Install
$ agentstack add mcp-blendsdk-fluentui-mcp ✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
About
FluentUI MCP Server
[](https://www.npmjs.com/package/fluentui-mcp) [](https://opensource.org/licenses/MIT) [](https://nodejs.org/)
> Model Context Protocol (MCP) server providing AI assistants with intelligent, context-efficient access to > Microsoft FluentUI documentation.
Build production-grade React UIs with FluentUI — powered by AI that actually knows the component library.
What is this?
This is an MCP server that gives AI assistants (Claude, Cline, Cursor, etc.) deep knowledge of the Microsoft FluentUI component library. Instead of the AI guessing at component APIs or hallucinating props, it queries real documentation through specialized tools.
The Problem
AI assistants often:
- ❌ Hallucinate FluentUI component props that don't exist
- ❌ Use outdated v8 patterns when you need v9
- ❌ Load entire documentation sets, wasting context window
- ❌ Miss best practices, accessibility requirements, and patterns
The Solution
This MCP server provides 12 specialized tools that give AI assistants:
- ✅ Accurate, up-to-date component documentation
- ✅ Smart search across 100+ documentation pages
- ✅ Props references, code examples, and patterns on demand
- ✅ Component suggestions based on UI descriptions
- ✅ Implementation guides combining docs + patterns + examples
- ✅ ~90% context window reduction vs loading all docs
Quick Start
Install
npm install -g fluentui-mcp
Configure Cline (VS Code)
Add to your Cline MCP settings:
{
"mcpServers": {
"fluentui-docs": {
"command": "fluentui-mcp"
}
}
}
Settings file location:
- macOS:
~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Windows:
%APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json
Configure Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"fluentui-docs": {
"command": "fluentui-mcp"
}
}
}
That's it! 🎉
Restart your AI assistant and you'll have access to all FluentUI documentation tools.
Multi-Version Support
The server supports multiple FluentUI versions. Pass the version as an argument:
{
"mcpServers": {
"fluentui-v9": {
"command": "fluentui-mcp",
"args": ["v9"]
}
}
}
You can even run multiple versions simultaneously:
{
"mcpServers": {
"fluentui-v9": {
"command": "fluentui-mcp",
"args": ["v9"]
},
"fluentui-v10": {
"command": "fluentui-mcp",
"args": ["v10"]
}
}
}
Custom Schema Path
Point to your own enhanced schema file:
{
"mcpServers": {
"fluentui-docs": {
"command": "fluentui-mcp",
"env": {
"FLUENTUI_SCHEMA_PATH": "/path/to/your/fluentui-schema-enhanced.json"
}
}
}
}
Available Tools (12)
Core Documentation Tools
| Tool | Description | | ---------------------- | ------------------------------------------------------------------------------------------- | | query_component | Get complete documentation for a specific component. Supports fuzzy name matching. | | search_docs | Search across ALL documentation (components, patterns, enterprise). Returns ranked results. | | list_by_category | List all components in a category (buttons, forms, navigation, etc.). | | get_foundation | Get setup, theming, styling, and architecture documentation. | | get_pattern | Get UI pattern documentation (forms, layout, navigation, modals, state management). | | get_enterprise | Get enterprise-grade patterns (dashboards, admin UIs, data-heavy apps, accessibility). |
Intelligence Tools
| Tool | Description | | ------------------------------ | -------------------------------------------------------------------------------------- | | suggest_components | Given a UI description, suggests which FluentUI components to use and why. | | get_implementation_guide | Combines relevant docs + patterns + examples into a step-by-step implementation guide. | | get_component_examples | Extracts only code examples from a component's docs (minimal context usage). | | get_props_reference | Extracts only the props table from a component's docs (quick lookup). |
Utility Tools
| Tool | Description | | ------------------- | ---------------------------------------------------------------- | | list_all_docs | Lists all available documentation with descriptions. | | reindex | Re-scans the documentation folder and rebuilds the search index. |
How It Works
The server is powered by a schema-driven pipeline. Instead of parsing markdown at runtime, a single pre-built JSON schema bundles all FluentUI documentation. That schema is generated offline by a two-stage pipeline:
┌─────────────┐ ┌──────────────┐ ┌─────────────────────────┐
│ Scraper │ → │ Enhancer │ → │ fluentui-schema- │
│ (ts-morph) │ │ (LLM-based) │ │ enhanced.json (bundled)│
└─────────────┘ └──────────────┘ └─────────────────────────┘
Extracts Adds AI Single source of truth
props/slots/ descriptions, shipped with the package
stories from best practices,
FluentUI source a11y, patterns
At runtime the MCP server simply loads and serves that schema:
┌──────────────────────────────────────────────────┐
│ MCP Server (stdio) │
│ Receives tool calls from AI assistants │
├──────────────────────────────────────────────────┤
│ 12 Specialized Tools │
│ query │ search │ suggest │ guide │ ... │
├──────────────────────────────────────────────────┤
│ Formatters Layer │
│ component │ guide │ pattern │ props │ list │ … │
├──────────────────────────────────────────────────┤
│ In-Memory Schema Store + Search │
│ ┌────────────┐ ┌────────────┐ ┌──────────┐ │
│ │ Schema │ │ Categories │ │ Search │ │
│ │ Store │ │ Index │ │ Index │ │
│ └────────────┘ └────────────┘ └──────────┘ │
├──────────────────────────────────────────────────┤
│ Schema Loader │ Validator │ Search Engine │
├──────────────────────────────────────────────────┤
│ Bundled Schema (fluentui-schema-enhanced) │
│ Components │ Utilities │ Guides │ Patterns │
└──────────────────────────────────────────────────┘
Loading Strategy
- Startup: Server loads the bundled enhanced schema JSON (< 1 second)
- Validate: Schema is validated; any structural issues are reported to stderr
- Index: Builds an in-memory search index with TF-IDF scoring
- Serve: All tool calls served from memory (instant, no disk I/O)
- Reindex: The
reindextool can rebuild the index on demand
Schema Coverage (FluentUI v9)
| Section | Content | Count | | -------------- | -------------------------------------------------------------------- | ----- | | Components | Props, slots, stories, AI descriptions, best practices, a11y, prop guidance, anti-patterns, composition examples, performance/theming notes, edge cases | 62 | | Utilities | Hooks and helper exports with parameter references + performance notes | 4 | | Guides | Foundation, enterprise, and quick-reference guides (with key takeaways, pitfalls, a11y notes) | 16 | | Patterns | Form, layout, navigation, modal, and state-management patterns (with when-to-use / when-not-to-use, pitfalls) | 15 |
Usage Examples
AI Workflow: Building a Login Form
User: "Create a login form with email and password"
AI uses tools:
1. suggest_components({ uiDescription: "login form with email and password" })
→ Suggests: Input, Field, Button, Card
2. get_implementation_guide({ goal: "login form" })
→ Returns combined docs + form patterns + code examples
3. AI implements the form with accurate props and patterns
AI Workflow: Building a Data Table
User: "Create a sortable data table with selection"
AI uses tools:
1. search_docs({ query: "table sorting selection" })
→ Finds: Table, DataGrid, sorting patterns
2. query_component({ componentName: "DataGrid" })
→ Full DataGrid documentation
3. get_component_examples({ componentName: "DataGrid" })
→ Just the code examples for reference
4. AI implements with correct DataGrid API
Development
Setup
git clone https://github.com/blendsdk/fluentui-mcp.git
cd fluentui-mcp
yarn install
Build
yarn build # Compile TypeScript
yarn watch # Watch mode
Test
yarn test # Run tests
yarn test:watch # Watch mode
yarn test:coverage # Coverage report
Project Structure
fluentui-mcp/
├── src/ # MCP server (runtime)
│ ├── index.ts # stdio transport entry point
│ ├── server.ts # Tool definitions, state, dispatch
│ ├── config.ts # Configuration resolver
│ ├── types/ # Schema + shared TypeScript types
│ ├── schema/
│ │ ├── schema-loader.ts # Resolves & loads the bundled schema
│ │ ├── schema-store.ts # In-memory schema store + indexes
│ │ └── schema-validator.ts # Structural schema validation
│ ├── search/
│ │ ├── search-engine.ts # TF-IDF search engine
│ │ └── search-index.ts # In-memory search index
│ ├── formatters/ # Render schema entries → markdown
│ └── tools/ # 12 MCP tool implementations
├── scripts/ # Offline schema pipeline (build-time)
│ ├── scraper/ # ts-morph extraction from FluentUI source
│ └── enhancer/ # LLM enrichment + guide/pattern generation
├── data/
│ └── v9/
│ ├── fluentui-schema.json # Raw scraped schema
│ └── fluentui-schema-enhanced.json # Enhanced schema (shipped)
├── package.json
├── tsconfig.json
└── vitest.config.ts
Configuration
| Source | Priority | Example | | ------------------------------ | ---------------------------- | -------------------------------------- | | CLI argument | Medium (version) | fluentui-mcp v9 | | FLUENTUI_VERSION env var | Medium | FLUENTUI_VERSION=v9 | | FLUENTUI_SCHEMA_PATH env var | Highest (overrides version) | FLUENTUI_SCHEMA_PATH=/my/schema.json | | Default | Lowest | Bundled v9 enhanced schema |
Regenerating the Schema
The bundled schema is generated offline by the scraper + enhancer pipeline. Enrichment requires an LLM provider — set LLM_PROVIDER (openai or anthropic) and the matching API key in a local .env file (see .env.example).
# 1. Scrape props/slots/stories from FluentUI source (clones the repo)
yarn scrape --version v9 --clone
# 2. Enhance with AI descriptions, best practices, a11y, and guides
yarn enhance --version v9 --full
# Or run the whole pipeline (scrape → enhance → build → test) in one step:
yarn pipeline:full
The enhancer is incremental: it hashes each source entry and only re-runs the LLM for entries that changed. Use --dry-run to preview a diff without making any LLM calls.
Troubleshooting
Server Not Loading
- Verify installation:
which fluentui-mcp - Test manually:
fluentui-mcp(should output to stderr: "FluentUI MCP Server running on stdio") - Check MCP settings JSON syntax
- Restart VS Code / AI assistant
Tool Errors
- "Schema not found": Check the version exists under
data/or setFLUENTUI_SCHEMA_PATH - "Component not found": Try
search_docswith broader terms - Search returning no results: Try
reindexto rebuild the search index
Performance
- First query: < 100ms (served from memory after startup load)
- Search queries: < 50ms (pre-built TF-IDF index)
- Startup: < 1 second to load and index the bundled schema
Contributing
Contributions welcome! Especially:
- Documentation for new FluentUI versions
- Additional tools and intelligence features
- Search engine improvements
- Bug reports and fixes
License
MIT — see [LICENSE](LICENSE) for details.
See Also
- FluentUI React Components — Official documentation
- Model Context Protocol — MCP specification
- Cline — VS Code AI assistant
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: blendsdk
- Source: blendsdk/fluentui-mcp
- License: MIT
- Homepage: https://blendsdk.github.io/fluentui-mcp/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.