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Two MCP servers, one design pattern
Two production Model Context Protocol servers giving AI agents structured access to TomTom APIs. Both open source, both authored end-to-end (TypeScript, design + impl + docs).
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#mcp
4 items · 3 projects · 1 feed item
projects
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TomTom Traffic Agent (CES 2026 demo)
Production multi-agent system for traffic analytics, demoed by Product Management at CES 2026 Las Vegas. Five specialised agents (routing, route monitoring, junction analytics, area analysis, traffic volumes) orchestrated through Agno's Team abstraction, served over AG-UI v1.0 with persistent chat memory.
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Neighbourly, AI location analyser (hackathon project)
Full-stack AI app that takes an address and returns a comprehensive neighbourhood profile (POIs, accessibility, routing to key destinations, market signal, livability score) by orchestrating a multi-step agent workflow over the TomTom MCP servers. Hackathon project that showcases MCP usage.
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Designing tools for LLMs: what makes a tool the model actually uses
Tool naming, description writing, argument schemas, error envelopes, idempotency. Lessons from authoring two production MCP servers, with the patterns I now reach for and the mistakes I've stopped making.