MCP Test MCP

--- story_id: "0008" title: "Implement prompt testing tools" created: "2025-10-09" status: done dependencies: ["0003", "0004"] estimated_complexity: "medium" tags: ["tools", "prompts", "phase1"] - status: in-progress timestamp: 2025-10-09T21:53:54Z - status: ready-for-review timestamp: 2025-10-09T22:16:10Z - status: done timestamp: 2025-10-10T01:13:01Z --- # Story 0008: Implement prompt testing tools ## Description Implement the two MCP tools for testing target server prompts: list_prompts and get_prompt. These tools enable AI assistants to discover and retrieve prompts from connected MCP servers. ## Acceptance Criteria - [x] `src/mcp_test_mcp/tools/prompts.py` created - [x] `list_prompts()` tool implemented - [x] `get_prompt(name: str, arguments: dict)` tool implemented - [x] Both tools registered with FastMCP server - [x] `list_prompts()` returns complete prompt metadata with argument schemas - [x] `get_prompt()` returns rendered prompt messages - [x] Error handling for not_connected, prompt_not_found, invalid_arguments - [x] Statistics updated after each prompt retrieval - [x] Unit tests for each tool (88%+ coverage) - [x] Integration test with mock MCP server providing prompts ## Technical Notes **list_prompts response:** ```python { "success": true, "prompts": [ { "name": "greeting", "description": "Generate a greeting", "arguments": [ { "name": "name", "description": "Person's name", "required": true } ] } ], "metadata": { "total_prompts": 1, "retrieved_at": "...", "request_time_ms": 76 } } ``` **get_prompt response:** ```python { "success": true, "prompt": { "name": "greeting", "description": "Generate a greeting", "messages": [ { "role": "user", "content": {"type": "text", "text": "Hello, Alice!"} } ] } } ``` ## AI Directives **IMPORTANT**: As you work through this story, please mark checklist items as complete `[x]` as you finish them. This ensures that if we need to pause and resume work, we have a clear record of progress. Update the `status` field in the frontmatter when moving between stages (in-progress, ready-for-review, done, blocked). Include full argument schemas to help AI construct valid prompt requests.