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T1nker-1220/memories-with-lessons-mcp-server

Memory server extended with lessons

Before you install: no copy-paste command · no license recorded · link reachable

First step: nothing runnable here yet - start from the repository: https://github.com/T1nker-1220/memories-with-lessons-mcp-server

View on GitHub ↗Link checked 2026-11-12 · HTTP 200 · opens the vendor's own site

We have neither an install command nor a public remote endpoint from this repository, so we do not print a config. A made-up one is worse than none. How each client wires MCP up →

Source
collected from the abordage/awesome-mcp list · type: MCP server
Harvest history
first seen 2026-11-05 · last seen 2026-11-14 · seen 10× · listed by 10 sources
Score
score 1,003 · 10 sources · mcp
FAQ (answers come from our records)
Who is it for?
We filed it under these tags: MCP 服务. The tags come from the entry itself, not a taxonomy we imposed.
Who maintains it?
first catalogued 2026-11-05;last seen 2026-11-14。There is no official certification or quality rating here — we record sources and dates only.

# Knowledge Graph Memory Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

A basic implementation of persistent memory using a local knowledge graph. This lets Claude remember information about the user across chats and learn from past errors through a lesson system.
## Core Concepts
### Entities
Entities are the primary nodes in the knowledge graph. Each entity has:
A unique name (identifier)
An entity type (e.g., "person", "organization", "event")
A list of observations
Example:
json
"name": "JohnSmith",
"entityType": "person",
"observations": ["Speaks fluent Spanish"]
### Relations
Relations define directed connections between entities. They are always stored in active voice and describe how entities interact or relate to each other.
Example:
json
"from": "JohnSmith",
"to": "Anthropic",
"relationType": "worksat"
### Observations
Observations are discrete pieces of information about an entity. They are:
Stored as strings
Attached to specific entities
Can be added or removed independently
Should be atomic (one fact per observation)
Example:
json
"entityName": "JohnSmith",
"observations": [
"Speaks fluent Spanish",
"Graduated in 2019",
"Prefers morning meetings"
### Lessons
Lessons are special entities that capture knowledge about errors and their solutions. Each lesson has:
A unique name (identifier)
Error pattern information (type, message, context)
Solution steps and verification
Success rate tracking
Environmental context
Metadata (severity, timestamps, frequency)
Example:
json
"name": "NPMVERSIONMISMATCH01",
"entityType": "lesson",
"observations": [
"Error occurs when using incompatible package versions",
"Affects Windows environments specifically",
"Resolution requires version pinning"
],
"errorPattern": {
"type": "dependency",
"message": "Cannot find package @shadcn/ui",
"context": "package installation"
},
"metadata": {
"severity": "high",
"environment": {
"os": "windows",
"nodeVersion": "18.x"
},
"createdAt": "2025-02-13T13:21:58.523Z",
"updatedAt": "2025-02-13T13:22:21.336Z",
"frequency": 1,
"successRate": 1.0
},
"verificationSteps": [
"command": "pnpm add shadcn@latest",
"expectedOutput": "Successfully installed shadcn",
"successIndicators": ["added shadcn"]
## API
### Tools
createentities
Create multiple new entities in the knowledge graph
Input: entities (array of objects)
Each object contains:
name (string): Entity identifier
entityType (string): Type classification
observations (string[]): Associated observations
Ignores entities with existing names
createrelations
Create multiple new relations between entities
Input: relations (array of objects)
Each object contains:
from (string): Source entity name
to (string): Target entity name
relationType (string): Relationship type in active voice
Skips duplicate relations
addobservations
Add new observations to existing entities
Input: observations (array of objects)
Each object contains:
entityName (string): Target entity
contents (string[]): New observations to add
Returns added observations per entity
Fails if entity doesn't exist
deleteentities
Remove entities and their relations
Input: entityNames (string[])
Cascading deletion of associated relations
Silent operation if entity doesn't exist
deleteobservations
Remove specific observations from entities
Input: deletions (array of objects)
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[![Listed on Anclum](https://anclum.com/badge/listed.svg)](https://anclum.com/en/s/t1nker-1220-memories-with-lessons-mcp-server/)
Source
awesome · https://github.com/T1nker-1220/memories-with-lessons-mcp-server
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