---
type: entity
subtype: tool
title: "FastAPI"
description: "Python web framework used to serve the swapped-in Python agent endpoint that streams AG-UI events."
resource: "https://fastapi.tiangolo.com"
tags: [python, api, backend, agent-deployment, web-framework]
videos: [revealing-my-complete-ai-agent-blueprint, introducing-rag-20-agentic-rag-knowledge-graphs-free-template, build-a-rag-ai-agent-with-real-time-source-validation-copilotkit-pydantic-ai, ag-ui-just-released-the-new-wave-of-ai-agent-apps, the-glow-up-every-ai-agent-needs, deploying-billions-of-ai-agents-is-easier-than-you-think, coding-subagents-the-next-evolution-of-ai-ides, complete-guide-to-langserve-make-your-ai-agent-actually-useful, im-addicted-to-windsurf-send-help]
created: 2026-07-21
updated: 2026-07-21
---

# FastAPI

FastAPI is the Python web framework Cole uses to put an agent behind an HTTP endpoint, which is his standard move for turning an agent into a production service. His blueprint states the rule directly: "you're going to want your agent to be behind an API built with something like FastAPI if you're using python" (revealing-my-complete-ai-agent-blueprint, 0:11:05). In his RAG 2.0 template it is exactly that layer: "we have FastAPI for building our agent API in Python" (introducing-rag-20, 0:06:00). FastAPI defines the request and response schema and hosts the route the front end calls, "it sets up FastAPI for the endpoint it defines your request and response schema" (the-glow-up, 0:15:09).

Because the agent lives behind a clean FastAPI endpoint, Cole can keep the framework frontend-agnostic and swap in different agent implementations without touching the client. Mounting a streaming protocol is a one-liner: "I just have to mount the AG-UI app and then boom, our Pydantic agent is immediately available on port 8000" (build-a-rag-ai-agent-real-time-source-validation, 0:13:22), and the same endpoint streams AG-UI events for the UI to render (ag-ui-just-released, 0:16:23). It composes with other tooling too, serving an MCP server "using FastAPI with the MCP python SDK" (coding-subagents, 0:15:41) and hosting LangServe routes off a LangGraph runnable (complete-guide-to-langserve, 0:05:44). Once the agent is a FastAPI app it packages cleanly into a container: "the output that we get from FastAPI looks just like what we usually see but now that it's all running within the container itself" (deploying-billions-of-ai-agents, 0:08:35).

## Realizes

- [Agent as an API Endpoint](../../concepts/agent-as-api-endpoint.md) - Wrapping an AI agent in a web API (typically FastAPI) turns it from a terminal-bound script into a deployable, scalable service any frontend, SaaS, or client can call remotely.
- [Agent Request/Response Schema](../../concepts/request-response-schema.md) - Standardizing how any agent plugs in by fixing a strict input payload (query, user_id, request_id, session_id) and a minimal output (a success boolean), so agents become interchangeable behind a common contract.

## Works with

- [Pydantic](./pydantic.md) - Python's de facto data-validation library (also the foundation of FastAPI), used as the validation layer by OpenAI, Anthropic, LangChain, and LlamaIndex, and the reason Pydantic AI puts validation at an agent framework's core.
- [Python](./python.md) - Language Auto-GPT is built in; requires Python 3.8+ to run.
- [Pydantic AI](./pydantic-ai.md) - Cole's framework for the individual agents, structured around three parts: dependencies, the agent definition, and tools.
- [LangGraph](./langgraph.md) - The orchestration framework wiring agents into a stateful graph of nodes and edges, used here to run agents in parallel and add human-in-the-loop.

## Related

- [Agent Deployment](../../concepts/agent-deployment.md) - Getting agents to production, containerizing, networking, reverse-proxying, and choosing a provider-agnostic, cost-predictable host.
- [Agent Protocols](../../concepts/agent-protocols.md) - Emerging standards (A2A, agent cards, discovery) that let agents interoperate and be called across clients.
- [Human in the Loop](../../concepts/human-in-the-loop.md) - Keeping a human as the approver and steerer of agentic work rather than fully automating, so AI augments engineers instead of replacing them.
- [Retrieval-Augmented Generation (RAG)](../../concepts/rag.md) - Grounding an LLM's answers by retrieving relevant documents from an external knowledge base and injecting them into the prompt at query time.
- [Model Selection](../../concepts/model-selection.md) - Choosing the right LLM per task by trading off quality, speed, and cost, often routing easy requests to cheap models and hard ones to expensive models.
- [Express.js](./express.md) - Minimal JavaScript web framework used to stand up the small backend API that holds the OpenAI key and proxies chat-completion requests for the browser client.

## Sources

- [Revealing my COMPLETE AI Agent Blueprint](../../sources/revealing-my-complete-ai-agent-blueprint.md) - "[0:11:05] you're going to want your agent to be behind an API built with something like FastAPI if you're using python"
- [Introducing RAG 2.0: Agentic RAG + Knowledge Graphs (FREE Template)](../../sources/introducing-rag-20-agentic-rag-knowledge-graphs-free-template.md) - "[0:06:00] we have FastAPI for building our agent API in Python."
- [Build a RAG AI Agent with REAL-TIME Source Validation (CopilotKit + Pydantic AI)](../../sources/build-a-rag-ai-agent-with-real-time-source-validation-copilotkit-pydantic-ai.md) - "[0:13:22] I just have to mount the AG-UI app and then boom, our Pydantic agent is immediately available on port 8000"
- [AG-UI Just Released: The NEW WAVE of AI Agent Apps](../../sources/ag-ui-just-released-the-new-wave-of-ai-agent-apps.md) - "[0:16:23] I have this FastAPI endpoint that's hosted just with slash AWP. I'm getting the message ID here"
- [The GLOW-UP Every AI Agent Needs](../../sources/the-glow-up-every-ai-agent-needs.md) - "[0:15:09] it sets up FastAPI for the endpoint it defines your request and response schema"
- [Deploying Billions of AI Agents is Easier than You Think](../../sources/deploying-billions-of-ai-agents-is-easier-than-you-think.md) - "[0:08:35] the output that we get from FastAPI looks just like what we usually see but now that it's all running within the container itself"
- [Coding Subagents - The Next Evolution of AI IDEs](../../sources/coding-subagents-the-next-evolution-of-ai-ides.md) - "[0:15:41] at a high level here we're using FastAPI with the MCP python SDK"
- [COMPLETE Guide to LangServe - Make Your AI Agent Actually Useful](../../sources/complete-guide-to-langserve-make-your-ai-agent-actually-useful.md) - "[0:05:44] this is where we use FastAPI and buy the routes in from my LangGraph runnable"
- [I'm Addicted to Windsurf, Send Help](../../sources/im-addicted-to-windsurf-send-help.md) - "[0:13:50] I'm telling it to use FastAPI and python for the API endpoint I'm telling it specifically what I want the API endpoint to do"
