About LLM Brand Monitor
LLM Brand Monitor is an MCP server published by SerpstatGlobal in the AI category: track how 350+ AI models mention your brand — manage projects, run scans, analyze results.
The repository has 1 stars and 0 forks, with the last commit 6 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
claude mcp add llm-brand-monitor -- npx -y @serpstat/llm-brand-monitor-mcpnpx -y @serpstat/llm-brand-monitor-mcpThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (7)
lbm_add_promptsAdd monitoring prompts to a project
Parameters not published.
lbm_archive_projectArchive a project
Parameters not published.
lbm_create_projectCreate a new project
Parameters not published.
lbm_delete_promptRemove a prompt from a project
Parameters not published.
lbm_get_projectGet project details with prompts and models
Parameters not published.
lbm_list_projectsList all brand monitoring projects
Parameters not published.
lbm_update_projectUpdate project name, models, or monitoring settings
Parameters not published.
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README
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-mcp
From Source
git clone https://github.com/SerpstatGlobal/llm-brand-monitor-mcp.git
cd llm-brand-monitor-mcp
npm install && npm run build
Then 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.js
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 |
|---|---|
lbm_list_projects |
List all brand monitoring projects |
lbm_get_project |
Get project details with prompts and models |
lbm_create_project |
Create a new project |
lbm_update_project |
Update project name, models, or monitoring settings |
lbm_archive_project |
Archive a project |
lbm_add_prompts |
Add monitoring prompts to a project |
lbm_delete_prompt |
Remove a prompt from a project |
Scans (3 tools)
| Tool | What it does |
|---|---|
lbm_run_scan |
Start a scan — sends prompts to LLMs and collects responses |
lbm_get_scan_status |
Check scan progress |
lbm_list_scans |
View scan history |
Results (5 tools)
| Tool | What it does |
|---|---|
lbm_list_results |
Browse monitoring results (brand mentions, status) |
lbm_get_transcript |
Read the full LLM response for a specific result |
lbm_list_competitors |
See which competitor brands LLMs mention |
lbm_list_links |
See which URLs and domains LLMs cite |
lbm_get_history |
Competitor mention trends over time |
Models & Usage (2 tools)
| Tool | What it does |
|---|---|
lbm_list_models |
List 350+ available LLM models |
lbm_get_usage |
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_competitors
Token-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 |
|---|---|---|---|
LBM_API_KEY |
Yes | — | API key from llmbrandmonitor.com |
LBM_API_BASE_URL |
No | https://llmbrandmonitor.com/api/v1 |
API base URL |
LOG_LEVEL |
No | info |
error, warn, info, debug |
Error Handling
Errors include actionable hints for the LLM:
| Error | Hint |
|---|---|
INSUFFICIENT_CREDITS |
Check balance with lbm_get_usage. Top up at llmbrandmonitor.com/pricing |
RATE_LIMITED |
Wait a few seconds and retry |
NOT_FOUND |
Call lbm_list_projects to verify the ID exists |
UNAUTHORIZED |
API key is invalid — check LBM_API_KEY |
Development
npm install
npm run build # TypeScript → dist/
npm test # 126 tests
API Documentation
Full REST API docs: llmbrandmonitor.com/api-docs
License
MIT
README copy captured when this server was indexed; it may lag the repository. The original is authoritative.