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Picsha AI Server

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MCP server for Picsha AI platform enabling LLMs to search, upload, and manage digital assets through natural language, with secure local proxy and multi-tenant

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About

MCP server for Picsha AI platform enabling LLMs to search, upload, and manage digital assets through natural language, with secure local proxy and multi-tenant sandbox support.

README

The official Model Context Protocol (MCP) proxy server for the Picsha AI platform.

This package provides a secure, local stdio proxy that connects your LLM and AI agents (like Claude Desktop or OpenClaw) directly to your Picsha AI environment. By running locally, the server is natively enabled to securely read local files and utilize Picsha's direct-to-S3 upload pipelines.

Installation & Configuration

You do not need to install this package permanently. You can run it dynamically via npx.

Claude Desktop / OpenClaw

Add the following to your claude_desktop_config.json or openclaw.json:

{
  "mcpServers": {
    "picsha-ai": {
      "command": "npx",
      "args": [
        "-y",
        "@picsha-ai/mcp-server@latest"
      ],
      "env": {
        "PICSHA_API_TOKEN": "<YOUR_API_TOKEN_HERE>"
      }
    }
  }
}

Security & Multi-Tenancy

You can generate a PICSHA_API_TOKEN via your Picsha Admin Dashboard. By default, this token grants the AI agent administrative access across your entire organization's library.

Sandbox Mode (User Isolation): If you are embedding this MCP server for end-user Slack bots or customer facing SaaS products, you can dynamically restrict the agent's context to a specific user by injecting their User ID as an environment variable:

      "env": {
        "PICSHA_API_TOKEN": "<YOUR_API_TOKEN>",
        "PICSHA_EXTERNAL_USER_ID": "user_123"
      }

Available Tools

This MCP server provides the following capabilities to your LLM:

  • search_assets: Perform exact or hybrid semantic vector searches across your media.
  • get_asset: Retrieve deep metadata profiles for resources.
  • upload_asset: Automatically infers MIME types and effortlessly uploads local files into Picsha's asynchronous AI ingest pipeline.
  • generate_render_url: Provides on-the-fly image transformations and AI generative fill parameters.
  • trigger_url_ingest: Ingest public web media directly into the DAM.
  • moderate_asset, link_assets, create_dam_group, update_asset, delete_asset ...and more!

Troubleshooting

Claude Desktop Hangs or Fails to Connect

If you are using macOS and Claude Desktop gets stuck connecting to the MCP (or the tools never show up), it is likely due to npx dropping standard input/output streams. To fix this:

  1. Install the server globally instead of using npx:
    npm install -g @picsha-ai/mcp-server
    
  2. Update your claude_desktop_config.json to point directly to the installed binary:
    {
      "mcpServers": {
        "picsha-ai": {
          "command": "picsha-ai-mcp",
          "args": [],
          "env": {
            "PICSHA_API_TOKEN": "<YOUR_API_TOKEN_HERE>"
          }
        }
      }
    }
    
  3. Restart Claude Desktop.

from github.com/picsha-ai/mcp-server

Install Picsha AI Server in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install picsha-ai-mcp-server

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add picsha-ai-mcp-server -- npx -y @picsha-ai/mcp-server

FAQ

Is Picsha AI Server MCP free?

Yes, Picsha AI Server MCP is free — one-click install via Unyly at no cost.

Does Picsha AI Server need an API key?

No, Picsha AI Server runs without API keys or environment variables.

Is Picsha AI Server hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Picsha AI Server in Claude Desktop, Claude Code or Cursor?

Open Picsha AI Server on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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