developer-tools

Specbridge

tbosak

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.

github stars

7

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Zero configuration setupFilesystem-based interfaceAuto authentication via .env

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 [![Verified on MseeP](https://mseep.ai/badge.svg)](https://mseep.ai/app/ab3b0729-c54e-4359-aed0-606b90995b59) [![smithery badge](https://smithery.ai/badge/@TBosak/specbridge)](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.

Specbridge MCP server

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. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 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

4.742 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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