developer-tools

OpenAPI Unbundler

auto-browse

by auto-browse

Split OpenAPI specification files into focused, manageable parts while preserving references for better documentation an

Splits and extracts portions of OpenAPI specification files into smaller, more focused files while preserving referenced components for improved documentation and maintainability.

github stars

2

0 commentsdiscussion

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

Zero setup with npxPreserves component references automatically

best for

  • / API developers managing large OpenAPI specifications
  • / Teams wanting modular API documentation
  • / Microservices architecture with endpoint separation

capabilities

  • / Split OpenAPI specs into multiple smaller files
  • / Extract specific endpoints into new OpenAPI files
  • / Preserve referenced components automatically
  • / Maintain valid OpenAPI structure after splitting

what it does

Breaks down large OpenAPI specification files into smaller, focused files or extracts specific endpoints while maintaining all necessary component references.

about

OpenAPI Unbundler is a community-built MCP server published by auto-browse that provides AI assistants with tools and capabilities via the Model Context Protocol. Split OpenAPI specification files into focused, manageable parts while preserving references for better documentation an It is categorized under developer tools. This server exposes 2 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install OpenAPI Unbundler 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

Apache-2.0

OpenAPI Unbundler is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Unbundle OpenAPI MCP Server

smithery badge

This project provides a Model Context Protocol (MCP) server with tools to split OpenAPI specification files into multiple files or extract specific endpoints into a new file. It allows an MCP client (like an AI assistant) to manipulate OpenAPI specifications programmatically.

Prerequisites

  • Node.js (LTS version recommended, e.g., v18 or v20)
  • npm (comes with Node.js)

Usage

Installing via Smithery

To install Unbundle OpenAPI MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @auto-browse/unbundle_openapi_mcp --client claude

The easiest way to use this server is via npx, which ensures you are always using the latest version without needing a global installation.

npx @auto-browse/unbundle-openapi-mcp@latest

Alternatively, you can install it globally (not generally recommended):

npm install -g @auto-browse/unbundle-openapi-mcp
# Then run using: unbundle-openapi-mcp

The server will start and listen for MCP requests on standard input/output (stdio).

Client Configuration

To use this server with MCP clients like VS Code, Cline, Cursor, or Claude Desktop, add its configuration to the respective settings file. The recommended approach uses npx.

VS Code / Cline / Cursor

Add the following to your User settings.json (accessible via Ctrl+Shift+P > Preferences: Open User Settings (JSON)) or to a .vscode/mcp.json file in your workspace root.

// In settings.json:
"mcp.servers": {
  "unbundle_openapi": { // You can choose any key name
    "command": "npx",
    "args": [
      "@auto-browse/unbundle-openapi-mcp@latest"
    ]
  }
  // ... other servers can be added here
},

// Or in .vscode/mcp.json (omit the top-level "mcp.servers"):
{
  "unbundle_openapi": { // You can choose any key name
    "command": "npx",
    "args": [
      "@auto-browse/unbundle-openapi-mcp@latest"
    ]
  }
  // ... other servers can be added here
}

Claude Desktop

Add the following to your claude_desktop_config.json file.

{
	"mcpServers": {
		"unbundle_openapi": {
			// You can choose any key name
			"command": "npx",
			"args": ["@auto-browse/unbundle-openapi-mcp@latest"]
		}
		// ... other servers can be added here
	}
}

After adding the configuration, restart your client application for the changes to take effect.

MCP Tools Provided

split_openapi

Description: Executes the redocly split command to unbundle an OpenAPI definition file into multiple smaller files based on its structure.

Arguments:

  • apiPath (string, required): The absolute path to the input OpenAPI definition file (e.g., openapi.yaml).
  • outputDir (string, required): The absolute path to the directory where the split output files should be saved. This directory will be created if it doesn't exist.

Returns:

  • On success: A text message containing the standard output from the redocly split command (usually a confirmation message).
  • On failure: An error message containing the standard error or exception details from the command execution, marked with isError: true.

Example Usage (Conceptual MCP Request):

{
	"tool_name": "split_openapi",
	"arguments": {
		"apiPath": "/path/to/your/openapi.yaml",
		"outputDir": "/path/to/output/directory"
	}
}

extract_openapi_endpoints

Description: Extracts specific endpoints from a large OpenAPI definition file and creates a new, smaller OpenAPI file containing only those endpoints and their referenced components. It achieves this by splitting the original file, modifying the structure to keep only specified paths, and then bundling the result.

Arguments:

  • inputApiPath (string, required): The absolute path to the large input OpenAPI definition file.
  • endpointsToKeep (array of strings, required): A list of the exact endpoint paths (strings) to include in the final output (e.g., ["/api", "/api/projects/{id}{.format}"]). Paths not found in the original spec will be ignored.
  • outputApiPath (string, required): The absolute path where the final, smaller bundled OpenAPI file should be saved. The directory will be created if it doesn't exist.

Returns:

  • On success: A text message indicating the path of the created file and the standard output from the redocly bundle command.
  • On failure: An error message containing details about the step that failed (split, modify, bundle), marked with isError: true.

Example Usage (Conceptual MCP Request):

{
	"tool_name": "extract_openapi_endpoints",
	"arguments": {
		"inputApiPath": "/path/to/large-openapi.yaml",
		"endpointsToKeep": ["/users", "/users/{userId}/profile"],
		"outputApiPath": "/path/to/extracted-openapi.yaml"
	}
}

Note: This server uses npx @redocly/cli@latest internally to execute the underlying split and bundle commands. An internet connection might be required for npx to fetch @redocly/cli if it's not cached. Temporary files are created during the extract_openapi_endpoints process and automatically cleaned up.

Development

If you want to contribute or run the server from source :

  1. Clone: Clone this repository.
  2. Navigate: cd unbundle_openapi_mcp
  3. Install Dependencies: npm install
  4. Build: npm run build (compiles TypeScript to dist/)
  5. Run: npm start (starts the server using the compiled code in dist/)

FAQ

What is the OpenAPI Unbundler MCP server?
OpenAPI Unbundler 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 OpenAPI Unbundler?
This profile displays 33 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 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

4.633 reviews
  • Dhruvi Jain· Dec 20, 2024

    We evaluated OpenAPI Unbundler against two servers with overlapping tools; this profile had the clearer scope statement.

  • Sofia Ramirez· Dec 20, 2024

    Strong directory entry: OpenAPI Unbundler surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Amina Perez· Dec 4, 2024

    I recommend OpenAPI Unbundler for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Sofia Yang· Nov 19, 2024

    We evaluated OpenAPI Unbundler against two servers with overlapping tools; this profile had the clearer scope statement.

  • Oshnikdeep· Nov 11, 2024

    OpenAPI Unbundler has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Michael Gupta· Oct 10, 2024

    OpenAPI Unbundler is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Ganesh Mohane· Oct 2, 2024

    According to our notes, OpenAPI Unbundler benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Sakshi Patil· Sep 21, 2024

    We wired OpenAPI Unbundler into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • Sofia Gonzalez· Sep 1, 2024

    We evaluated OpenAPI Unbundler against two servers with overlapping tools; this profile had the clearer scope statement.

  • Naina Flores· Aug 24, 2024

    OpenAPI Unbundler is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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