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LLM Brand Monitor

LLM Brand Monitor

Local
llmbrandmonitor.comBusiness & Marketing1Updated 27w ago

About LLM Brand Monitor

LLM Brand Monitor MCP Server connects compatible clients to the LLM Brand Monitor platform to manage projects, scan model responses, and analyze results. It offers 17 tools for projects, scans, results, and model usage.

Key features

  1. 01Create and manage monitoring projects and prompts
  2. 02Run scans and check progress and history
  3. 03Review brand mentions, competitors, and cited links
  4. 04Track competitor mention trends
  5. 05List available models and check usage

Use cases

  1. 01Set up brand-monitoring projects and prompts
  2. 02Scan model responses for brand mentions
  3. 03Compare competitor mentions and trends
  4. 04Review scan results, cited sources, and credit usage

MCP support

The MCP server uses the LLM Brand Monitor API and exposes 17 tools for project management, scans, results, and model usage to compatible clients. An LBM_API_KEY is required.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"serpstatglobal-llm-brand-monitor": {
"command": "npx",
"args": [
"-y",
"@serpstat/llm-brand-monitor-mcp"
],
"env": {
"LBM_API_KEY": "<LBM_API_KEY>"
}
}
}
}
Run commandnpx -y @serpstat/llm-brand-monitor-mcp
Environment variables to set
LBM_API_KEYSecretAPI key from llmbrandmonitor.com/profile

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@serpstat/llm-brand-monitor-mcp1.0.1

Tools

17

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
limitnumberNoItems per page (default: 20, max: 100)
offsetnumberNoItems to skip (default: 0)
statusstringNoOptional: filter by status (active, inactive, pending)
include_all_fieldsbooleanNoSet true for full JSON response. Default: false (compact CSV — recommended).

Details

From the project README

LLM Brand Monitor MCP Server

npm version MCP Badge License: MIT

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

  1. Sign up at llmbrandmonitor.com
  2. Open your Profile page
  3. Copy your API key (starts with lbm_)
API key in LLM Brand Monitor profile

Tools

17 tools across 4 categories:

Projects (7 tools)
ToolWhat it does
lbm_list_projectsList all brand monitoring projects
lbm_get_projectGet project details with prompts and models
lbm_create_projectCreate a new project
lbm_update_projectUpdate project name, models, or monitoring settings
lbm_archive_projectArchive a project
lbm_add_promptsAdd monitoring prompts to a project
lbm_delete_promptRemove a prompt from a project
Scans (3 tools)
ToolWhat it does
lbm_run_scanStart a scan — sends prompts to LLMs and collects responses
lbm_get_scan_statusCheck scan progress
lbm_list_scansView scan history
Results (5 tools)
ToolWhat it does
lbm_list_resultsBrowse monitoring results (brand mentions, status)
lbm_get_transcriptRead the full LLM response for a specific result
lbm_list_competitorsSee which competitor brands LLMs mention
lbm_list_linksSee which URLs and domains LLMs cite
lbm_get_historyCompetitor mention trends over time
Models & Usage (2 tools)
ToolWhat it does
lbm_list_modelsList 350+ available LLM models
lbm_get_usageCheck 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

VariableRequiredDefaultDescription
LBM_API_KEYYes—API key from llmbrandmonitor.com
LBM_API_BASE_URLNohttps://llmbrandmonitor.com/api/v1API base URL
LOG_LEVELNoinfoerror, warn, info, debug

Error Handling

Errors include actionable hints for the LLM:

ErrorHint
INSUFFICIENT_CREDITSCheck balance with lbm_get_usage. Top up at llmbrandmonitor.com/pricing
RATE_LIMITEDWait a few seconds and retry
NOT_FOUNDCall lbm_list_projects to verify the ID exists
UNAUTHORIZEDAPI 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

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.