Advanced
Let AI agents like Claude, Cursor, and Windsurf query your chatbot’s knowledge base directly using the Model Context Protocol. Includes automatic WebMCP browser discovery.
Every AI Chatbot chatbot can act as an MCP (Model Context Protocol) server, giving AI agents direct access to your knowledge base. Instead of scraping your website or chat widget, agents connect to a structured endpoint and get accurate, sourced answers from your trained content.
AI Chatbot supports two ways for AI agents to access your knowledge base:
AI agents are becoming the primary way people find and interact with information. When a developer asks Cursor about your API, or a user asks Claude about your product, those agents need a reliable source of truth. Your MCP server provides that.
When an AI agent connects to your MCP server endpoint, it gets access to one tool:
query_knowledge_base - Searches your chatbot’s trained content using the full RAG pipeline (vector search, query expansion, and Cohere reranking). Returns relevant content chunks with source URLs.
The agent sends a natural language query, and your MCP server returns the most relevant content from your training sources - the same content your chatbot uses to answer questions.
In your chatbot dashboard, select your chatbot and go to Settings.
Click the Advanced tab.
Scroll down to the MCP Server (Public Access) section.
Toggle Public MCP Access to allow AI agents to query your knowledge base without authentication.
When disabled, agents need a valid API token to connect (see Authentication below).
Click the copy button next to your MCP Endpoint URL. This is the URL AI agents will use to connect.
Your endpoint URL follows this format:
https://chatbot.sitespeak.ai/api/{chatbotId}/server/mcp
Click Save to apply your changes.
WebMCP lets AI agents running in the browser automatically discover and query your knowledge base, with zero configuration from the end user. When someone visits your website with a WebMCP-compatible browser or AI assistant, the chatbot widget registers itself as a tool the agent can use.
When your chatbot widget loads on a page, it checks for navigator.modelContext support in the browser. If available, the widget automatically registers a tool called query_{your_chatbot_name} that the browser’s AI agent can call.
When an AI agent calls this tool:
This is different from the standard MCP server endpoint, where the full RAG pipeline (including the LLM response) runs server-side. With WebMCP, the browser’s AI agent handles the synthesis step, making responses faster and more contextual to the user’s conversation.
No additional setup is needed. Once both conditions are met, any visitor using a WebMCP-compatible browser will have automatic access to your knowledge base through their AI agent.
Go to Settings
In your chatbot dashboard, select your chatbot and go to Settings.
Open Advanced settings
Click the Advanced tab.
Enable Public MCP Access
Toggle Public MCP Access on. This enables both the MCP server endpoint and WebMCP browser discovery.
Click Save to apply your changes.
That’s it. As long as your chatbot widget is installed on your website, WebMCP will work automatically for any visitor using a compatible browser.
Your MCP server supports two access modes:
When Public MCP Access is enabled, any AI agent can query your knowledge base without a token. This is the simplest option and works well when you want maximum reach - for example, letting anyone’s Claude or Cursor instance access your documentation.
When Public MCP Access is disabled, agents must include a valid API token in the Authorization header:
Authorization: Bearer YOUR_API_TOKEN
Generate an API token from your Account page. This is the same token used for the AI Chatbot REST API.
Add your MCP server to Claude Desktop’s configuration file:
Edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"my-knowledge-base": {
"type": "url",
"url": "https://chatbot.sitespeak.ai/api/{chatbotId}/server/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Edit %APPDATA%\Claude\claude_desktop_config.json:
{
"mcpServers": {
"my-knowledge-base": {
"type": "url",
"url": "https://chatbot.sitespeak.ai/api/{chatbotId}/server/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Restart Claude Desktop. You should see your knowledge base listed as an available tool.
Add your MCP server in Cursor’s settings:
If using authenticated access, add the Authorization header in the server configuration.
Add your MCP server in Windsurf’s MCP configuration:
{
"mcpServers": {
"my-knowledge-base": {
"serverUrl": "https://chatbot.sitespeak.ai/api/{chatbotId}/server/mcp"
}
}
}
Any MCP-compatible client can connect using the Streamable HTTP transport:
MCP server requests are rate-limited to 30 requests per minute per IP address. This is separate from your chat widget rate limits.
Each query to query_knowledge_base uses one query credit from your monthly allowance:
Pro
1,000
Pro Plus
2,500
Business
10,000
Track your usage on the Usage page in your account settings.
When your monthly limit is reached, the server returns a 429 status code. Credits reset at the start of each billing cycle.
Expose your product documentation so developers using Cursor, Windsurf, or Claude can look up your APIs, configuration options, and guides without leaving their editor.
Connect your company’s trained chatbot to your team’s AI tools. Sales teams can query product specs from Claude, support teams can look up troubleshooting guides, and engineers can search internal docs - all through the tools they already use.
Expose your product documentation so developers using Cursor, Windsurf, or Claude can look up your APIs, configuration options, and guides without leaving their editor.
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