Dishant Raghav
Production AI Eng. | RAG • Agents • Observability • LLMs
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MCP Server Starter: Production-Ready TypeScript Template
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Knowledge-Base AI Assistant and Multi-Cloud GenAI Tools
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What I learned building MCP servers for LinkedIn, Medium, Kaggle and X
Over the past year I've open-sourced a series of MCP servers that let AI assistants like Claude work directly with LinkedIn, Medium, Kaggle and X. The biggest lesson had nothing to do with the APIs. It was how the tools are described.
Three things made the clearest difference to whether an agent picked the right tool:
- Action-first names like search_posts or get_profile, instead of vague ones like posts or query.
- Descriptions that say when to use a tool, not just what it does.
- Short, precise parameter docs with examples of valid values.
With those changes, wrong tool calls dropped noticeably and agents needed far fewer retries.
If you're adding AI agents or LLM features to your product and want them to work reliably in production, I'd be glad to help.
Code: github.com/Dishant27
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An open-source MCP (Model Context Protocol) server that lets AI assistants like Claude work with X directly, using 11 tools built on the X API v1 and v2.
Agents can post and search content, look up and update profiles, follow and unfollow accounts, list followers and following, and create and manage public or private lists.
It's set up with environment-based API keys and stdio transport, plus GitHub Actions for publishing and releases. It's part of my open-source MCP series, alongside servers for LinkedIn, Medium, and Kaggle.
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