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LLM Brand Monitor

mcp-serpstatglobal-llm-brand-monitor-mcp · by SerpstatGlobal

Track how 350+ AI models mention your brand — manage projects, run scans, analyze results

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Install

$ agentstack add mcp-serpstatglobal-llm-brand-monitor-mcp

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v1.0.1 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v1.0.1. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

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About

LLM Brand Monitor MCP Server

[](https://www.npmjs.com/package/@serpstat/llm-brand-monitor-mcp) [](https://lobehub.com/mcp/serpstatglobal-llm-brand-monitor-mcp) [](https://opensource.org/licenses/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_)

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

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v1.0.1 Imported from the upstream source.