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MCP Server

by DollhouseMCP

Adds modular personas, skills, templates, agents, memories, and ensembles to MCP-compatible AI clients.

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Install MCP Server

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "dollhousemcp-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@dollhousemcp/mcp-server@latest"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— we haven't run this command through our automated sandbox yet. Not a red flag; we're working through the catalog.

Overview

DollhouseMCP/mcp-server MCP server adds reusable personas, skills, templates, agents, memories, and ensembles to MCP clients. It stores elements in a local portfolio, where you can create, edit, activate, search, browse, and install customization content. Activated elements can change behavior, available tools, commands, and approval requirements. Reach for it when you need repeatable AI behavior, structured context, reusable output formats, or grouped customization policies.

Use cases

  • Create reusable personas for recurring workflows
  • Activate skills for on-demand capabilities
  • Standardize reports and other outputs with templates
  • Persist project facts and preferences across sessions
  • Bundle related customization elements into ensembles

Key features

  • Personas with behavior and permission policies
  • Skills, templates, agents, memories, and ensembles
  • Local portfolio for created and installed elements
  • Community collection browsing and installation
  • Bidirectional Dollhouse and agent skills conversion
  • Multi-step agent execution and structured memory

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 3d ago

Recent health check succeeded.

17/17 checks healthy over the last 79d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 9h ago via OSV.dev · @dollhousemcp/mcp-server@latest (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars46Stargazers on the source repository.
npm downloads1.5kPackage downloads in the last 30 days.
Last commit3d agoMost recent push to the default branch.
Directory activity4 viewsConfig copies, upvotes, and views on AllMCPs.

How MCP Server works

What DollhouseMCP/mcp-server does

DollhouseMCP/mcp-server MCP server provides modular customization elements for MCP-compatible AI applications. Its six element types are personas, skills, templates, agents, memories, and ensembles. Personas influence behavior, tone, expertise, priorities, and permission policies. Skills add on-demand capabilities, templates standardize generated outputs, agents manage multi-step goals, memories retain structured context, and ensembles combine multiple elements into one activatable unit.

The server is useful for teams or individual developers who want reusable AI behavior instead of repeating the same instructions in every conversation. It also supports a public collection of shareable elements and local installations from that collection.

How it works

Elements are kept in a local portfolio directory: ~/.dollhouse/portfolio/ on macOS and Linux, or %USERPROFILE%\\.dollhouse\\portfolio\\ on Windows. The portfolio contains starter elements, user-created content, and installed community elements.

After connecting the server to an MCP client, you can describe an element in natural language, activate an existing item, or refine one that is already in the portfolio. Activation changes the AI's behavior or available capabilities for the session. Ensembles can activate several elements together and coordinate their activation and permission policies.

DollhouseMCP/mcp-server MCP server also includes a bidirectional converter for Dollhouse Skills and the later agent skills format. Converted skills can be managed as native Dollhouse elements or exported for platforms that use the other format.

Setup and configuration

The interactive installer is started with:

Terminal
npx @dollhousemcp/mcp-server@latest --web

It opens a browser-based setup wizard and can install the server for Claude Desktop, Claude Code, Cursor, VS Code, Codex, Gemini CLI, Windsurf, Cline, and LM Studio. The wizard detects existing installations and supports automatic updates or pinned versions.

Claude Code can also be configured directly:

Terminal
claude mcp add -s user dollhousemcp -- npx -y @dollhousemcp/mcp-server

For Claude Desktop, the project provides a desktop extension in .mcpb format that can be downloaded and opened. The server supports Windows, macOS, and Linux.

Permission-hook support varies by client. Claude Code has full native support; Cursor, VS Code, Codex, Gemini CLI, and Windsurf have partial support. Codex's partial support is Bash-only. Cline and LM Studio provide MCP setup in the documented release, while Claude Desktop has no native permission-hook path in that release.

Tools and capabilities

The documented workflows expose capabilities to:

  • Create and edit personas, skills, templates, agents, memories, and ensembles.
  • Activate elements from the local portfolio.
  • Search and browse available elements.
  • Install elements from the community collection.
  • Convert skills between Dollhouse and agent skills formats.
  • Persist structured facts, preferences, and project state through memories.
  • Apply permission policies through personas and ensembles.
  • Run multi-step agent goals with state tracking and autonomy-related policies.

DollhouseMCP/mcp-server MCP server includes starter content and supports adding content created locally or obtained from the community collection.

Limitations and notes

Core element management is documented as working across MCP-compatible platforms. Advanced Gatekeeper confirmation flows and agentic loop execution have been tested extensively on Claude Code and are expected to depend on standard MCP tool call and response behavior on other clients.

Permission hooks are not equally available across the supported clients, so installing the MCP server does not guarantee the same approval workflow everywhere. Skills introduced by DollhouseMCP predate the later agent skills format; conversion is provided for interoperability rather than treating the formats as identical.

The project is licensed under AGPL-3.0.

Read the full README View source on GitHub

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Frequently Asked Questions about MCP Server

DollhouseMCP/mcp-server is an MCP server that connects MCP-compatible AI clients to a local portfolio of reusable customization elements. Its main tools support creating, editing, activating, searching, and browsing personas, skills, templates, agents, memories, and ensembles, with skill-format conversion and permission policies.

Run `npx @dollhousemcp/mcp-server@latest --web` to open the browser-based setup wizard. It installs the server for supported clients including Claude Desktop, Claude Code, Cursor, VS Code, Codex, Gemini CLI, Windsurf, Cline, and LM Studio.

Yes, DollhouseMCP/mcp-server works with Cursor through the interactive setup wizard. Core element management is supported, while permission-hook support is listed as partial native support for Cursor.

DollhouseMCP/mcp-server stores elements in a local portfolio at `~/.dollhouse/portfolio/` on macOS and Linux, and `%USERPROFILE%\\.dollhouse\\portfolio\\` on Windows. The folder holds starter, created, and installed community elements.

Yes, DollhouseMCP/mcp-server includes a bidirectional converter between its Dollhouse Skills format and the agent skills format. It can import agent skills as Dollhouse elements and export Dollhouse Skills for platforms that use the other format.

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