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qualityProvides tools for managing quantitative research knowledge graphs, enabling structured representation of research projects, datasets, variables, hypotheses, statistical tests, models, and results.
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内存 MCP 服务器
模型上下文协议 (MCP) 服务器提供知识图谱功能，用于管理内存中的实体、关系和观察，并具有严格的验证规则以维护数据一致性。
安装
在 Claude Desktop 中安装服务器：
mcp install main.py -v MEMORY_FILE_PATH=/path/to/memory.jsonl
数据验证规则
实体名称
必须以小写字母开头
可以包含小写字母、数字和连字符
最大长度为 100 个字符
在图表中必须是唯一的
有效名称示例：
python-project、meeting-notes-2024、user-john
实体类型
支持以下实体类型：
person：人类实体concept：抽象的想法或原则project：工作计划或任务document：任何形式的文件tool：软件工具或实用程序organization：公司或团体location：物理或虚拟位置event：有时限的事件
观察
非空字符串
最大长度为 500 个字符
每个实体必须是唯一的
应为事实和客观的陈述
包含相关时间戳
关系
支持以下关系类型：
knows：人与人之间的联系contains：父母/子女关系uses：实体利用另一个实体created：作者/创作关系belongs-to：成员资格/所有权depends-on：依赖关系related-to：一般关系
附加关系规则：
源实体和目标实体必须存在
不允许自指关系
不允许循环依赖
必须使用预定义的关系类型
用法
服务器提供了管理知识图谱的工具：
获取实体
result = await session.call_tool("get_entity", {
"entity_name": "example"
})
if not result.success:
if result.error_type == "NOT_FOUND":
print(f"Entity not found: {result.error}")
elif result.error_type == "VALIDATION_ERROR":
print(f"Invalid input: {result.error}")
else:
print(f"Error: {result.error}")
else:
entity = result.data
print(f"Found entity: {entity}")
获取图表
result = await session.call_tool("get_graph", {})
if result.success:
graph = result.data
print(f"Graph data: {graph}")
else:
print(f"Error retrieving graph: {result.error}")
创建实体
# Valid entity creation
entities = [
Entity(
name="python-project", # Lowercase with hyphens
entityType="project", # Must be a valid type
observations=["Started development on 2024-01-29"]
),
Entity(
name="john-doe",
entityType="person",
observations=["Software engineer", "Joined team in 2024"]
)
]
result = await session.call_tool("create_entities", {
"entities": entities
})
if not result.success:
if result.error_type == "VALIDATION_ERROR":
print(f"Invalid entity data: {result.error}")
else:
print(f"Error creating entities: {result.error}")
添加观察
# Valid observation
result = await session.call_tool("add_observation", {
"entity": "python-project",
"observation": "Completed initial prototype" # Must be unique for entity
})
if not result.success:
if result.error_type == "NOT_FOUND":
print(f"Entity not found: {result.error}")
elif result.error_type == "VALIDATION_ERROR":
print(f"Invalid observation: {result.error}")
else:
print(f"Error adding observation: {result.error}")
创建关系
# Valid relation
result = await session.call_tool("create_relation", {
"from_entity": "john-doe",
"to_entity": "python-project",
"relation_type": "created" # Must be a valid type
})
if not result.success:
if result.error_type == "NOT_FOUND":
print(f"Entity not found: {result.error}")
elif result.error_type == "VALIDATION_ERROR":
print(f"Invalid relation data: {result.error}")
else:
print(f"Error creating relation: {result.error}")
搜索记忆
result = await session.call_tool("search_memory", {
"query": "most recent workout" # Supports natural language queries
})
if result.success:
if result.error_type == "NO_RESULTS":
print(f"No results found: {result.error}")
else:
results = result.data
print(f"Search results: {results}")
else:
print(f"Error searching memory: {result.error}")
搜索功能支持：
时间查询（例如“最近”、“最后”、“最新”）
活动查询（例如“锻炼”、“运动”）
常规实体搜索
具有 80% 相似度阈值的模糊匹配
加权搜索范围：
实体名称（权重：1.0）
实体类型（权重：0.8）
观察结果（权重：0.6）
删除实体
result = await session.call_tool("delete_entities", {
"names": ["python-project", "john-doe"]
})
if not result.success:
if result.error_type == "NOT_FOUND":
print(f"Entity not found: {result.error}")
else:
print(f"Error deleting entities: {result.error}")
删除关系
result = await session.call_tool("delete_relation", {
"from_entity": "john-doe",
"to_entity": "python-project"
})
if not result.success:
if result.error_type == "NOT_FOUND":
print(f"Entity not found: {result.error}")
else:
print(f"Error deleting relation: {result.error}")
刷新内存
result = await session.call_tool("flush_memory", {})
if not result.success:
print(f"Error flushing memory: {result.error}")
错误类型
服务器使用以下错误类型：
NOT_FOUND：未找到实体或资源VALIDATION_ERROR：输入数据无效INTERNAL_ERROR：服务器端错误ALREADY_EXISTS：资源已存在INVALID_RELATION：实体之间的关系无效
响应模型
所有工具都使用以下模型返回类型化的响应：
实体响应
class EntityResponse(BaseModel):
success: bool
data: Optional[Dict[str, Any]] = None
error: Optional[str] = None
error_type: Optional[str] = None
GraphResponse
class GraphResponse(BaseModel):
success: bool
data: Optional[Dict[str, Any]] = None
error: Optional[str] = None
error_type: Optional[str] = None
操作响应
class OperationResponse(BaseModel):
success: bool
error: Optional[str] = None
error_type: Optional[str] = None
发展
运行测试
pytest tests/
添加新功能
更新
validation.py中的验证规则在
tests/test_validation.py中添加测试在
knowledge_graph_manager.py中实现更改
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
提供知识图谱功能，用于管理内存中的实体、关系和观察，并使用严格的验证规则来维护数据一致性。
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