Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-domain-radar Check if mybrand.com is available"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server that checks domain availability in real-time during brand naming.
Name your brand. Check the domain. All in one conversation.
We've all been there:
You: "Suggest a name for my service"
AI: "How about NexFlow?"
You: Search nexflow.com... already taken
You: "Another one"
AI: "DataPulse?"
You: Search datapulse.com... also taken
You: "..."
(repeat 10 times)Install mcp-domain-radar once, and your AI checks domain availability the moment it thinks of a name. No more switching between browser and terminal.
Related MCP server: Domain Checker MCP Server
1. Install
npm install -g mcp-domain-radar2. Connect to your AI coding tool
claude mcp add domain-radar -- mcp-domain-radarcodex mcp add domain-radar -- npx mcp-domain-radarAdd to .cursor/mcp.json:
{
"mcpServers": {
"domain-radar": {
"command": "npx",
"args": ["mcp-domain-radar"]
}
}
}Add to claude_desktop_config.json:
{
"mcpServers": {
"domain-radar": {
"command": "npx",
"args": ["mcp-domain-radar"]
}
}
}3. Install the brand-naming skill (optional, Claude Code only)
mkdir -p ~/.claude/skills/brand-naming
cp node_modules/mcp-domain-radar/.claude/skills/brand-naming/SKILL.md ~/.claude/skills/brand-naming/Or copy it manually from the GitHub repo.
4. Use it
With the skill installed, type /brand-naming in Claude Code to start a guided naming session.
Or just talk naturally:
"I'm building a task management app for developers.
Help me find a brand name with an available domain."Claude will automatically check domains as it brainstorms.
Tool | What it does |
| Check exact domain names — |
| Check one name across 17+ TLDs at once — |
| Generate name variations from keywords & check all — |
| Show all TLDs this server supports |
Category | TLDs |
Classic |
|
Tech / Startup |
|
Trending |
|
Creative |
|
Commerce |
|
Country |
|
You: Check if "nexflow" is available — try .com, .io, .ai, and .devAVAILABLE:
+ nexflow.dev
+ nexflow.ai
TAKEN:
- nexflow.com
- nexflow.io
--- 2 available / 2 taken / 0 unknown ---You: I need a name for an AI code review tool.
Keywords: code, review, pulse, scan.
Find me names with available domains.Generated 20 name variations from: code, review, pulse, scan
Checking .com .io .ai .dev .app .co for each
+ codepulse (compound) — available: .dev, .ai | taken: .com, .io
+ scanflow (suffix) — available: .ai, .dev, .app | taken: .com
+ getpulse (prefix) — available: .dev, .co | taken: .com, .io, .ai
+ revscan (blend) — available: .com, .io, .ai, .dev, .app, .co
- codelab (suffix) — all checked TLDs taken
TOP PICKS (have available domains):
revscan → revscan.com, revscan.io, revscan.ai, revscan.dev, revscan.app, revscan.co
codepulse → codepulse.dev, codepulse.ai
scanflow → scanflow.ai, scanflow.dev, scanflow.appbrand-naming promptThe server includes a built-in prompt template that walks you through the full naming process step by step.
Your question
│
▼
Claude brainstorms names
│
▼
mcp-domain-radar
├── 1. DNS lookup (fast — if it resolves, it's taken)
└── 2. WHOIS query (definitive — checks registration status)
│
▼
Only names with available domains are recommendedNo API keys required — uses native DNS and WHOIS protocols
Rate-limit friendly — batches queries with delays
Works offline for DNS checks — WHOIS requires network
git clone https://github.com/sonwr/mcp-domain-radar.git
cd mcp-domain-radar
npm install
npm run buildTest locally:
claude mcp add domain-radar -- node ./dist/index.jsDomain price estimation per registrar
Expiring / recently dropped domain suggestions
Registrar API integration (Namecheap, Cloudflare, GoDaddy)
Internationalized domain name (IDN) support
More TLDs and WHOIS servers
Contributions welcome! Open an issue or PR.
MIT
Check domain availability for a single brand name across many popular TLDs at once. Default TLDs: .com .io .dev .app .ai .co .so .me .xyz .tech .net .sh .run .cloud .to .gg .cc Supports 30+ TLDs including trending ones like .ai, .gg, .so, .lol, .wtf, .cool.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Brand / product / service name without TLD, e.g. "nexflow" | |
| tlds | No | Custom list of TLDs to check. Omit to use the default popular set. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the tool checks availability, implying a read operation, but does not mention any side effects, rate limits, or return format. For a simple read tool, this is minimally adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loading the purpose in the first sentence and adding important detail about TLDs in the second. No extraneous text; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with two parameters and no output schema. The description provides the default TLD list and mentions support for 30+ TLDs, which is sufficient context for the tool's use. A minor gap is the lack of indication of what the output looks like, but it is not essential for a check tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds value beyond the schema by enumerating the default TLDs (.com .io .dev .app .ai etc.) and noting that it supports 30+ TLDs including trending ones. This provides context for the 'tlds' parameter that the schema alone does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks domain availability for a single brand name across many TLDs. It includes a specific verb (check) and resource (domain availability), and distinguishes itself from siblings like 'check_domains' and 'suggest_and_check_domains' by focusing on a single brand name and listing default TLDs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use the tool (for a single brand name) and how to customize TLDs, but does not explicitly exclude alternatives or provide when-not-to-use guidance. It offers clear parameter usage instructions: 'Omit to use the default popular set.' This provides sufficient context for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check availability of specific domain names. Use this when you already have exact domain names to verify (e.g. "mybrand.com", "mybrand.ai"). Checks via DNS + WHOIS for accurate results.
| Name | Required | Description | Default |
|---|---|---|---|
| domains | Yes | Full domain names including TLD, e.g. ["cool.ai", "cool.com", "cool.dev"] |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavior. It discloses the method: 'Checks via DNS + WHOIS for accurate results.' However, it does not mention potential side effects, rate limits, or result format. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two sentences. Front-loaded with the main purpose, followed by usage guidance and method. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a simple tool with one parameter and no output schema, the description is fairly complete. It covers purpose, usage context, and method. It could mention the output format (e.g., availability status per domain) but the lack is minor.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'domains' well-described in the schema. The tool description adds example values but does not provide additional semantic meaning beyond the schema. Baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking availability of specific domain names. It distinguishes itself from siblings by emphasizing that it operates on exact domain names, contrasting with tools like 'suggest_and_check_domains' which suggest domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly indicates when to use this tool: 'Use this when you already have exact domain names to verify.' It provides examples, making the usage context clear. Lacks explicit when-not guidance, but the context of siblings implies when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all TLDs that this server can check via WHOIS, grouped by category.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses a read-only operation that lists TLDs grouped by category. This is adequate for a simple list tool, though no additional behavioral traits like rate limits or authentication needs are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, concise sentence that efficiently conveys the tool's purpose without any wasted words or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters, no output schema, and is a straightforward listing operation, the description is fully complete. It tells the agent exactly what the tool does and how the results are organized.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%. Baseline for 0 params is 4. The description adds no parameter info, which is appropriate since no parameters exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all TLDs the server can check via WHOIS, grouped by category, which is a specific verb-resource combination. It distinguishes from sibling tools like check_domains which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The context implies it's used to discover supported TLDs before using check tools, but no when-not or alternative direction is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate brand-name variations from keywords, then check domain availability for each. Creates variations using prefixes (get-, try-, my-…), suffixes (-hq, -lab, -flow…), compounds (keyword1+keyword2), and portmanteau blends. Great for brainstorming when obvious names are taken.
| Name | Required | Description | Default |
|---|---|---|---|
| keywords | Yes | Root keywords to generate variations from, e.g. ["pulse", "data"] | |
| tlds | No | TLDs to check per variation. Default: com, io, ai, dev, app, co | |
| max_variations | No | Max name variations to generate & check. Default: 20 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It explains generation methods (prefixes, suffixes, compounds, blends) and domain checking, but omits return format, auth needs, or rate limits. Adequate but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences plus a third usage hint, front-loaded with the main action. It is appropriately sized and structured, though could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain return format or data structure, but it does not. It also does not explicitly differentiate from sibling tools beyond the implicit generation step. Somewhat incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for each parameter. The tool description adds meaningful context about how variations are generated (prefixes, suffixes, etc.), supplementing the schema and aiding agent understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates brand-name variations from keywords and checks domain availability. It distinguishes from siblings (check_brand_domains, check_domains, list_supported_tlds) by combining generation and checking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit context ('Great for brainstorming when obvious names are taken') but does not specify when not to use or explicitly name alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.2check_brand_domainscheck_domainslist_supported_tldssuggest_and_check_domainsScored across 4 tools
Each tool has a distinct purpose: checking a brand across TLDs, checking specific domains, listing TLDs, and brainstorming variations. Minor potential confusion between check_brand_domains and check_domains, but descriptions clarify the difference.
Tool names follow a verb_noun pattern (check_, list_, suggest_and_check_). The compound verb in suggest_and_check_domains is a slight deviation, but overall consistent.
Four tools is appropriate for the domain checking and suggestion use case. Not too few or too many, each earns its place.
Covers core functionality: checking specific domains, checking a brand across TLDs, suggesting variations, and listing supported TLDs. Minor gaps like bulk brand checking or WHOIS details beyond availability, but sufficient for typical use.
AI-powered domain & business name generation with real-time availability checks.
AI-powered domain & business name generation with real-time availability checks.
Buy & manage domains from any AI chat: availability, register, DNS, email forwarding, AI bot stats.
Domain search, registration, DNS, marketplace, and checkout with your AI agent.