# mockloop-mcp [Health: Active]

**Category:** 💻 Developer Tools  
**Repository:** https://github.com/MockLoop/mockloop-mcp  
**GitHub Stars:** 17  
**Views:** 0  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/mockloop-mcp

## Description
Intelligent Model Context Protocol (MCP) server for AI-assisted API development. Generate mock servers from OpenAPI specs with advanced logging, performance analytics, and server discovery. Optimized for AI development workflows with comprehensive testing insights and automated analysis.

## Tools
Capabilities this server exposes over MCP:

- **validate_scenario_config**
- **deploy_scenario**
- **switch_scenario**
- **list_active_scenarios**
- **execute_test_plan**
- **run_test_iteration**
- **run_load_test**
- **run_security_test**
- **analyze_test_results**
- **generate_test_report**
- **compare_test_runs**
- **get_performance_metrics**
- **create_test_session**
- **end_test_session**
- **schedule_test_suite**
- **monitor_test_progress**

## Claude Desktop Quick Installation
Install path detected from listing signals. Uses `uvx` (confidence: high):

```json
"mcpServers": {
  "mockloop-mcp": {
    "command": "uvx",
    "args": ["mockloop-mcp"]
  }
}
```

## Documentation

## What mockloop-mcp does

mockloop-mcp connects an MCP-compatible AI client to API testing workflows centered on scenarios, test plans, and test results. Its capabilities cover scenario validation and deployment, switching between active scenarios, individual test iterations, complete test plans, load tests, and security tests.

The server also supports analysis and reporting. Agents can inspect performance metrics, compare test runs, generate reports, and monitor progress. OpenAPI-oriented prompts can help analyze an API for testing, generate scenario configurations, optimize scenarios for load, create error cases, and produce security-test scenarios.

Scenario resources include load-testing, error-simulation, security, performance, and integration-testing packs. The project also describes community sharing and validation for these scenario resources.

## How it works

The server exposes testing operations as MCP tools and maintains state for longer workflows. Test sessions can be created and ended explicitly, while workflow and agent contexts hold data across related operations. Context data can be retrieved or updated, and context snapshots can be created and restored for recovery or rollback.

Global context provides a way to share selected data across sessions. The workflow tools can schedule a test suite and report its progress while execution is underway. Audit logging covers request and response trails, performance information, and security events for testing and compliance-oriented tracking.

## Setup and configuration

Install the Python package with:

```bash
pip install mockloop-mcp
```

Verify the command is available by running:

```bash
mockloop-mcp --version
```

Then add the server to an MCP client configuration. The quick-start instructions identify Cline and Claude Desktop as supported configuration targets. Releases and tool schemas can also be checked through the project’s SchemaPin metadata at `https://mockloop.com/.well-known/schemapin.json`.

## Tools and capabilities

The exposed testing tools are grouped into four areas:

- Scenario management: `validate_scenario_config`, `deploy_scenario`, `switch_scenario`, and `list_active_scenarios`.
- Test execution: `execute_test_plan`, `run_test_iteration`, `run_load_test`, and `run_security_test`.
- Analysis and reporting: `analyze_test_results`, `generate_test_report`, `compare_test_runs`, and `get_performance_metrics`.
- Workflow management: `create_test_session`, `end_test_session`, `schedule_test_suite`, and `monitor_test_progress`.

Additional MCP prompts support OpenAPI analysis and scenario generation. Context operations include creating session, workflow, and agent contexts; reading and updating context data; listing contexts; managing snapshots; and reading or changing global context.

## Limitations and notes

mockloop-mcp is designed for MCP clients and requires client-side MCP configuration after installation. Its testing behavior depends on the scenarios, test plans, and context supplied to the tools. Validate that installed releases and tool schemas originate from the project’s repository, using SchemaPin where appropriate.

_Full upstream README: https://allmcps.com/mcp/mockloop-mcp/readme_