Building BookCompass with Mastra: From AI Agent to Telex Integration

Ayomikun Adeosun — Mon, 03 Nov 2025 21:24:20 +0000

Introduction

AI agents are evolving from gimmicks into practical knowledge tools — and what used to require custom infrastructures, caching, state machines, and hand-wired API logic… can now be built in days, not weeks.

That’s exactly what happened with BookCompass — a Mastra powered Book Knowledge Assistant that uses Google Books to help readers:

discover books
retrieve authors & their titles
get recommendations and related titles
and interact conversationally

In this post, I’ll walk through how I built BookCompass using Mastra agents + tools, and then deployed it into Telex.im — a platform like Make/Zapier but optimized for AI agents & workflows.

The result?

A knowledge assistant that can sit inside a community, classroom, or reading club… and answer contextual book queries instantly.

What is Telex?

Telex.im is a new category of platform: AI co-workers.

Not chatbots.
Not LLM demos.
Not Slack integrations that only respond with boilerplate messages.

Telex lets you deploy agents that can:

respond in channels
call tools
fetch external data
chain workflows
talk to other agents (A2A)

And all of this is standardized with the A2A Protocol.

Because Mastra already speaks A2A out of the box — the connection was basically plug-and-play.

Project Overview

BookCompass combines:

Google Books Data + Mastra Tools + Telex Integration

The assistant currently supports:

Feature

Book Search: Search books by keywords or title

Author Books: Retrieve top N books from a specific author

Recommended Titles: Suggest similar titles based on a query

Mastra Features Used

1) Agents

Mastra’s Agent class handled the “brain” of BookCompass — instructions, tools, model config, and memory.

Model used: Google Gemini 2.5 Pro

2) Tools

I created multiple tools using createTool():

searchBooksTool
getAuthorBooksTool
getRecommendationsTool

All API calls hit Google Books — which conveniently requires no auth, no token.
Huge advantage for prototyping.

3) Workflows

While not required, I built a small one for recommendations (lookup book → then lookup similar authors).

4) Memory

Using LibSQL store — BookCompass can keep conversation context (so if a user says “show me more like that one”, it resolves the last book reference).

5) Observability + Logging

Mastra captures agent execution traces, tool calls, performance stats — which made debugging API responses easier.

6) Telex Integration

This part was shockingly easy.

POST /a2a/agent/bookCompass
GET  /a2a/agent/bookCompass/card

Telex reads the agent card → understands:

tools
capabilities
instructions

And now BookCompass can live inside any Telex workspace.

API Integration Surprises

Even though Google Books is open/no auth, there were still small quirks:

authors are stored as arrays
some results return only partial metadata
some books have no ISBN

So I wrote a simple normalization utility that always returns:


{
  title,
  authors,
  categories,
  description,
  previewLink
}

Small detail, big impact.

Key Learnings

Takeaway

Type Safety helps: Zod schemas caught malformed Google Books responses

A2A is powerful: Telex didn’t require ANY custom integration special casing

Memory improves UX: “show me more from that author” now works naturally

Simplicity wins: Google Books is perfect for rapid prototype agents

Future Enhancements

caching + local embeddings for book similarity
store user preferences (“favorite author”, etc)
integrate Goodreads style rating metadata from alternate free sources

Conclusion

Mastra + Google Books + Telex = effortless production-grade agent building.

BookCompass only uses one API — yet the depth of capability feels like more than a demo.

This is the kind of agent you can plug into:

reading clubs
online book communities
education projects
book recommendation systems
and immediately deliver utility, not gimmicks.

DEV Community: Ayomikun Adeosun