Connecting an AI Agent to Slack, GitHub, Wikis, and Tickets
A practical pattern for connecting an agent to four different systems: one shared connector interface, so search and citations don't special-case each source.
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A practical pattern for connecting an agent to four different systems: one shared connector interface, so search and citations don't special-case each source.
A practical MCP security model: scope permissions per caller, keep secrets out of the model's context entirely, and never let a tool exceed its agent's access.
Preventing unsafe AI agent actions is an architecture problem, not a prompting one: four concrete layers that actually stop damage before it happens.
Practical rules for designing MCP tools that an agent can actually use well: narrow scope, task-shaped names, bounded results, and no mode flags.
Why the next wave of AI automation is many narrow, domain-specific agents instead of one general-purpose agent, and how to start building that way.
Six lessons from building Nexus's citation system: why similar text isn't trustworthy evidence, and what actually makes a RAG answer verifiable.
Nexus is a self-hosted RAG knowledge base I built on Postgres and MCP that answers questions from Slack, code, wikis and tickets, with citations.
"AI is amazing, but existing solutions limit your control... here's how to build your own."