11 posts tagged #mcp-servers.
A destructive-tool annotation plus a mid-call elicitation request gives you a deterministic human checkpoint that travels with the capability — so a confused or injected instruction can't quietly delete your data, no matter which client is driving.
When a tool call lacks a parameter, the agent's two instincts — fail or guess — are both wrong. Have the server elicit the missing field against a JSON schema and turn a half-specified request into a clean, validated dialogue.
An MCP server exposes resources, tools, and prompts — context the app pulls, actions the model takes, workflows the user invokes. Wiring them to the right controller is how the agent reads your conventions instead of guessing them.
Asking an agent to review what you say you did grades your spin, not your code. A small MCP server that reads the live diff and carries its own rubric grades reality instead.
Before you write one more anti-hallucination instruction, split each wrong answer into a retrieval failure and a generation failure. The two need opposite fixes, and no prompt rescues context that was never pulled into scope.
Wiring up Stripe or a database you've never touched by vibe-coding traps you at the first failure. Point the agent at the service's docs over MCP and force it to teach you back — close its codebase gap and your knowledge gap in the same pass.
Pairing an isolated subagent with the right tools and a thin slice of your conventions rebuilds the proven agent loop — read, pick a tool, act, report — without dragging dozens of tool-call logs back into your main thread.
The dangerous MCP server isn't the malicious one — it's the convenient all-in-one that reads untrusted data and holds privileged access to a second system. Scope it, gate the writes, and you close the confused-deputy attack.
An MCP server is a trust boundary, not a passthrough. Hold every secret server-side and expose a curated verb set, so a prompt-injected agent is bounded by the tools you chose — not your full API surface.
Give every consequential tool a declared output schema and validate the result against it at the boundary, so the UI gates on a real success boolean instead of trusting the agent's prose — and a malformed result fails loud instead of rendering a lie.
Ship your team's recurring workflows as server-side MCP prompts that pre-load their own data as embedded resources. A teammate types a slash command, fills one argument, and gets an expert prompt with the context already attached.