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MCP server · AI

Petstormcp Cliente

Model Context Protocol (MCP) Server for the *petstormcp-cliente* API.

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Scored 4 months ago · breakdown

About Petstormcp Cliente

Petstormcp Cliente is an MCP server in the AI category: model Context Protocol (MCP) Server for the *petstormcp-cliente* API. It has been installed 0 times through Conduid.

Install

Claude Code
claude mcp add petstormcp-cliente -- npx -y petstormcp-cliente
npx
npx -y petstormcp-cliente

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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README

petstormcp-cliente

Model Context Protocol (MCP) Server for the petstormcp-cliente API.

Built by Speakeasy

[!IMPORTANT] This MCP Server is not yet ready for production use. To complete setup please follow the steps outlined in your workspace. Delete this notice before publishing to a package manager.

Summary

Petstore - OpenAPI 3.1: This is a sample Pet Store Server based on the OpenAPI 3.1 specification.

Some useful links:

For more information about the API: Find out more about Swagger

Table of Contents

Installation

[!TIP] To finish publishing your MCP Server to npm and others you must run your first generation action.

Install the MCP server as a Desktop Extension using the pre-built mcp-server.mcpb file:

Simply drag and drop the mcp-server.mcpb file onto Claude Desktop to install the extension.

The MCP bundle package includes the MCP server and all necessary configuration. Once installed, the server will be available without additional setup.

[!NOTE] MCP bundles provide a streamlined way to package and distribute MCP servers. Learn more about Desktop Extensions.

Install MCP Server

Or manually:

  1. Open Cursor Settings
  2. Select Tools and Integrations
  3. Select New MCP Server
  4. If the configuration file is empty paste the following JSON into the MCP Server Configuration:
{
  "command": "npx",
  "args": [
    "petstormcp-cliente",
    "start",
    "--environment",
    "prod",
    "--api-key",
    ""
  ]
}
claude mcp add Petstore -- npx -y petstormcp-cliente start --environment prod --api-key 
gemini mcp add Petstore -- npx -y petstormcp-cliente start --environment prod --api-key 

Refer to Official Windsurf documentation for latest information

  1. Open Windsurf Settings
  2. Select Cascade on left side menu
  3. Click on Manage MCPs. (To Manage MCPs you should be signed in with a Windsurf Account)
  4. Click on View raw config to open up the mcp configuration file.
  5. If the configuration file is empty paste the full json
{
  "command": "npx",
  "args": [
    "petstormcp-cliente",
    "start",
    "--environment",
    "prod",
    "--api-key",
    ""
  ]
}

Install in VS Code

Or manually:

Refer to Official VS Code documentation for latest information

  1. Open Command Palette
  2. Search and open MCP: Open User Configuration. This should open mcp.json file
  3. If the configuration file is empty paste the full json
{
  "command": "npx",
  "args": [
    "petstormcp-cliente",
    "start",
    "--environment",
    "prod",
    "--api-key",
    ""
  ]
}
npx petstormcp-cliente start --environment prod --api-key 

For a full list of server arguments, run:

npx petstormcp-cliente --help

Progressive Discovery

MCP servers with many tools can bloat LLM context windows, leading to increased token usage and tool confusion. Dynamic mode solves this by exposing only a small set of meta-tools that let agents progressively discover and invoke tools on demand.

To enable dynamic mode, pass the --mode dynamic flag when starting your server:

{
  "mcpServers": {
    "Petstore": {
      "command": "npx",
      "args": ["petstormcp-cliente", "start", "--mode", "dynamic"],
      // ... other server arguments
    }
  }
}

In dynamic mode, the server registers only the following meta-tools instead of every individual tool:

  • list_tools: Lists all available tools with their names and descriptions.
  • describe_tool: Returns the input schema for one or more tools by name.
  • execute_tool: Executes a tool by name with the provided input parameters.

This approach significantly reduces the number of tokens sent to the LLM on each request, which is especially useful for servers with a large number of tools.

Development

Run locally without a published npm package:

  1. Clone this repository
  2. Run npm install
  3. Run npm run build
  4. Run node ./bin/mcp-server.js start --environment prod --api-key To use this local version with Cursor, Claude or other MCP Clients, you'll need to add the following config:
{
  "command": "node",
  "args": [
    "./bin/mcp-server.js",
    "start",
    "--environment",
    "prod",
    "--api-key",
    ""
  ]
}

Or to debug the MCP server locally, use the official MCP Inspector:

npx @modelcontextprotocol/inspector node ./bin/mcp-server.js start --environment prod --api-key 

Publishing to Anthropic MCP Registry

This server generates a server.json that conforms to the official MCP Registry schema. You can publish automatically via your Speakeasy workflow or manually using the mcp-publisher CLI.

Automated Publishing (Recommended)

Add mcpRegistry to the publish block in your workflow.yaml:

targets:
  my-mcp:
    target: mcp-typescript
    source: my-source
    publish:
      npm:
        token: $NPM_TOKEN
      mcpRegistry:
        auth: github-oidc  # recommended, no token needed

The github-oidc method uses GitHub Actions OIDC — no secrets required. For other auth methods:

  • github — requires a MCP_REGISTRY_TOKEN secret (GitHub PAT with read:org + read:user scopes)
  • dns — requires a MCP_REGISTRY_TOKEN secret (Ed25519 private key for custom domain namespaces)

When the Speakeasy workflow runs, it will automatically publish to npm first, then to the MCP Registry.

Manual Publishing

If you prefer to publish manually, follow the official publishing guide:

  1. Publish to npm: npm publish --access public
  2. Install the publisher CLI:
    curl -sL "https://github.com/modelcontextprotocol/registry/releases/latest/download/mcp-publisher_$(uname -s | tr '[:upper:]' '[:lower:]')_$(uname -m | sed 's/x86_64/amd64/;s/aarch64/arm64/').tar.gz" | tar xz mcp-publisher && sudo mv mcp-publisher /usr/local/bin/
    
  3. Authenticate (GitHub OAuth for io.github.* namespaces):
    mcp-publisher login github
    
  4. Publish: mcp-publisher publish
  5. Verify:
    curl "https://registry.modelcontextprotocol.io/v0/servers?search=<your-mcp-name>"
    

Contributions

While we value contributions to this MCP Server, the code is generated programmatically. Any manual changes added to internal files will be overwritten on the next generation. We look forward to hearing your feedback. Feel free to open a PR or an issue with a proof of concept and we'll do our best to include it in a future release.

MCP Server Created by Speakeasy

README mirrored from the source repository 4 months ago. The original is authoritative.

Questions

About Petstormcp Cliente

How do I install Petstormcp Cliente?

Run claude mcp add petstormcp-cliente -- npx -y petstormcp-cliente, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Petstormcp Cliente safe to use with an AI agent?

Its trust score is 37 out of 100 (low). Conduid hasn't run static security checks on this repository yet, so review the source yourself before granting it credentials. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Petstormcp Cliente still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.