Agent Ecosystem: MCP, Gateways and Platforms
The pieces that connect agents to the world: building your own MCP server, the self-hosted visual platforms Langflow, Flowise and Dify, integrations with Composio, web data with Firecrawl, browsing with browser-use and the OpenRouter gateway.
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Building Your Own MCP Server
Your own MCP server exposes your data and functions to any AI assistant through the Model Context Protocol. With the official Python SDK and its FastMCP class you write a server in about twenty lines: you define tools, resources and prompts as type-annotated functions, and you connect it to Claude, Cline or Goose over stdio or HTTP.
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Langflow: a visual agent builder
Langflow is an open-source tool for building AI agents and workflows by dragging blocks onto a visual canvas, with barely any code. You can self-host it with Docker, wire up models, tools and vector databases, and publish every flow as an API or as an MCP server. This guide explains how to deploy it and build your first agent.
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Flowise: self-hosted low-code agents
Flowise is an open-source tool that lets you build AI agents by dragging nodes onto a visual canvas, with barely any code. It is built on LangChain.js and you can self-host the whole thing with a single Docker container. This guide covers how to deploy it, the difference between chatflows and AgentFlow v2, and how it compares to Langflow and Dify.
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Dify: a self-hosted LLMOps platform
Dify is an open-source platform for building AI applications and agents, with a visual workflow canvas, prompt management, a RAG knowledge base and LLMOps layers. You can self-host the whole thing with Docker Compose on top of Postgres, Redis and a vector database. This guide explains how to deploy it and when it beats Flowise and Langflow.
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Composio: Tools and Integrations for Agents
Composio connects your AI agent to more than a thousand applications (GitHub, Slack, Gmail, Notion) through pre-authenticated tools and managed OAuth authentication. Instead of writing each integration by hand, you request the tools by name and the agent acts on behalf of each user. This guide explains what it is, how it handles authentication and how to plug it into your agent framework.
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Firecrawl: Web Data for Agents
Firecrawl is an open-source API that turns any web page into clean Markdown, ready for a language model. With scrape and crawl endpoints plus schema-guided JSON extraction, it gives your AI agent reliable web data. This guide covers its formats, how to self-host it with Docker and when it beats a scraper of your own.
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browser-use: agents that browse the web
browser-use is an open-source Python library that lets an AI agent drive a web browser the way you do: it opens pages, reads the DOM, clicks and fills in forms. It was born on Playwright and in 2025 switched to speaking Chrome's CDP protocol directly for speed. This guide explains how it works and when to use it.
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OpenRouter: A Gateway for AI Models
OpenRouter is a hosted gateway that gathers more than 400 AI models from over 70 providers behind a single OpenAI-compatible API. You change the base URL, use one key and one balance, and gain automatic routing, failover and pass-through token pricing. Unlike a self-hosted proxy such as LiteLLM, you run no infrastructure at all.