Mcp Semantic Search
What is Mcp Semantic Search
mcp-semantic-search is an MCP Server designed to search a Vectorize database, enabling efficient retrieval of documentation and information stored in a vectorized format.
Use cases
Use cases include searching technical documentation, retrieving information from knowledge bases, and enhancing user experience in applications that require quick access to relevant data.
How to use
To use mcp-semantic-search, you can deploy it on Cloudflare, test it in Claude Desktop or VSCode, or run it locally with a populated Vectorize DB. For deployment, you can use the command provided in the README, and for local testing, run ‘npm run dev’ and access it via the specified URL.
Key features
Key features include the ability to search documentation efficiently, integration with Cloudflare’s Agents SDK, and compatibility with various testing environments such as AI Playground and VSCode.
Where to use
mcp-semantic-search can be used in various fields including software development, documentation management, and any application requiring efficient semantic search capabilities over large datasets.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Mcp Semantic Search
mcp-semantic-search is an MCP Server designed to search a Vectorize database, enabling efficient retrieval of documentation and information stored in a vectorized format.
Use cases
Use cases include searching technical documentation, retrieving information from knowledge bases, and enhancing user experience in applications that require quick access to relevant data.
How to use
To use mcp-semantic-search, you can deploy it on Cloudflare, test it in Claude Desktop or VSCode, or run it locally with a populated Vectorize DB. For deployment, you can use the command provided in the README, and for local testing, run ‘npm run dev’ and access it via the specified URL.
Key features
Key features include the ability to search documentation efficiently, integration with Cloudflare’s Agents SDK, and compatibility with various testing environments such as AI Playground and VSCode.
Where to use
mcp-semantic-search can be used in various fields including software development, documentation management, and any application requiring efficient semantic search capabilities over large datasets.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Semantic Search MCP Server
An MCP Server using the Agents SDK that can search documentation stored
in a Vectorize database.
The same code that powers the MCP Server at https://mcp.developers.cloudflare.com/sse (or https://mcp.developers.cloudflare.com/mcp for the stateless version)
Using in Claude Desktop
{
"mcpServers": {
"cloudflare-docs": {
"command": "npx", // or may need the full path, eg if using volta: "/Users/myuser/.volta/bin/npx"
"args": ["mcp-remote@latest", "https://mcp.developers.cloudflare.com/mcp"]
// Below only needed if you're using a Zero Trust client like Cloudflare WARP
// "env": {
// "NODE_EXTRA_CA_CERTS": "/path/to/certificate.pem"
// }
}
}
}
Testing in Cloudflare’s AI Playground
Go to https://playground.ai.cloudflare.com/ and enter https://mcp.developers.cloudflare.com/mcp as the MCP Server
Testing in VSCode
Type Shift-Cmd-P and choose “MCP: Add Server…” and then choose “HTTP (server-sent events)”, then enter https://mcp.developers.cloudflare.com/sse as the URL.
Testing locally (requires a populated Vectorize DB)
npm run dev
Then go to https://playground.ai.cloudflare.com/ and enter http://localhost:8787/mcp as the MCP Server
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
