SpecBridge
Automatically generates MCP tools from OpenAPI specifications by scanning a folder for spec files. No configuration is needed and it supports authentication via environment variables.
SpecBridge
An MCP server that turns OpenAPI specifications into MCP tools. Scan a folder for OpenAPI spec files and automatically generate corresponding tools. No configuration files, no separate servers - just drop specs in a folder and get tools.Built with FastMCP for TypeScript.
✨ Features
- 🎯 Zero Configuration: Filesystem is the interface - just drop OpenAPI specs in a folder
- 🔐 Auto Authentication: Simple
.envfile with{API_NAME}_API_KEYpattern - 🏷️ Namespace Isolation: Multiple APIs coexist cleanly (e.g.,
petstore_getPet,github_getUser) - 📝 Full OpenAPI Support: Handles parameters, request bodies, authentication, and responses
- 🚀 Multiple Transports: Support for stdio and HTTP streaming
- 🔍 Built-in Debugging: List command to see loaded specs and tools
🚀 Quick Start
1️⃣ Install (optional)
npm install -g specbridge
2️⃣ Create a specs folder
mkdir ~/mcp-apis
3️⃣ Add OpenAPI specs
Drop any .json, .yaml, or .yml OpenAPI specification files into your specs folder:
# Example: Download the Petstore spec
curl -o ~/mcp-apis/petstore.json https://petstore3.swagger.io/api/v3/openapi.json
4️⃣ Configure authentication (optional)
Create a .env file in your specs folder:
# ~/mcp-apis/.env
PETSTORE_API_KEY=your_api_key_here
GITHUB_TOKEN=ghp_your_github_token
OPENAI_API_KEY=sk-your_openai_key
5️⃣ Add to MCP client configuration
For Claude Desktop or Cursor, add to your MCP configuration:
If installed on your machine:
{
"mcpServers": {
"specbridge": {
"command": "specbridge",
"args": ["--specs", "/path/to/your/specs/folder"]
}
}
}
Otherwise:
{
"mcpServers": {
"specbridge": {
"command": "npx",
"args": ["-y", "specbridge", "--specs", "/absolute/path/to/your/specs"]
}
}
}
💻 CLI Usage
🚀 Start the server
# Default: stdio transport, current directory
specbridge
# Custom specs folder
specbridge --specs ~/my-api-specs
# HTTP transport mode
specbridge --transport httpStream --port 8080
📋 List loaded specs and tools
# List all loaded specifications and their tools
specbridge list
# List specs from custom folder
specbridge list --specs ~/my-api-specs
🔑 Authentication Patterns
The server automatically detects authentication from environment variables using these patterns:
| Pattern | Auth Type | Usage |
|---|---|---|
{API_NAME}_API_KEY | 🗝️ API Key | X-API-Key header |
{API_NAME}_TOKEN | 🎫 Bearer Token | Authorization: Bearer {token} |
{API_NAME}_BEARER_TOKEN | 🎫 Bearer Token | Authorization: Bearer {token} |
{API_NAME}_USERNAME + {API_NAME}_PASSWORD | 👤 Basic Auth | Authorization: Basic {base64} |
The {API_NAME} is derived from the filename of your OpenAPI spec:
petstore.json→PETSTORE_API_KEYgithub-api.yaml→GITHUB_TOKENmy_custom_api.yml→MYCUSTOMAPI_API_KEY
🏷️ Tool Naming
Tools are automatically named using this pattern:
- With operationId:
{api_name}_{operationId} - Without operationId:
{api_name}_{method}_{path_segments}
Examples:
petstore_getPetById(from operationId)github_get_user_repos(generated fromGET /user/repos)
📁 File Structure
your-project/
├── api-specs/ # Your OpenAPI specs folder
│ ├── .env # Authentication credentials
│ ├── petstore.json # OpenAPI spec files
│ ├── github.yaml #
│ └── custom-api.yml #
└── mcp-config.json # MCP client configuration
📄 Example OpenAPI Spec
Here's a minimal example that creates two tools:
# ~/mcp-apis/example.yaml
openapi: 3.0.0
info:
title: Example API
version: 1.0.0
servers:
- url: https://api.example.com
paths:
/users/{id}:
get:
operationId: getUser
summary: Get user by ID
parameters:
- name: id
in: path
required: true
schema:
type: string
responses:
'200':
description: User found
/users:
post:
operationId: createUser
summary: Create a new user
requestBody:
required: true
content:
application/json:
schema:
type: object
properties:
name:
type: string
email:
type: string
responses:
'201':
description: User created
This creates tools named:
example_getUserexample_createUser
🔧 Troubleshooting
❌ No tools appearing?
-
Check that your OpenAPI specs are valid:
specbridge list --specs /path/to/specs -
Ensure files have correct extensions (
.json,.yaml,.yml) -
Check the server logs for parsing errors
⚠️ Note: Specbridge works best when you use absolute paths (with no spaces) for the
--specsargument and other file paths. Relative paths or paths containing spaces may cause issues on some platforms or with some MCP clients.
🔐 Authentication not working?
- Verify your
.envfile is in the specs directory - Check the naming pattern matches your spec filename
- Use the list command to verify auth configuration:
specbridge list
🔄 Tools not updating after spec changes?
- Restart the MCP server to reload the specs
- Check file permissions
- Restart the MCP client if needed
🛠️ Development
# Clone and install
git clone https://github.com/TBosak/specbridge.git
cd specbridge
npm install
# Build
npm run build
# Test locally
npm run dev -- --specs ./examples
🤝 Contributing
Contributions are welcome! Please feel free to submit issues and pull requests.
Máy chủ liên quan
Scout Monitoring MCP
nhà tài trợPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
nhà tài trợAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
MCP SFTP Orchestrator
Orchestrates remote server tasks via SSH and SFTP with a persistent queue. Ideal for DevOps and AI agents.
Modellix Docs
Search the Modellix knowledge base to quickly find relevant technical information, code examples, and API references. Retrieve implementation details and official guides to solve development queries efficiently. Access direct links to documentation for deeper context on specific features and tools.
Email MCP Server by Sidemail
Let AI agents write & manage your SaaS emails
SwissArmyHammer
Manage AI prompts as local markdown files.
MCP Bridge API
A lightweight, LLM-agnostic RESTful proxy that unifies multiple MCP servers under a single API.
Python Interpreter MCP
An MCP server that provides Python code execution capabilities through a REST API interface.
AppDeploy
AppDeploy lets you deploy a real, full-stack web app directly from an AI chat and turn your AI conversations into live apps, without leaving the chat or touching infrastructure.
MCP Tools
A collection of MCP servers for growth and analytics, including a server for Google Analytics.
Azure DevOps
Interact with Azure DevOps for managing projects, pipelines, and repositories.
Shaka Packager MCP Server
Video transcoding, packaging, and analysis using the Shaka Packager tool, integrated with Claude AI.