--- title: MCP Setup - Connect AI Assistants description: Connect Claude Code, Cursor, Windsurf, Cline, or OpenCode to MockServer via the built-in MCP endpoint at /mockserver/mcp -- no glue code required. shortTitle: MCP Setup layout: page pageOrder: 1 section: 'AI Integration' subsection: true sitemap: priority: 0.8 changefreq: 'monthly' lastmod: 2026-05-22T00:00:00+00:00 ---

MockServer includes a built-in MCP (Model Context Protocol) server that enables AI coding assistants to programmatically create mock expectations, verify requests, retrieve recorded traffic, and debug HTTP issues — all through natural language conversations.

## Prerequisites

You need a running MockServer instance. The quickest way to start one is with Docker:

    docker run -d --rm -p 1080:1080 mockserver/mockserver

Alternatively, see Running MockServer for other ways to start MockServer (Java API, Maven plugin, npm, etc.).

## MCP Endpoint

The MCP server is available at the following URL on any running MockServer instance — no additional configuration is required:

    http://localhost:1080/mockserver/mcp

The endpoint supports the Streamable HTTP transport as defined by the MCP specification. If your MockServer is running on a different host or port, adjust the URL accordingly.

## Configuring Your AI Assistant

Choose your AI coding assistant or client library below and follow the configuration instructions.

### Cursor

Create a `.cursor/mcp.json` file in your project root:

    {
      "mcpServers": {
        "mockserver": {
          "type": "streamable-http",
          "url": "http://localhost:1080/mockserver/mcp"
        }
      }
    }

Restart Cursor to pick up the new configuration.

### Claude Code

Run the following command in your terminal:

    claude mcp add mockserver --transport streamable-http http://localhost:1080/mockserver/mcp

Claude Code will automatically detect the MCP server on the next conversation.

### Windsurf

Create a `.windsurf/mcp.json` file in your project root:

    {
      "mcpServers": {
        "mockserver": {
          "type": "streamable-http",
          "url": "http://localhost:1080/mockserver/mcp"
        }
      }
    }

Restart Windsurf to pick up the new configuration.

### Cline

Create a `.cline/mcp_settings.json` file in your project root:

    {
      "mcpServers": {
        "mockserver": {
          "type": "streamable-http",
          "url": "http://localhost:1080/mockserver/mcp"
        }
      }
    }

Cline will detect the new MCP server automatically.

### Continue

Add the following to your `.continue/config.yaml` file:

    mcpServers:
      - name: mockserver
        type: streamable-http
        url: http://localhost:1080/mockserver/mcp

Restart Continue to pick up the new configuration.

### OpenCode

Add the following to your `.opencode/config.toml` file:

    [mcpServers.mockserver]
    type = "streamable-http"
    url = "http://localhost:1080/mockserver/mcp"

OpenCode will detect the new MCP server on the next session.

### Programmatic clients (LangChain, LangGraph, ...)

The assistants above are IDE and CLI tools configured through a file or command. You can also connect to the MCP endpoint programmatically — for example from an agent built with LangChain or LangGraph using the `langchain-mcp-adapters` library. The same approach applies to any MCP client library:

    from langchain_mcp_adapters.client import MultiServerMCPClient
    from langgraph.prebuilt import create_react_agent

    client = MultiServerMCPClient({
        "mockserver": {
            "transport": "streamable_http",
            "url": "http://localhost:1080/mockserver/mcp",
        }
    })

    # MockServer's MCP tools are now available to the agent
    tools = await client.get_tools()
    agent = create_react_agent(model, tools)

The agent can now create expectations, verify requests, retrieve recorded traffic, and debug mismatches through the same MCP tools as the IDE assistants above.

## Quick Test

Once configured, verify the integration by asking your AI assistant:

> "Create a mock that returns 200 OK for GET /api/health"

The assistant should use the `create_expectation` MCP tool to configure the expectation on your running MockServer instance. You can verify it worked by running:

    curl -v http://localhost:1080/api/health

You should see a `200 OK` response.

## Next Steps

- MCP Tools Reference — full documentation of all available MCP tools, parameters, and example requests
- Debugging with AI — workflows for using AI assistants to debug HTTP traffic
- Contract Verification — verify recorded traffic and run contract/resiliency tests against an OpenAPI spec
- AI Traffic Inspection — inspect and record LLM/MCP traffic for debugging and deterministic replay
- OpenAPI for AI — using MockServer's OpenAPI spec as a fallback for AI tools without MCP support