servertools- Backend REST API
- Postgres persistence (Supabase-compatible)
Core Concepts
Block
A named unit of team knowledge containing one or more Markdown files.
Draft and Published Versions
Draft content can be edited freely. Published versions are stable and intended for consumption.
Scoped Access
Data and permissions are scoped by team and workspace.
Resolution
At usage time, the system resolves and composes relevant published blocks into an AI-ready payload.
Component Details
1) Backend (app-backend)
Tech stack:
- NestJS 11
- PostgreSQL via
pg(Supabase-compatible connection) - TypeScript
Responsibilities:
- Authentication and authorization
- RBAC and API key management
- Block CRUD, versioning, publishing, and archiving
- Resolution orchestration
- Injection log and audit log APIs
Notable backend capabilities:
- API key format:
mdmd_<token> - Roles: reader, author, admin
- Per-block permission overrides
- Health and observability endpoints used by MCP
2) Client Dashboard (app-client)
Tech stack:
- React 19
- Vite
- TypeScript
- MUI + Emotion
Responsibilities:
- Create and edit blocks
- Manage block files
- Publish versions
- Preview resolution output
- Configure auth/scope information for usage
3) MCP Server (mcp-server)
Tech stack:
- Node.js + TypeScript
@modelcontextprotocol/sdk- Zod for argument validation
Responsibilities:
- Expose md.md capabilities as MCP tools
- Forward tool calls to backend APIs
- Handle retries, timeouts, and health checks
Primary tools include:
resolve_contextattach_blockslist_blocksget_blockhealth_check- Block lifecycle tools (
create_block,update_block,publish_block, etc.) - Access and observability tools (
whoami,list_injection_logs)
4) IDE Integrations (ide-integrations)
Contains setup patterns for connecting editors to the MCP server.
Current documented integration:
- Cursor (MCP client configuration)
5) Product and Design Docs (docs)
idea_1.0.md: product rationale and system visionphases_1.0.md: implementation roadmap (phase-oriented)resolution_model.md: detailed target model for selection, ordering, and composition
Local Development Setup
Prerequisites
- Node.js 18+
- npm
- PostgreSQL database (Supabase Postgres recommended)
1) Backend
Create app-backend/.env with at least:
Start backend:
2) Create Admin API Key
From app-backend:
Save the generated mdmd_... key securely.
3) Client Dashboard
4) MCP Server
Set environment variables for MCP runtime (either shell or IDE config):
Common Developer Workflows
Backend
Client
MCP Server
Security and Secrets
- Do not commit API keys or token files.
- Keep secrets in environment files or secure secret managers.
- Use least-privilege API keys for integrations.
- Rotate keys regularly.
- Review audit logs for sensitive actions.
Recent local ignore defaults in mcp-server/.gitignore include:
.mcpregistry_github_token.mcpregistry_registry_token
Current Product Status
Implemented:
- End-to-end block lifecycle (create, edit, publish)
- Dashboard authoring and resolve preview
- Backend RBAC and API key management
- MCP server with tooling for context resolution and block operations
In progress or planned:
- Smarter policy-based contextual selection and ordering
- Expanded IDE integrations
- Additional analytics and governance features
Where To Go Next
- Backend implementation and auth docs:
app-backend/docs/ - MCP usage and integration details:
mcp-server/README.md - IDE setup notes:
ide-integrations/README.md - Product vision and roadmap:
docs/
License
See license declarations in each package (app-backend, app-client, mcp-server).
来源:README.md,提交 e71126d
工具
0版本历史
1- v1.0.0最新Sep 16, 2026
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