AI Topic: MCP

Serverless agent platform that deploys persistent, customizable AI agents via a single API and SDKs with pay-per-step pricing and mixture-of-models architecture.

AI solutions engineer for API and SDK publishers that generates production-ready integration code, embeds interactive API playgrounds, and automates API consumption and testing.

Speakeasy provides tools to generate idiomatic SDKs and Terraform providers, host and deploy MCP servers, and build agent tools and developer experiences for connecting LLMs to real-world APIs.

WorkOS MCP is an OAuth 2.1 authorization server for securing Model Context Protocol servers, providing dynamic client registration, PKCE, JWT verification, and token management for AI agents—plus enterprise SSO, directory sync, and admin tooling.

Open-source platform for stateful AI agents with persistent memory. Build, observe, and deploy agents via ADE, REST API, SDKs, and a desktop app. Connect tools via MCP; use any model; run self-hosted or on Letta Cloud.

Memory layer for AI apps and agents. Open-source SDK + managed API that adds long-term, semantic and graph memory with fast retrieval, policy controls, and analytics.

High-accuracy web research and search APIs built for AI agents, providing structured answers, citations, and MCP-ready integrations.

Local MCP server in Figma Dev Mode that pipes design context (variables, components, layout) to AI coding tools like VS Code, Cursor, Windsurf, and Claude Code.

Zapier’s Model Context Protocol server exposes Zaps and app actions as MCP tools for AI agents like Claude, Cursor, and Windsurf.

TypeScript framework for building and shipping MCP applications with file system routing, hot reloading, and flexible deployment options.