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Mirror MCP

Adds a reflect tool that uses MCP sampling for model self-questioning, context, and configurable prompts.

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Install Mirror MCP

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": {
    "mirror-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "mirror-mcp"
      ]
    }
  }
}

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

Automated check passed— started and listed 1 tools correctly (2d ago).

Overview

The mirror-mcp MCP server exposes a reflect tool that lets an LLM ask itself a question through MCP sampling. It accepts a question, optional context, custom prompts, and sampling controls, then returns a reflection with metadata. Use it when an agent needs to review reasoning, examine assumptions, or explore alternative perspectives. It runs as a standard stdio MCP server through npx or a global npm installation.

Use cases

  • Review an earlier analysis for unsupported assumptions
  • Check confidence in a conclusion before presenting it
  • Ask for alternative perspectives on a proposed solution
  • Structure a critical-thinking or coaching reflection
  • Iterate on reasoning with additional context

Key features

  • MCP sampling through a reflect tool
  • Custom system and user prompts
  • Optional context for reflection requests
  • Configurable token limit and temperature
  • Reflection metadata with token and timing details
  • stdio launch through npx

Tools1

What Mirror MCP lets your agent do. Expand a tool for its parameters.

Verified live~354 tokens of context

Security & health

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

ActiveLast checked 2d ago

Recent health check succeeded.

8/8 checks healthy over the last 49d

What it can do

From the 1 tool this server returned when we ran it.

Read-only tools · 1
Network at startup3 connections
Files written at startupNone
Install scriptsprepare
npm provenanceNot published
Package age453 days
Maintainers1

Observed 2026-10-25 in an isolated sandbox. A description of reach, not a security audit.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 12d ago via OSV.dev · mirror-mcp (npm)

Adoption & maintenance

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

GitHub stars15Stargazers on the source repository.
npm downloads187Package downloads in the last 30 days.
Last commit1y agoMost recent push to the default branch.
Availability100%Our rolling endpoint + install checks that succeeded.
Install checkPassedOur sandbox started it and listed its tools.
Tools exposed1Callable tools this server registers over MCP.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Mirror MCP works

What mirror-mcp MCP server does

The mirror-mcp MCP server adds one MCP tool, reflect, for model-directed self-questioning. An LLM supplies a question and can include prior context, then receives a response generated through MCP sampling. The result contains the reflection and metadata such as token usage and elapsed reflection time.

The tool is intended for reasoning checks rather than access to an external application or data source. Typical prompts can ask the model to assess confidence, identify weaknesses, inspect assumptions, or consider other viewpoints.

How it works

The calling MCP client sends the reflection request to mirror-mcp, which passes the self-directed question to the MCP sampling interface. Sampling options control response generation, while the returned result is formatted for the client to consume.

Without custom instructions, the tool uses built-in guidance oriented around strengths, weaknesses, assumptions, and alternative perspectives. A caller can instead provide a system prompt to establish a role or perspective and a user prompt to specify the desired structure or focus. This makes mirror-mcp suitable for tasks such as critical review, coaching-style analysis, and iterative problem-solving.

The max_tokens option defaults to 500, and temperature defaults to 0.8. The tool also accepts a separate context value so the reflection can refer to information from the current reasoning process.

Setup and configuration

The mirror-mcp MCP server can run without a local installation by using:

Terminal
npx mirror-mcp

For a persistent npm installation, install the package globally with npm install -g mirror-mcp. MCP hosts using stdio can launch it with the following configuration:

config.json
{
  "type": "stdio",
  "command": "npx",
  "args": ["mirror-mcp@latest"]
}

VS Code has a documented one-click installation path. Developers running from source need Node.js 18 or newer, then clone the repository, install dependencies, build the project, and start it. Development also provides a npm run dev command and a test command.

Tools and capabilities

reflect accepts these arguments:

  • question — required string containing the self-directed question.
  • context — optional supporting information.
  • system_prompt — optional instruction defining the reflection role or perspective.
  • user_prompt — optional instruction controlling response format, structure, or focus.
  • max_tokens — optional response limit, defaulting to 500.
  • temperature — optional sampling setting, defaulting to 0.8.

The response includes a reflection string and metadata with token usage and reflection time.

Limitations and notes

Reflection quality depends on the model and MCP client providing sampling support. The server does not independently verify the model’s conclusions; its output is another model-generated perspective. Custom prompts replace or shape the default reflection guidance, so callers should specify the desired review method when consistent structure matters.

The documented deployment uses stdio. No environment variables or authentication settings are specified. The project is distributed under the MIT license.

Read the full README View source on GitHub

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Frequently Asked Questions about Mirror MCP

mirror-mcp is an MCP server that connects an MCP-compatible AI client to MCP sampling infrastructure and exposes the reflect tool. It lets a model submit a question, optional context, and prompt instructions, then receive a sampled reflection with configurable token and temperature limits plus response metadata.

Run `npx mirror-mcp` to use it without installation, or install it globally with `npm install -g mirror-mcp`. For an MCP host, configure a stdio server with `npx` as the command and `mirror-mcp@latest` as its argument.

The `reflect` tool sends a model’s question through MCP sampling and returns a reflection. It can include context, custom system and user prompts, a maximum token count, and a temperature value.

Yes, provide `system_prompt` to set the reflection role or perspective and `user_prompt` to control the response’s format or focus. If these are omitted, the tool uses built-in guidance about assumptions, weaknesses, strengths, and alternative perspectives.

Other MCP-compatible clients can use the same stdio setup.

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