MCP Aggregator

Overview

A unified MCP (Model Context Protocol) aggregator that routes AI agent tool calls across 11 connected servers through a single gateway. Builder project management, research pipelines, web scraping, knowledge base, and more.

What it connects

• Builder Agent - task management, lessons learned, session tracking
• Research Pipeline - deep research with expert panels and debate synthesis
• Knowledge Base - semantic search across conversation history
• Web Tools - Firecrawl scraping, Perplexity search, Playwright automation
• Media Tools - YouTube transcript extraction, document conversion

Architecture

Single aggregator process on port 4072 discovers and connects to tool servers, normalizes their schemas, and routes calls transparently. Agents see one unified tool catalog - they don’t need to know which server handles what.

How it evolved

Started as a simple proxy for one MCP server. Then a second server needed connecting. Then a third. By server five, the pattern was clear: every AI project needed tool access, and managing separate connections was unsustainable.

The breakthrough was schema normalization - different servers expose tools differently. The aggregator learned to flatten, merge, and route transparently. A bug where the aggregator stripped parameter schemas (returning empty properties: {}) taught us that the contract between aggregator and server must be exact. That bug blocked three other projects before we caught it.

The Builder Agent tools (task tracking, lessons, sessions) emerged from needing to coordinate work across projects. The research pipeline (expert panels, debate synthesis) was the most ambitious addition - it turns a research question into a structured multi-expert investigation.

Next: self-healing connections, automatic server discovery, and a visual dashboard showing tool usage patterns across all projects.