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Track how 350+ AI models mention your brand — manage projects, run scans, analyze results
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Track how 350+ AI models mention your brand — manage projects, run scans, analyze results
Security Report
4.8
Use Caution4.8High RiskThis MCP server is well-architected with proper authentication, secure credential handling, and no malicious patterns detected. The codebase demonstrates good security practices with input validation, error handling, and appropriate permissions scoped to the LLM Brand Monitor API. Minor code quality observations noted but do not materially impact security posture. Supply chain analysis found 4 known vulnerabilities in dependencies (0 critical, 2 high severity). Package verification found 1 issue.
7 files analyzed · 8 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
What You'll Need
Set these up before or after installing:
API key from llmbrandmonitor.com/profileRequired
Environment variable: LBM_API_KEY
How to Install
Add this to your MCP configuration file:
{
"mcpServers": {
"io-github-serpstatglobal-llm-brand-monitor": {
"env": {
"LBM_API_KEY": "your-lbm-api-key-here"
},
"args": [
"-y",
"@serpstat/llm-brand-monitor-mcp"
],
"command": "npx"
}
}
}Documentation
View on GitHubFrom the project's GitHub 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
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