LLM Pulse MCP Server
Monitors brand mentions, citations, sentiment, competitor share of voice, and GEO performance across AI search engines.
README
LLM Pulse MCP Server
LLM Pulse is an AI visibility analytics platform for monitoring brand mentions, citations, sentiment, competitor share of voice, and GEO performance across AI search engines.
This repository contains a small runnable wrapper for the hosted LLM Pulse MCP server. It does not contain the private LLM Pulse application source code.
Hosted MCP Endpoint
https://api.llmpulse.ai/api/v1/mcp
Transport: Streamable HTTP
Authentication: Bearer token
Create an LLM Pulse API key in the app, then send it as:
Authorization: Bearer llmpulse_your_key_here
API keys are available on Scale plans and above.
Local MCP Wrapper
Run the wrapper with an API key to expose the hosted LLM Pulse MCP tools through stdio:
npm install
LLMPULSE_API_KEY=llmpulse_your_key_here npm start
Without LLMPULSE_API_KEY, the wrapper still starts and exposes a read-only setup/status tool. This lets registries verify that the server starts and responds to MCP introspection without requiring a secret.
Docker
docker build -t llmpulse-mcp .
docker run --rm -i -e LLMPULSE_API_KEY=llmpulse_your_key_here llmpulse-mcp
What It Provides
- Project and competitor dimensions
- AI visibility, mention rate, citation rate, and weighted visibility metrics
- Brand mentions, citations, sources, sentiments, and prompt execution data
- Share of voice and top source analytics
- Recommendation, GEO Writer, Search Console, and AI traffic data where plan access allows
Documentation
- API docs: https://api.llmpulse.ai/api-docs
- OpenAPI: https://api.llmpulse.ai/openapi.json
- Product site: https://llmpulse.ai
Example MCP Client Configuration
{
"mcpServers": {
"llm-pulse": {
"type": "streamable-http",
"url": "https://api.llmpulse.ai/api/v1/mcp",
"headers": {
"Authorization": "Bearer llmpulse_your_key_here"
}
}
}
}
Support
Questions? Contact info@llmpulse.ai.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.