Question 1

What is an MCP Server?

Accepted Answer

An MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

Question 2

Why would I need an MCP Aggregator?

Accepted Answer

An MCP Aggregator is useful for combining multiple MCP servers into a single interface. This helps overcome limitations in clients (like Cursor) that restrict the number of concurrent MCP connections, simplifies configuration, and resolves potential tool name conflicts.

Question 3

How does the MCP Aggregator work?

Accepted Answer

The MCP Aggregator functions as both an MCP server (to the client) and an MCP client (to the backend servers). It receives requests from the client, routes them to the appropriate backend server, and aggregates the responses before returning them to the client.

Question 4

What is tool name sanitization?

Accepted Answer

Tool name sanitization is the process of replacing dashes with underscores in tool names. This is necessary because some clients, like Cursor, have issues with tools that contain dashes in their names. The MCP Aggregator performs this sanitization automatically.

Question 5

How do I configure the MCP Aggregator?

Accepted Answer

The MCP Aggregator is configured using a JSON file (e.g., `config.json`). This file defines the connection details for each backend MCP server, including the command to execute, arguments, environment variables, and optional tool filtering rules.

Question 6

What are the available deployment options?

Accepted Answer

The MCP Aggregator can be deployed using several methods, including: Installation script, `go install`, Docker, and Makefile.

Question 7

What environment variables does the MCP Aggregator support?

Accepted Answer

The MCP Aggregator supports the following environment variables: `MCP_CONFIG`, `MCP_LOG_LEVEL`, `MCP_LOG_FILE`, `MCP_PROTOCOL_VERSION`, and `MCP_CURSOR_MODE`.

Question 8

How does the MCP Aggregator integrate with UBOS?

Accepted Answer

The MCP Aggregator integrates seamlessly with the UBOS platform, enabling you to leverage the full power of UBOS for AI agent development, orchestration, and deployment.

Question 9

What is tool filtering, and how do I use it?

Accepted Answer

Tool filtering allows you to selectively expose tools from each backend MCP server. To enable tool filtering, add a `tools` object to your server configuration with an `allowed` array listing the tools you want to expose. This can help to limit the number of exposed tools, avoid name conflicts, and improve performance.

MCP Aggregator

Resources

Project Details

Recomended MCP Servers

Featured Templates

AI Chatbot Starter Kit

Talk with Claude 3

Sarcastic AI Chat Bot

AI Chat Bot: Text, Voice, and Video Magic

Service ERP

Python Bug Fixer

Start your free trial