mcp-testing-tools
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| generate_testsB | Generate test cases from a function signature. Produces happy path, edge cases, error cases, and boundary value tests as Jest/Vitest test code. |
| generate_mock_dataA | Generate realistic mock data: names, emails, addresses, dates, UUIDs, phone numbers, company names, credit cards (fake), IP addresses. Configurable count and locale. |
| generate_api_mockB | Generate mock API responses from a schema. Creates realistic JSON responses for REST endpoints based on field names and types. |
| analyze_test_coverageA | Parse source code and test code to identify untested functions. Suggests which functions need tests most based on complexity, export status, and parameter count. |
| generate_assertionsA | Given expected and actual values (as JSON strings), generate detailed assertion code with descriptive messages. Supports deep object comparison, array comparison, and type checking. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Most tools have clearly distinct purposes, but generate_tests and generate_assertions overlap slightly since generated test cases often include assertions. generate_mock_data and generate_api_mock are similarly related, though the former is general-purpose data and the latter is schema-driven API responses.
All tool names follow a consistent verb_noun pattern: generate_tests, generate_mock_data, generate_api_mock, generate_assertions, and analyze_test_coverage. The naming convention is uniform and predictable.
Five tools is a well-scoped set for a testing-focused server. Each tool covers a distinct aspect of test generation, mocking, assertions, or coverage analysis without unnecessary redundancy.
The tool surface covers test generation, mock data, API mocking, assertions, and coverage analysis well. Minor gaps exist, such as no direct test execution or test file management, but the core testing workflow is addressed.