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OpenAPI Client Generator MCP

by orhanveli
OverviewSchemaRelated ServersScoreDiscussions
JavaScript

openapi-client-generator MCP Server

A Model Context Protocol server to generate API clients by using TypeScript.

Features

Resources

  • Generates an axios based API client that can be used to interact with the API.

  • It uses OpenAPI / Swagger specs to generate the client.

Prompts

  • generate_client - Generate a API client for specified OpenAPI specs.

Related MCP server: Emcee

Development

Install dependencies:

npm install

Build the server:

npm run build

For development with auto-rebuild:

npm run watch

Installation

To use with Claude Desktop, add the server config:

On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "openapi-client-generator": {
      "command": "node",
      "args": [
        "< PATH TO >/openapi-client-generator/build/index.js"
      ]
    }
  }
}

Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:

npm run inspector

The Inspector will provide a URL to access debugging tools in your browser.

Contributing

Feel free to contribute to the project by opening issues or submitting pull requests. We welcome any improvements or new features that align with the project's goals.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Built with Cline

Available Tools

1 tool
generate_clientB

Generate TypeScript API client from OpenAPI specification

ParametersJSON Schema
NameRequiredDescriptionDefault
inputYesURL or file path to OpenAPI specification
outputYesOutput directory for generated client
httpClientYesHTTP client to use (fetch or axios)

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral traits. It does not disclose side effects (e.g., file creation, overwriting), dependencies (valid spec), permissions, or error conditions. This is a significant gap for a generation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, precise sentence with no wasted words. It is appropriately sized for a straightforward generation tool with three well-defined parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description is incomplete. It lacks details on what the generated client includes, whether existing files are overwritten, and any runtime behaviors. More context is needed for an AI agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with parameter descriptions, satisfying the baseline. The tool description does not add any additional parameter semantics beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Generate'), the output ('TypeScript API client'), and the source ('from OpenAPI specification'). It is specific and distinguishes the tool from any potential siblings (none defined).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when or when not to use the tool. While there are no sibling tools, the description lacks context such as prerequisites (valid OpenAPI spec) or best practices for selecting the HTTP client.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.5/5.0
Disambiguation5/5

With only one tool, there is no possibility of confusion. The tool has a clear and singular purpose.

Naming Consistency5/5

The single tool uses a clear verb_noun pattern ('generate_client'), which is consistent and descriptive.

Tool Count3/5

A single tool feels thin for an OpenAPI client generator. While it may suffice for a minimal use case, most users would expect additional capabilities like validation or endpoint listing.

Completeness2/5

The tool only generates a client from a specification. Obvious gaps include validating the spec, listing endpoints, or configuring output options, which limits its usefulness.

Resources

Related MCP Connectors

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  • OpenAPI to MCP Server

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