# FastAPI MCP Server

> Use this tool when you need to introspect and analyze FastAPI applications, as it provides route discovery, model schema extraction, and source code viewing capabilities to solve problems related to API structure exploration, documentation generation, and dependency injection debugging. It takes in FastAPI application data as input and outputs detailed insights and documentation through a natural language interface. Use it to streamline API development, testing, and maintenance workflows.

Canonical page: https://skillsregistry.net/skills/nabeelshar-fastapi-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/nabeelshar-fastapi-mcp-server

## Description

A Model Context Protocol server that provides tools for introspecting and analyzing FastAPI applications, including route discovery, model schema extraction, and source code viewing. It enables users to explore API structures, generate documentation, and debug dependency injection hierarchies through natural language.

## Trust

- **Trust score (0–1):** 0.99
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** file-system
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/h4lj00nuas)
- **Repository:** <https://github.com/Nabeelshar/fastapi-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "nabeelshar-fastapi-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/nabeelshar-fastapi-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/nabeelshar-fastapi-mcp-server/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt