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@mcp-workbench/mcp-server

Agent-facing MCP adapter for MCP Workbench — lets AI agents inspect, test, and validate MCP servers through structured tool calls.

Claude Code demo

Overview

@mcp-workbench/mcp-server wraps the MCP Workbench CLI as an MCP server, exposing its inspect, generate, run, and explain capabilities as structured tools that AI agents can call directly. It spawns the CLI as a subprocess and parses the output into typed responses.

Entry points: @mcp-workbench/cli is the human-facing runner. @mcp-workbench/mcp-server is the agent-facing MCP adapter. Both use the same core engine.

Prerequisites

• Node.js >= 20

• MCP Workbench CLI must be installed and available on your PATH:

# Primary — scoped package
npm install -g @mcp-workbench/cli

# Alternative — convenience wrapper
npm install -g mcp-workbench-cli

Or set the MCP_WORKBENCH_CLI environment variable to point to the binary.

Installation

npm install -g @mcp-workbench/mcp-server

Or clone and build from source:

git clone https://github.com/raeseoklee/mcp-workbench-mcp-server.git
cd mcp-workbench-mcp-server
npm install
npm run build

Connecting to a Host

Claude Code

claude mcp add mcp-workbench -- npx -y @mcp-workbench/mcp-server

OpenAI Codex CLI

codex mcp add mcp-workbench -- npx -y @mcp-workbench/mcp-server

Or add to ~/.codex/config.toml:

[mcp_servers.mcp-workbench]
command = "npx"
args    = ["-y", "@mcp-workbench/mcp-server"]
enabled = true

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mcp-workbench": {
      "command": "npx",
      "args": ["-y", "@mcp-workbench/mcp-server"]
    }
  }
}

Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "mcp-workbench": {
      "command": "npx",
      "args": ["-y", "@mcp-workbench/mcp-server"]
    }
  }
}

Available Tools

inspect_server

Connect to an MCP server and inspect its capabilities, version, and supported features.

Inputs:

Output: Human-readable summary + structured JSON:

{
  "serverName": "my-server",
  "serverVersion": "1.0.0",
  "protocolVersion": "2025-11-25",
  "capabilities": {
    "tools": true,
    "resources": true,
    "prompts": false,
    "completions": false,
    "logging": false
  }
}

generate_spec

Auto-generate a YAML test spec by discovering server capabilities. Partial discovery is supported automatically by the underlying CLI.

Inputs:

Output: Human-readable summary + structured JSON:

{
  "yaml": "apiVersion: mcp-workbench.dev/v0alpha1\n...",
  "testCount": 9,
  "warnings": ["city: TODO_CITY_NAME  # TODO: replace with actual value"]
}

run_spec

Run a YAML test spec against an MCP server. Provide either specText (inline YAML) or specPath (path to a file). At least one is required.

Inputs:

*At least one of specText or specPath must be provided.

Output: Human-readable summary + structured JSON:

{
  "total": 3,
  "passed": 3,
  "failed": 0,
  "skipped": 0,
  "errors": 0,
  "durationMs": 4,
  "failures": []
}

explain_failure

Analyze test run results and explain failures with heuristic classification and actionable recommendations.

Inputs:

Output: Human-readable summary + structured JSON:

{
  "summary": "All tests passed",
  "causes": [],
  "recommendations": []
}

Internationalization

Tool text summaries support multiple languages. Structured JSON outputs are always language-neutral.

Set language via environment variable:

MCP_WORKBENCH_LANG=ko node dist/index.js

Only user-facing text summaries are translated. Tool names, schema fields, and JSON output keys are always in English.

Example Use Cases

• "Inspect this server and tell me what capabilities it has"

• "Generate a YAML test spec for this server"

• "Run this spec and explain any failures"

Security Considerations

• Authentication headers are passed per-call and not persisted

• No tokens or credentials are stored by this server

• Tokens are not echoed back in tool outputs

• The server spawns mcp-workbench CLI as a subprocess with the current environment

• Spec files written to temp directories are cleaned up after use

MVP Limitations

• specText in run_spec uses a temporary file internally

• Headers in run_spec are not forwarded to the underlying server — headers must be embedded in the spec YAML itself

• explain_failure is heuristic-based, not AI-powered

• generate_spec test count detection is regex-based

• Only stdio transport is supported for connecting to this MCP server itself

• No streaming of test results (waits for full completion)

• No caching of inspection or generation results between calls

Development

npm install
npm run build
npm test

Roadmap

v0.1 (current):

• inspect_server, generate_spec, run_spec, explain_failure

• Claude Code integration demo

v0.2:

• Structured outputs via outputSchema (when SDK support lands)

• Spec diff support

v0.3:

• AI-assisted assertions

• Merge/update existing spec

License

Apache-2.0