Developer builds MCP server to give AI coding agents access to real user feedback

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A developer building a feedback board product noticed that AI coding agents like Claude Code could read an entire codebase but had no visibility into what users were actually requesting. To close that gap, they exposed their feedback board's data via the Model Context Protocol (MCP), allowing the agent to discover and chain tools autonomously rather than relying on manually scripted REST API calls. The MCP server was deliberately kept minimal, with just five read tools and two write tools, to reduce context bloat and limit the risk of unintended actions. Write access is restricted to filing new requests and updating post statuses, with no destructive operations possible through the integration. The author argues that MCP fundamentally differs from REST in that it shifts integration work from the developer to the agent itself, making it more suitable for conversational AI workflows.

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