This content originally appeared on DEV Community and was authored by ContextSpace
When the concept of MCP (Model Context Protocol) first emerged, I felt a jolt of genuine excitement. This was it. This was the key that would let us unlock the true potential of LLMs, allowing them to interact with tools and the real world. I jumped in headfirst, my mind buzzing with ideas for truly intelligent agents.
Then reality hit.
My initial excitement quickly turned into a grinding frustration. The cycle became depressingly familiar:
- Spend hours figuring out the right API calls for a tool.
- Manually edit a sprawling, unforgiving config.yaml file.
- Worry constantly about accidentally committing secret keys.
- Finally get it to work, only to have the agent forget a crucial piece of information from the previous turn.
I spent more time debugging YAML syntax and juggling API keys than I did thinking about the actual AI logic. The promise of intelligent agents was buried under a mountain of tedious, brittle, and insecure configuration.
One evening, deep in this frustration, I asked myself: What’s the real problem here? It’s not the LLM. It’s not even the idea of MCP.
Turns out, the problem is context.
We’re building brains with amnesia and giving them tools with instructions written on sticky notes.
I started talking to my dev friends and realized I wasn’t alone. We were all sharing the same war stories, the same disillusionment. During one of these chats, an idea sparked. What if we stopped complaining? What if we, a group of developers who felt this pain deeply, just built the thing we all wished existed?
That’s exactly what we did.
A few of us, driven by this shared vision, went into a self-imposed lockdown. For one intense month, we did nothing but code. We architected, debated, and built. We poured everything we had into it. 30,000 lines of code later, Context Space was born.
It’s the infrastructure we dreamed of: a system that replaces config hell with secure OAuth flows and gives agents a persistent, queryable memory.
A few weeks ago, as we were preparing to surface, a tweet from Andrej Karpathy appeared on our feeds: “context engineering > prompt engineering.” It was a moment of incredible validation. It gave a name to the very thing we had been obsessing over.
But we know our initial version, this first fruit of our labor, is far from the complete vision of true Context Engineering. The road is long. That is precisely why we are open-sourcing Context Space today.
We are calling on everyone who has felt this frustration. Everyone who believes in a future of truly capable AI agents. Come join us. Let’s build the foundational infrastructure for the next era of AI.
Star Context Space on GitHub and join the movement: https://github.com/context-space/context-space
This content originally appeared on DEV Community and was authored by ContextSpace