swaggbot
Transforms Swagger/OpenAPI documented APIs into conversational interfaces, enabling natural language interaction with APIs through an MCP server for use with AI assistants.
README
Swaggbot
Transform Swagger/OpenAPI docs into conversational interfaces. Self-hosted, local-first, AI-powered API exploration.
Quick Start
# Docker (recommended)
git clone https://github.com/techbloom-ai/swaggbot.git
cd swaggbot && cp .env.example .env
# Generate SESSION_SECRET and add LLM API keys
docker-compose up -d
What is Swaggbot?
Swaggbot converts any Swagger/OpenAPI documented API into a conversational interface. Built for developers who want to:
- Explore APIs naturally β Chat instead of reading raw JSON
- Automate workflows β Multi-step operations with data extraction
- Stay in control β Self-hosted, data stays local
- Integrate anywhere β Web UI, MCP server, or direct API
Features
- π€ Natural Language API Interaction β "List all users" β
GET /users - π Workflow Automation β Chain multiple API calls with dependency resolution
- π MCP Server β Use with Claude Desktop, Cursor, Windsurf
- π Self-Hosted β Your data, your infrastructure
- π Session Management β Encrypted auth tokens, per-session isolation
- π Multi-Provider LLM β Moonshot, OpenAI, Anthropic, Ollama
- π Array Filtering β
[name=John].idsyntax for data extraction - π‘οΈ Security β CSP headers, rate limiting, encrypted storage
Architecture
βββββββββββ βββββββββββ βββββββββββ
β Web UI β β MCP β β API β
β Next.js β β Server β β Clients β
ββββββ¬βββββ ββββββ¬βββββ ββββββ¬βββββ
βββββββββββββββΌββββββββββββββ
βΌ
βββββββββββββββββββ
β Chat Service β Intent Classification
β + LLM Provider β β Curl Generation β Execution
βββββββββββββββββββ
β
βββββββββββββββΌββββββββββββββ
βΌ βΌ βΌ
ββββββββββ βββββββββββ ββββββββββββ
βSQLite β βWorkflow β β Target β
β(Local) β β Engine β β API β
ββββββββββ βββββββββββ ββββββββββββ
Installation
Prerequisites
- Node.js 18+ or Docker
- LLM API key (Moonshot, OpenAI, Anthropic, or Ollama)
Docker (Recommended)
# 1. Clone and configure
git clone https://github.com/techbloom-ai/swaggbot.git
cd swaggbot
cp .env.example .env
# 2. Set SESSION_SECRET (required for auth)
# Linux/macOS:
export SESSION_SECRET=$(openssl rand -base64 32)
# Or add to .env: SESSION_SECRET=your_random_secret_here
# 3. Add your LLM API key to .env
# MOONSHOT_API_KEY=your_key_here
# 4. Start
docker-compose up -d
Database migrations run automatically on first startup.
Local Development
git clone https://github.com/techbloom-ai/swaggbot.git
cd swaggbot
pnpm install
cp .env.example .env.local
# Edit .env.local with SESSION_SECRET and LLM API keys
pnpm db:migrate
pnpm dev
Configuration
| Variable | Required | Default | Description |
|---|---|---|---|
SESSION_SECRET |
Yes | β | Random secret for session encryption (min 32 chars) |
MOONSHOT_API_KEY |
Yes* | β | Moonshot AI API key |
OPENAI_API_KEY |
Yes* | β | OpenAI API key |
ANTHROPIC_API_KEY |
Yes* | β | Anthropic API key |
OLLAMA_BASE_URL |
Yes* | β | Ollama server URL |
LLM_PROVIDER |
No | moonshot |
moonshot | openai | anthropic | ollama |
DATABASE_URL |
No | file:./data/swaggbot.db |
SQLite database path |
NEXT_PUBLIC_APP_URL |
No | http://localhost:3003 |
App base URL |
*At least one LLM provider required
Generate SESSION_SECRET
# Linux/macOS
openssl rand -base64 32
# Or any random string (min 32 characters)
API Reference
REST API
All endpoints require authentication via session cookie.
| Endpoint | Method | Description |
|---|---|---|
/api/auth/login |
POST | Authenticate and create session |
/api/session |
POST | Create API session from Swagger URL |
/api/session |
GET | List all sessions (paginated) |
/api/chat |
POST | Send message to API |
/api/workflow |
POST | Create multi-step workflow |
/api/workflow/:id/execute |
POST | Execute workflow |
MCP Server
{
"mcpServers": {
"swaggbot": {
"command": "docker",
"args": ["compose", "run", "--rm", "swaggbot-mcp"],
"env": {
"SESSION_SECRET": "your_secret",
"MOONSHOT_API_KEY": "your_key"
}
}
}
}
Usage Examples
Web UI
- Navigate to login page
- Create a session with your Swagger URL
- Start chatting:
"Create a user named John" "List all pets with status available" "Execute the login workflow"
API
# Authenticate
curl -X POST http://localhost:3003/api/auth/login \
-H "Content-Type: application/json" \
-d '{"password": "your_password"}' \
-c cookies.txt
# Chat with API
curl -X POST http://localhost:3003/api/chat \
-H "Content-Type: application/json" \
-b cookies.txt \
-d '{"sessionId": "...", "message": "List all users"}'
Technology Stack
| Component | Technology |
|---|---|
| Framework | Next.js 16 (App Router) |
| Language | TypeScript 5 |
| Database | SQLite (libSQL/Turso) |
| ORM | Drizzle ORM |
| UI | shadcn/ui + TailwindCSS 4 |
| State | Zustand |
| LLM SDK | Vercel AI SDK patterns |
| MCP | Model Context Protocol SDK |
| Testing | Vitest |
| Container | Docker + Docker Compose |
Project Structure
swaggbot/
βββ app/ # Next.js App Router
β βββ api/ # API routes
β βββ sessions/ # Session UI
β βββ settings/ # Settings page
βββ components/ # shadcn/ui components
βββ lib/
β βββ db/ # Database schema & migrations
β βββ llm/ # LLM provider implementations
β βββ services/ # Business logic
β βββ auth/ # Session & encryption
β βββ prompts/ # LLM prompt management
βββ scripts/ # MCP server & entrypoint
βββ data/ # SQLite storage (Docker volume)
Security
- Local-first: All data stored locally in SQLite
- Encrypted tokens: Auth tokens encrypted with AES-256-GCM
- Session-based auth: Password-protected access
- CSP headers: Content Security Policy protection
- Rate limiting: Per-endpoint limits configurable
- No telemetry: Zero analytics or tracking
License
MIT Β© TechBloom
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.