Central Memory MCP
Workspace-grounded knowledge graph shared by multiple developers, hosted on Azure Functions with Table storage.
Que pouvez-vous faire avec Central Memory MCP ?
- read_graph - returns all entities for a workspace (relations currently queried separately and joined)
- upsert_entity - create or update entity (preserves existing Id if name exists)
- upsert_relation - create or update relation between two entities (requires GUIDs or resolvable names)
- get_entity_relations - list relations originating from a specific entity
- Health & Ready endpoints (/api/health, /api/ready)
Installation
Les étapes d'installation sont dans la documentation ci-dessous. Documentation
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.
Sommaire
Central Memory MCP Server (.NET 10 Azure Functions)
Model Context Protocol (MCP) compliant memory & knowledge graph server implemented in .NET 10 (Azure Functions isolated worker). Provides durable project memory (entities, relations, observations) for AI assistants with workspace isolation and simple HTTP tool endpoints.
Implemented MCP Tools
Current function set (alpha stage):
- read_graph - returns all entities for a workspace (relations currently queried separately and joined)
- upsert_entity - create or update entity (preserves existing Id if name exists)
- upsert_relation - create or update relation between two entities (requires GUIDs or resolvable names)
- get_entity_relations - list relations originating from a specific entity
- Health & Ready endpoints (/api/health, /api/ready)
Planned (not yet implemented): search_entities, search_relations, stats, temporal, batch operations, merge/detect duplicates.
Data Model
- Entities table: PartitionKey = WorkspaceName, RowKey = Guid (Id)
- Relations table: PartitionKey = WorkspaceName, RowKey = Guid (Id)
- Workspaces table (future expansion)
Observations stored as a single delimited string ("||") internally; split into List<string> at read time.
Quick Start
dotnet restore
dotnet build
func start --port 7071
curl http://localhost:7071/api/health
To read the graph, invoke the read_graph MCP tool from the client and supply the workspaceName parameter.
Directory Layout
flowchart TD
A[CentralMemoryMcp.Functions]
A --> P[Program.cs]
A --> SR[ServiceRegistration.cs]
A --> F[Functions]
F --> GF[GraphFunctions.cs]
F --> HF[HealthFunctions.cs]
A --> S[Services]
S --> KGS[KnowledgeGraphService.cs]
A --> ST[Storage]
ST --> TSS[TableStorageService.cs]
A --> M[Models]
M --> GM[GraphModels.cs]
A --> CFG[appsettings.json]
A --> HOST[host.json]
Usage Notes
- Use workspaceName consistently; workspaceId in docs replaced.
- Upsert preserves entity identity by lookup on (WorkspaceName + Name).
- Relation upsert requires entity GUIDs or resolves names; fails if names missing.
Logging & Telemetry
Add Application Insights connection to capture request latency & storage dependency tracking (future enhancement).
Roadmap
Add search, pagination, stats aggregation, batch operations, duplicate detection, merge strategy, semantic vector layer.
License
MIT.
Questions fréquentes
Qu'est-ce que Central Memory MCP ?
Workspace-grounded knowledge graph shared by multiple developers, hosted on Azure Functions with Table storage.
Comment installer Central Memory MCP ?
Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.
Central Memory MCP est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient Central Memory MCP ?
Il est publié par MWGMorningwood. AI.tn le référence sans le maintenir ni le recommander.
Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.