Skip to main content
Glama

Code Knowledge MCP Server

by davidvc
fixtures.py2.69 kB
"""Test fixtures and helper functions.""" import json from typing import Any, Dict, List import mcp.types as types from pathlib import Path # Test storage directory TEST_STORAGE_DIR = Path("test_knowledge_store") # Test knowledge examples TEST_KNOWLEDGE = { "active_context": { "path": "memory-bank/activeContext.md", "content": """ # Active Context ## Current Focus Integration testing with focus on MCP functionality: - Single comprehensive integration test suite - Focus on MCP tool functionality - Testing real-world usage scenarios """, "metadata": { "type": "memory_bank", "category": "active_context", "last_updated": "2024-02-17" } }, "system_patterns": { "path": "memory-bank/systemPatterns.md", "content": """ # System Patterns ## Memory Bank Architecture The memory bank combines two complementary storage approaches: 1. Vector Database (ChromaDB) 2. Markdown Documentation """, "metadata": { "type": "memory_bank", "category": "architecture", "status": "current" } } } def assert_tool_response( result: List[types.TextContent | types.ImageContent], expected_data: Dict[str, Any] = None, expect_error: bool = False ) -> Dict[str, Any]: """Assert tool response format and return parsed data.""" assert len(result) == 1 assert result[0].type == "text" data = json.loads(result[0].text) if expect_error: assert "error" in data else: assert "error" not in data if expected_data: for key, value in expected_data.items(): assert data[key] == value return data def assert_resource_content( content: str, expected_content: str, expected_metadata: Dict[str, Any] ) -> None: """Assert resource content matches expectations.""" data = json.loads(content) assert data["content"] == expected_content assert data["metadata"] == expected_metadata def assert_storage_exists() -> None: """Assert storage files exist.""" assert TEST_STORAGE_DIR.exists() assert (TEST_STORAGE_DIR / "embeddings.npy").exists() assert (TEST_STORAGE_DIR / "segments.json").exists() async def add_test_knowledge(server, entries: Dict[str, Dict] = None) -> None: """Add test knowledge entries to server.""" entries = entries or TEST_KNOWLEDGE for entry in entries.values(): await server.call_tool( "add_knowledge", { "path": entry["path"], "content": entry["content"], "metadata": entry["metadata"] } )

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/davidvc/code-knowledge-mcptool'

If you have feedback or need assistance with the MCP directory API, please join our Discord server