The CB Insights MCP Server enables AI agents to interact with CB Insights' ChatCBI LLM through the Model Context Protocol (MCP) standard for querying business intelligence data.
Key Capabilities:
Send messages to ChatCBI: Submit queries to receive intelligent, AI-generated responses with business insights
Maintain conversation context: Continue existing conversations by providing a chat ID from previous interactions, or start fresh sessions without one
Access comprehensive responses: Receive structured data including the message content, related references, source citations, suggested follow-up questions, and conversation titles
Query business intelligence: Leverage CB Insights' data through natural language queries
Integration & development: Designed for AI agent frameworks with support for testing and debugging using the MCP inspector tool
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CB Insights MCP ServerWhat are the latest trends in fintech startups?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
CB Insights MCP Server
Deprecation notice: This repository, serving as an example implementation of a simple self-hosted MCP server that acts as a pass-through to the CB Insights API, is deprecated as of January 2026. CB Insights is pleased to offer a fully supported MCP server at mcp.cbinsights.com, which can be invoked programmatically or through clients like ChatGPT, Claude, and Microsoft Copilot.
The CBI MCP Server provides an interface for developers to interact with CB Insights ChatCBI LLM through AI Agents.
Tools
ChatCBI
Send a message from an agent to ChatCBI and return the response.
Input parameters:
message: The content of your message to ChatCBIchatID(optional): A unique identifier for the chat session, obtained from a previous response. If included, the conversation is continued. Otherwise, a new conversation is started.
Returns JSON object containing the following fields:
chatID: Identifies the conversation. If chatID was provided in the request, this will be the same.message: ChatCBI response to the message.relatedContent: List of related references.sources: List of sources used to generate the response.suggestions: List of suggested follow-up questions.title: Title of the chat
For more information see Using ChatCBI
Related MCP server: MCP Server for Dify AI
Setup
The CBI MCP Server uses uv to manage the project.
Environment variables are set via the .env file:
CBI_CLIENT_ID&CBI_CLIENT_SECRETOAuth Client ID and Secretsee CB Insights API Authentication for usage and how to obtain them
CBI_MCP_TIMEOUT(default: 120)CBI_MCP_PORT(default: 8000)
Usage
With Claude Desktop
Update the claude_desktop_config.json file using the following command:
mcp install server.pyThis will add the following configuration:
{
"mcpServers": {
"cbi-mcp-server": {
"command": "/path/to/.local/bin/uv",
"args": [
"--directory",
"/path/to/cloned/cbi-mcp-server",
"run",
"server.py"
]
}
}
}Debugging
The inspector can be used to test/debug your server.
mcp dev server.py Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.