Model Context Protocol (MCP) Server Directory

Mastra is the TypeScript agent framework bridging backend workflows and Next.js frontends: built-in state, vector databases, evaluation harnesses, and native tool calling for full-stack AI teams.

While the EU AI Act goes live, US regulation arrives through states: California's SB 53 frontier AI law, training-data transparency, and the FTC's AI-washing enforcement. A practical compliance map for AI developers.

Gemini 3.1 Pro ingests documents and video that break other models: 900-page PDFs and hour-long videos in one pass. A practical guide to multimodal RAG, cost modeling, and when single-pass wins.

Open weights meet frontier: DeepSeek V4-Pro's 1.6T-parameter MoE delivers near-frontier SWE-bench Pro resolution at a fraction of Claude Opus 5's price. A rigorous benchmark and unit-economics comparison.

Give your AI agents one gateway to 500+ SaaS tools — Slack, Jira, Salesforce, Gmail — with automated OAuth flows and action-level role-based access control, built as a production FastMCP TypeScript server.

Expose every legacy REST API in your enterprise as a Model Context Protocol tool without rewriting a single endpoint, using Kong AI Gateway's MCP proxy with rate limiting, tracing, and per-tool ACLs.

Make long-running agent workflows crash-proof: LangGraph 1.x checkpoints resume interrupted runs, while Temporal handles durable scheduling and human-in-the-loop approval gates that pause and resume safely.

Ship trustworthy agents by measuring what matters: a CLEAR-based evaluation harness that runs your agent dozens of times, computes pass@k consistency, and gates deploys on reliability scores.

Architect a self-updating market intelligence pipeline where Firecrawl MCP scrapes the web, LangGraph orchestrates analyst agents, and Qdrant vector memory prevents redundant re-research across weekly sweeps.

Learn how to build a production-grade Model Context Protocol (MCP) server for Shopify Admin using FastMCP, enabling Claude and Cursor to autonomously manage inventory, process orders, and generate real-time e-commerce analytics.

Build a hyper-efficient, edge-native AI architecture where TinyML models detect local anomalies, triggering cloud-based LangGraph agents via MQTT to dynamically reconfigure IoT fleets and deploy self-healing patches.

Deploy a real-time, event-driven multi-agent system that ingests global supply chain data via Apache Flink, predicts disruptions using LLMs, and autonomously negotiates alternate sourcing with suppliers via CrewAI.