LLM Brand Monitor MCP Server
OfficialClick on "Install 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., "@LLM Brand Monitor MCP ServerList all my brand monitoring projects."
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.
LLM Brand Monitor MCP Server
MCP server for LLM Brand Monitor — a platform that tracks how AI models mention your brand.
Connect Claude, Cursor, Windsurf, or any MCP-compatible client to manage brand monitoring projects, run scans across 350+ LLMs, and analyze results — all through natural language.
Quick Start
Claude Desktop
Add to your claude_desktop_config.json:
{
"mcpServers": {
"lbm": {
"command": "npx",
"args": ["-y", "@serpstat/llm-brand-monitor-mcp"],
"env": {
"LBM_API_KEY": "lbm_your_key_here"
}
}
}
}Claude Code
claude mcp add lbm-mcp -e LBM_API_KEY=lbm_your_key_here -- npx -y @serpstat/llm-brand-monitor-mcpFrom Source
git clone https://github.com/SerpstatGlobal/llm-brand-monitor-mcp.git
cd llm-brand-monitor-mcp
npm install && npm run buildThen add to your MCP client config:
{
"mcpServers": {
"lbm": {
"command": "node",
"args": ["/path/to/llm-brand-monitor-mcp/dist/index.js"],
"env": {
"LBM_API_KEY": "lbm_your_key_here"
}
}
}
}MCP Inspector
LBM_API_KEY=lbm_your_key_here npx @modelcontextprotocol/inspector node dist/index.jsRelated MCP server: ai-visibility-mcp
Getting an API Key
Sign up at llmbrandmonitor.com
Open your Profile page
Copy your API key (starts with
lbm_)
Tools
17 tools across 4 categories:
Projects (7 tools)
Tool | What it does |
| List all brand monitoring projects |
| Get project details with prompts and models |
| Create a new project |
| Update project name, models, or monitoring settings |
| Archive a project |
| Add monitoring prompts to a project |
| Remove a prompt from a project |
Scans (3 tools)
Tool | What it does |
| Start a scan — sends prompts to LLMs and collects responses |
| Check scan progress |
| View scan history |
Results (5 tools)
Tool | What it does |
| Browse monitoring results (brand mentions, status) |
| Read the full LLM response for a specific result |
| See which competitor brands LLMs mention |
| See which URLs and domains LLMs cite |
| Competitor mention trends over time |
Models & Usage (2 tools)
Tool | What it does |
| List 350+ available LLM models |
| Check credit balance and usage stats |
Typical Workflow
You: "What brand monitoring projects do I have?"
Claude: → lbm_list_projects
You: "Run a scan on the Serpstat project"
Claude: → lbm_run_scan (asks you to confirm — scans spend credits)
→ lbm_get_scan_status (polls until complete)
You: "Show me the results — which models mentioned my brand?"
Claude: → lbm_list_results
You: "What did GPT-5 say exactly?"
Claude: → lbm_get_transcript
You: "Who are my competitors according to AI models?"
Claude: → lbm_list_competitorsToken-Efficient Responses
All list tools return compact CSV by default instead of verbose JSON. This reduces token usage by 80–96%, keeping responses within context limits.
# Default (CSV) — 3-6 key columns
competitor,mentions,visibility_pct
Competitor A,178,72.4
Competitor B,105,42.7
# Full JSON — pass include_all_fields: true
{"data": [{"competitor_id": "...", "competitor_name": "Competitor A", ...}]}All list tools support offset and limit for pagination.
Configuration
Variable | Required | Default | Description |
| Yes | — | API key from llmbrandmonitor.com |
| No |
| API base URL |
| No |
|
|
Error Handling
Errors include actionable hints for the LLM:
Error | Hint |
| Check balance with |
| Wait a few seconds and retry |
| Call |
| API key is invalid — check |
Development
npm install
npm run build # TypeScript → dist/
npm test # 126 testsAPI Documentation
Full REST API docs: llmbrandmonitor.com/api-docs
License
MIT
Maintenance
Resources
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If you are the server author, to access and configure the admin panel.
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