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Synapse MCP + GPT-6 on Steroids

Launching today

Turn Astra into a senior engineer who knows your codebase.

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Turn Astra into a senior engineer who knows your codebase.

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GPT-6 Astra is the most capable coding model ever built. That only matters if it knows how your code is put together. Without Synapse, it's a talented junior — grep, guess, pray the build passes. With Synapse? Astra is a confident senior engineer. Synapse MCP is the structural brain: a local AST graph, 50+ languages, instant caller trees, edits simulated before they land. 60% fewer tokens. 2.2x faster. No babysitting. Astra reasons; Synapse knows how all of your code is built. Fast. Local. Free.

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Launch tags:Productivity•Developer Tools•Artificial Intelligence

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Viktor.comAn AI coworker that actually does the work

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GPT-6 Astra Challenge

What real task does your product handle with GPT-6 Astra?

Maker

We tasked GPT-6 Astra with auditing Synapse MCP's production codebase using Synapse's own AST graph. Instead of generating boilerplate, Astra executed a deep architectural audit that exposed six structural defects in our toolchain—including JS/TS scope collapse, false runtime coverage confidence, and silent schema truncation. Places where our engine was guessing instead of knowing. Astra didn't just patch code. Across 15+ Gherkin specs and 6 core files, Astra authored BDD-first acceptance scenarios before implementation, provided source-anchored evidence for every fix, and preserved full backward compatibility. As a result, Astra used Synapse's structural brain to harden Synapse itself. An AI agent mapped, audited, and refined the exact context engine that powers it. A tool built to make AI agents more accurate got measurably better by asking Astra how to improve it for itself and other agents. That self-improving engineering loop is live in production for this release.

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23h ago

Maker

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GPT-6 Astra is the best coding model ever built. Synapse MCP makes it even better — in every way. We don't mean 5% better. We mean we watched Astra spend 12 tool calls trying to understand a 500k-LOC codebase — grepping, reading imports, chasing callers it had already seen. The reasoning was genius. The exploration was from 1995. Synapse MCP fixes the discovery Astra can't do very well. It's a local AST knowledge graph that sits between Astra and your codebase: - Astra wants a caller tree? One query, under 500ms, transitive depth 3. - Astra wants to refactor? Simulate the edit in memory, mathematically prove no caller breaks, then write. - Astra wants context? Compressed structural signatures — 60% less token burn. Same Astra. Same task. 60% fewer tokens, 2.2× faster, zero broken callers. We published the full benchmark — you can verify it. This is our entry to the GPT-6 Astra Challenge because we believe the next leap in AI coding isn't a smarter model. It's giving the models we already have full structural understanding of our code. We built this version of Synapse by asking Astra what was missing. We delivered. 100% local. Free and Pro versions. In the comments all day — ask us anything.

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2d ago