spell-checker-mcp

jezweb/spell-checker-mcp

3.3

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The Spell Checker MCP Server provides multi-language spell checking and AI-powered grammar correction for MCP clients, supporting 53 languages with automatic detection.

Tools
3
Resources
0
Prompts
0

Spell Checker MCP Server

Multi-language spell checking and AI-powered grammar correction for MCP clients

Deploy to Cloudflare npm version License: MIT

MCP server for real-time spell checking and grammar correction in AI coding assistants. Supports 53 languages with automatic detection, powered by Cloudflare Workers, nspell dictionaries, and Workers AI.

Live Demo: https://spellcheck.mcp.jezweb.ai

Features

  • 53 Languages: Comprehensive spell checking with automatic language detection
  • AI Grammar: Context-aware grammar checking powered by DeepSeek R1 32B
  • Auto-Correction: Three modes (spelling only, grammar only, or both)
  • Document Storage: Corrected documents saved to R2 with 30-day auto-delete
  • Edge Deployment: Global low-latency via Cloudflare Workers
  • Zero-Config: One-click deployment with automatic resource provisioning

Supported Languages

English (en, en-au, en-ca, en-gb, en-us, en-za) • Spanish • French • German • Italian • Dutch • Portuguese • Russian • Polish • Czech • Romanian • Swedish • Danish • Norwegian • Bulgarian • Catalan • Welsh • Greek • Esperanto • Estonian • Basque • Faroese • Friulian • Frisian • Irish • Scottish Gaelic • Galician • Hebrew • Croatian • Hungarian • Armenian • Icelandic • Georgian • Korean • Latin • Lithuanian • Latvian • Macedonian • Mongolian • Persian • Breton • Slovak • Slovenian • Serbian • Turkish • Ukrainian • Vietnamese

Quick Start

Option 1: Deploy Your Own (Recommended)

Click the button to deploy your own instance:

Deploy to Cloudflare

This will automatically:

  1. Fork the repository to your GitHub account
  2. Create R2 buckets for dictionaries and documents
  3. Set up Workers AI binding for grammar checking
  4. Deploy to Cloudflare Workers with CI/CD

After deployment:

  • Your server will be live at: https://spell-checker-mcp.<your-subdomain>.workers.dev
  • No additional configuration needed - all bindings are auto-provisioned!

Option 2: Use Public Instance

Connect to the public demo instance (rate-limited):

# Claude Code CLI
claude mcp add spell-checker --transport http https://spellcheck.mcp.jezweb.ai/mcp

Option 3: Run Locally

# Clone repository
git clone https://github.com/jezweb/spell-checker-mcp.git
cd spell-checker-mcp

# Install dependencies
npm install

# Start dev server
npm run dev

Installation

Connect this MCP server to your favorite AI coding assistant.

Claude Code CLI

Via CLI (Recommended)

Use HTTP transport (public server):

claude mcp add spell-checker --transport http https://spellcheck.mcp.jezweb.ai/mcp

Or use NPX (local):

claude mcp add spell-checker -- npx -y spell-checker-mcp

Via Configuration File

Add to ~/.claude/mcp.json (user-level) or .mcp.json (project-level):

HTTP Transport:

{
  "mcpServers": {
    "spell-checker": {
      "url": "https://spellcheck.mcp.jezweb.ai/mcp",
      "transport": "http"
    }
  }
}

NPX (local):

{
  "mcpServers": {
    "spell-checker": {
      "command": "npx",
      "args": ["-y", "spell-checker-mcp"]
    }
  }
}

Verify Installation

claude mcp list
claude mcp get spell-checker
Cursor
  1. Open Cursor Settings
  2. Navigate to "MCP Servers"
  3. Click "Add Server"
  4. Choose configuration:

HTTP Transport (Public Server):

{
  "mcpServers": {
    "spell-checker": {
      "url": "https://spellcheck.mcp.jezweb.ai/mcp",
      "transport": "http"
    }
  }
}

NPX (Local):

{
  "mcpServers": {
    "spell-checker": {
      "command": "npx",
      "args": ["-y", "spell-checker-mcp"]
    }
  }
}
  1. Save and restart Cursor
Cline (VS Code Extension)

Add to ~/Library/Application Support/Code/User/globalStorage/rooveterinaryinc.roo-cline/settings/cline_mcp_settings.json:

HTTP Transport:

{
  "mcpServers": {
    "spell-checker": {
      "url": "https://spellcheck.mcp.jezweb.ai/mcp",
      "transport": "http"
    }
  }
}

NPX:

{
  "mcpServers": {
    "spell-checker": {
      "command": "npx",
      "args": ["-y", "spell-checker-mcp"]
    }
  }
}

Restart VS Code after configuration.

Zed Editor

Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "spell-checker": {
      "settings": {
        "url": "https://spellcheck.mcp.jezweb.ai/mcp",
        "transport": "http"
      }
    }
  }
}

Restart Zed after configuration.

Other MCP Clients

Most MCP clients support the standard configuration format:

HTTP Transport:

{
  "mcpServers": {
    "spell-checker": {
      "url": "https://spellcheck.mcp.jezweb.ai/mcp",
      "transport": "http"
    }
  }
}

Stdio (NPX):

{
  "mcpServers": {
    "spell-checker": {
      "command": "npx",
      "args": ["-y", "spell-checker-mcp"]
    }
  }
}

Consult your client's documentation for the specific configuration file location.

MCP Tools

spell_check_analyze

Analyze text for spelling errors with suggestions.

Input:

{
  "text": "The text to check for speling errors",
  "language": "en-au"
}

Output:

{
  "summary": "Found 1 spelling error",
  "errors": [
    {
      "word": "speling",
      "line": 1,
      "column": 25,
      "suggestions": ["spelling", "spieling", "peeling"]
    }
  ]
}

Parameters:

  • text (required): Text to analyze
  • language (optional): Language code (defaults to auto-detect)

spell_check_grammar

AI-powered grammar and style checking.

Input:

{
  "text": "The team are ready but they dont know what their doing.",
  "language": "en-au"
}

Output:

{
  "summary": "Found 2 grammar issues",
  "errors": [
    {
      "message": "Missing apostrophe in contraction",
      "context": "they dont know",
      "suggestions": ["they don't know"],
      "ruleId": "APOSTROPHE_MISSING",
      "category": "PUNCTUATION"
    },
    {
      "message": "Incorrect use of 'their' - should be 'they're'",
      "context": "what their doing",
      "suggestions": ["what they're doing"],
      "ruleId": "THEIR_THEYRE",
      "category": "GRAMMAR"
    }
  ]
}

Categories:

  • GRAMMAR: Subject-verb agreement, tense, etc.
  • PUNCTUATION: Apostrophes, commas, quotation marks
  • STYLE: Wordiness, passive voice, clarity
  • TYPOGRAPHY: Spacing, capitalization

spell_check_correct

Auto-correct spelling and grammar errors.

Input:

{
  "text": "The text to corect with speling and grammer errors.",
  "language": "en-au",
  "mode": "both"
}

Output:

{
  "original": "The text to corect with speling and grammer errors.",
  "corrected": "The text to correct with spelling and grammar errors.",
  "changes": [
    {
      "type": "spelling",
      "position": 12,
      "original": "corect",
      "correction": "correct",
      "confidence": 0.95
    },
    {
      "type": "spelling",
      "position": 24,
      "original": "speling",
      "correction": "spelling",
      "confidence": 0.98
    },
    {
      "type": "spelling",
      "position": 36,
      "original": "grammer",
      "correction": "grammar",
      "confidence": 0.92
    }
  ],
  "summary": "Applied 3 corrections",
  "r2": {
    "url": "https://spellcheck.files.jezweb.ai/abc123.txt",
    "key": "abc123.txt",
    "size": 52,
    "expiresAt": "2025-12-13T00:00:00Z"
  }
}

Modes:

  • spelling: Fix spelling only (fast, no AI required)
  • grammar: Fix grammar only (AI-powered)
  • both: Fix spelling then grammar (default)

R2 Storage: All corrected documents are automatically uploaded to R2 storage with:

  • 30-day automatic expiration
  • Unique non-guessable URLs
  • Public read access

Architecture

Tech Stack

  • Runtime: Cloudflare Workers (V8 isolates)
  • Framework: Hono (lightweight HTTP)
  • Spell Checking: nspell + 53 Hunspell dictionaries
  • Language Detection: franc-min (automatic)
  • Grammar AI: Workers AI (DeepSeek R1 Distill Qwen 32B)
  • Storage: R2 (dictionaries + corrected documents)
  • Transport: HTTP JSON-RPC (MCP standard)

Project Structure

src/
├── index.ts              # Main Worker entry, HTTP routes
├── lib/
│   ├── dictionary.ts     # Dictionary loader with R2 lazy loading
│   ├── spellcheck.ts     # nspell wrapper with position tracking
│   ├── grammar.ts        # Workers AI grammar checking
│   ├── correction.ts     # Correction application logic
│   └── storage.ts        # R2 document storage
├── mcp/
│   ├── server.ts         # MCP request handler
│   ├── tools.ts          # Tool definitions (3 tools)
│   └── types.ts          # JSON-RPC type definitions
├── tools/
│   ├── analyze.ts        # spell_check_analyze implementation
│   ├── grammar.ts        # spell_check_grammar implementation
│   └── correct.ts        # spell_check_correct implementation
├── prompts/
│   ├── types.ts          # Grammar prompt configuration interfaces
│   └── grammar-prompts.ts # 53-language grammar prompts registry
└── utils/
    └── responses.ts      # JSON-RPC response helpers

Bindings

Configured in wrangler.jsonc:

  • SPELL_CHECK_DICTS: R2 bucket for dictionaries (170MB, 106 files)
  • SPELL_CHECK_DOCS: R2 bucket for corrected documents (30-day lifecycle)
  • AI: Workers AI binding for grammar checking
  • MCP_METRICS: Analytics Engine for usage tracking

Development

Prerequisites

  • Node.js 18+
  • Cloudflare account
  • Wrangler CLI (npm install -g wrangler)

Setup

# Install dependencies
npm install

# Generate Cloudflare types
npm run cf-typegen

# Start dev server
npm run dev
# Server runs on http://localhost:8787

Testing

# Health check
curl http://localhost:8787/health

# Test spell checking
curl -X POST http://localhost:8787/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "id": 1,
    "method": "tools/call",
    "params": {
      "name": "spell_check_analyze",
      "arguments": {
        "text": "This is a tesst with speling errors"
      }
    }
  }'

Deployment

# Build TypeScript
npm run build

# Deploy to Cloudflare
npm run deploy

Production URL: https://spell-checker-mcp.<your-subdomain>.workers.dev

Configuration

Environment Variables

None required! All bindings (R2, AI) are provisioned automatically via the Deploy to Cloudflare button.

Custom Deployment

If deploying manually:

  1. Create R2 Buckets:

    wrangler r2 bucket create spell-checker-dictionaries
wrangler r2 bucket create spell-checker-documents

  2. Upload Dictionaries:

    npm run upload-dictionaries

  3. Configure Lifecycle Policy (30-day auto-delete):

    wrangler r2 bucket lifecycle set spell-checker-documents \
  --expiration-days 30

  4. Deploy:

    npm run deploy

Performance

Benchmarks

  • Spell check (cached): <50ms
  • Spell check (first load): 200-400ms (R2 fetch + parse)
  • Grammar check: 800-1500ms (AI inference)
  • Auto-correct: 300-2000ms (depends on mode)

Bundle Size

  • Worker bundle: 348KB (gzipped)
  • Dictionaries: 170MB (R2 lazy-loaded, not bundled)

Caching Strategy

  • Dictionaries: In-memory cache (per-language, per-isolate)
  • HTTP responses: Standard Cloudflare CDN caching
  • AI results: No caching (always fresh grammar checks)

Troubleshooting

MCP server not connecting

Check server status:

curl https://spellcheck.mcp.jezweb.ai/health

Verify client configuration:

# Claude Code CLI
claude mcp get spell-checker

Check logs:

wrangler tail
Grammar checking fails

Verify Workers AI binding:

wrangler deployments list

Workers AI binding must be configured in wrangler.jsonc:

{
  "ai": {
    "binding": "AI"
  }
}
R2 upload errors

Check R2 bucket exists:

wrangler r2 bucket list

Verify bindings:

wrangler deployments list

Bindings must match wrangler.jsonc configuration.

Deployment fails

Common issues:

  1. Missing Wrangler login:

    wrangler login

  2. Binding name mismatch:

    • Check wrangler.jsonc binding names
    • Must match variable names in code

  3. TypeScript errors:

    npm run build

Contributing

Contributions welcome! Please:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit changes (git commit -m 'Add amazing feature')
  4. Push to branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

Development Guidelines

  • Use TypeScript strict mode
  • Follow existing code style
  • Add tests for new features
  • Update documentation

Roadmap

  • URL fetching support (spell check content from external URLs)
  • Document format conversion (HTML → text, PDF → text)
  • Chunking for very large documents (>1MB)
  • Custom dictionary management (add/remove words)
  • Language-specific grammar rules refinement
  • Batch processing API
  • WebSocket streaming for real-time checking

License

MIT License - see file for details.

Copyright (c) 2025 Jeremy Dawes (Jezweb)

Author

Jezweb - jeremy@jezweb.net

Acknowledgments

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