Specbridge▌
by tbosak
Specbridge auto-converts OpenAPI specifications into tools with endpoint generation, parameter validation, authenticatio
Automatically converts OpenAPI specifications into executable tools by scanning folders for spec files and generating corresponding endpoints with parameter validation, authentication support, and HTTP request handling.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / API developers testing endpoints
- / Building API integration workflows
- / Exploring public APIs from APIs.guru
- / Rapid API prototyping
capabilities
- / Convert OpenAPI specs to executable tools
- / List and manage OpenAPI specification files
- / Download specs from URLs
- / Browse APIs.guru directory
- / Handle authentication with .env files
- / Validate parameters automatically
what it does
Converts OpenAPI specification files into executable MCP tools by scanning folders and auto-generating endpoints with parameter validation and authentication support.
about
Specbridge is a community-built MCP server published by tbosak that provides AI assistants with tools and capabilities via the Model Context Protocol. Specbridge auto-converts OpenAPI specifications into tools with endpoint generation, parameter validation, authenticatio It is categorized under developer tools. This server exposes 11 tools that AI clients can invoke during conversations and coding sessions.
how to install
You can install Specbridge in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
MIT
Specbridge is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
SpecBridge
[](https://mseep.ai/app/ab3b0729-c54e-4359-aed0-606b90995b59)
[](https://smithery.ai/server/@TBosak/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](https://www.npmjs.com/package/fastmcp) for TypeScript.
## ✨ Features
- 🎯 **Zero Configuration**: Filesystem is the interface - just drop OpenAPI specs in a folder
- 🔐 **Auto Authentication**: Simple `.env` file with `{API_NAME}_API_KEY` pattern
- 🏷️ **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)
```bash
npm install -g specbridge
```
### 2️⃣ Create a specs folder
```bash
mkdir ~/mcp-apis
```
### 3️⃣ Add OpenAPI specs
Drop any `.json`, `.yaml`, or `.yml` OpenAPI specification files into your specs folder:
```bash
# 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:
```bash
# ~/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:
```json
{
"mcpServers": {
"specbridge": {
"command": "specbridge",
"args": ["--specs", "/path/to/your/specs/folder"]
}
}
}
```
Otherwise:
```json
{
"mcpServers": {
"specbridge": {
"command": "npx",
"args": ["-y", "specbridge", "--specs", "/absolute/path/to/your/specs"]
}
}
}
```
## 💻 CLI Usage
### 🚀 Start the server
```bash
# 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
```bash
# 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_KEY`
- `github-api.yaml` → `GITHUB_TOKEN`
- `my_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 from `GET /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:
```yaml
# ~/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_getUser`
- `example_createUser`
## 🔧 Troubleshooting
### ❌ No tools appearing?
1. Check that your OpenAPI specs are valid:
```bash
specbridge list --specs /path/to/specs
```
2. Ensure files have correct extensions (`.json`, `.yaml`, `.yml`)
3. Check the server logs for parsing errors
> **⚠️ Note:** Specbridge works best when you use absolute paths (with no spaces) for the `--specs` argument and other file paths. Relative paths or paths containing spaces may cause issues on some platforms or with some MCP clients.
### 🔐 Authentication not working?
1. Verify your `.env` file is in the specs directory
2. Check the naming pattern matches your spec filename
3. Use the list command to verify auth configuration:
```bash
specbridge list
```
### 🔄 Tools not updating after spec changes?
1. Restart the MCP server to reload the specs
2. Check file permissions
3. Restart the MCP client if needed
## 🛠️ Development
```bash
# 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.
FAQ
- What is the Specbridge MCP server?
- Specbridge is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for Specbridge?
- This profile displays 42 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.7 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Extended AI Capabilities
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Context Enhancement
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Workflow Automation
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Implementation Guide▌
Prerequisites
- ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
- ›Basic understanding of MCP architecture and capabilities
- ›Access credentials for integrated services (if required)
- ›Willingness to experiment and iterate on configuration
Time Estimate
15-60 minutes depending on server complexity
Installation Steps
- 1.Install MCP server: npm install -g [package-name] or via GitHub
- 2.Add server configuration to ~/.claude/mcp.json
- 3.Provide required credentials and configuration
- 4.Restart Claude Desktop to load new server
- 5.Test basic functionality with simple prompts
- 6.Explore capabilities and experiment with use cases
- 7.Document successful patterns for reuse
Troubleshooting
- ⚠MCP server not loading: Check config syntax, verify installation
- ⚠Connection errors: Check network, firewall, credentials
- ⚠Feature not working: Read server docs, check required parameters
- ⚠Performance issues: Monitor resource usage, check for network latency
- ⚠Conflicts with other servers: Check port assignments, namespace collisions
Best Practices▌
✓ Do
- +Read server documentation thoroughly before setup
- +Start with simple use cases to validate functionality
- +Test in non-production environment first
- +Monitor resource usage and performance
- +Keep servers updated for bug fixes and new features
- +Document configuration for team members
- +Use environment variables for sensitive configuration
✗ Don't
- −Don't grant overly permissive access to MCP servers
- −Don't skip reading security considerations in docs
- −Don't expose sensitive data without proper controls
- −Don't run untrusted MCP servers without code review
- −Don't ignore error messages—investigate root cause
💡 Pro Tips
- ★Combine multiple MCP servers for powerful workflows
- ★Create custom MCP servers for your specific needs
- ★Share successful configurations with team
- ★Use MCP inspector for debugging
- ★Join MCP community for tips and troubleshooting
Technical Details▌
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
- Model Context Protocol (MCP)
- JSON-RPC 2.0
- stdio or HTTP transport
Compatibility
- Claude Desktop
- Cursor IDE
- Custom MCP clients
When to Use This▌
✓ Use When
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid When
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.
Integration▌
- →Tool composition: Chain multiple MCP tools in workflows
- →Context augmentation: Provide AI with relevant external data
- →Action delegation: Let AI execute tasks on external systems
- →Bidirectional sync: Keep AI context and external systems in sync
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.7★★★★★42 reviews- ★★★★★Fatima Martin· Dec 16, 2024
We wired Specbridge into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Neel Agarwal· Dec 16, 2024
Specbridge is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Chaitanya Patil· Dec 12, 2024
Specbridge is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Layla Torres· Nov 23, 2024
Specbridge has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Rahul Santra· Nov 11, 2024
Specbridge has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
- ★★★★★Neel Iyer· Nov 7, 2024
We evaluated Specbridge against two servers with overlapping tools; this profile had the clearer scope statement.
- ★★★★★Neel Gupta· Nov 7, 2024
Specbridge is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Piyush G· Nov 3, 2024
Specbridge is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Advait Khan· Oct 26, 2024
Specbridge is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Naina Nasser· Oct 26, 2024
We wired Specbridge into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
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