Practical overview
When it fits
Use MagiCore when a .NET application needs memory beyond the current interaction, especially when scoped semantic search, auditable history, or temporal and spatial records are part of the design.
Who it is for
- Developers building AI agents or assistants in .NET that need persistent, scoped recall.
- Teams building simulations or robotics applications that need timestamped spatial observations or action episodes.
- Developers integrating memory with Microsoft.Extensions.AI, Microsoft.Extensions.VectorData or the .NET MCP SDK.
Documented uses
- Save user-, session- or agent-scoped information and retrieve relevant context with a query.
- Combine dense vector retrieval and BM25 keyword scoring, with reranking options.
- Track memory changes and, with history-capable storage, query past state or roll back selected changes.
- Represent timestamped 3D observations and recall measured action episodes.
Requirements & limits
The repository identifies the project as Apache-2.0 licensed and documents package installation through NuGet.
- Basic memory can run in-process using the documented local defaults, without a required hosted service.
- Durable vector storage is configurable through Microsoft.Extensions.VectorData; the README lists PostgreSQL/pgvector, Qdrant, SQLite, Redis and other providers.
- Point-in-time reads and rollback require a history-capable store, and provider limitations apply.
- The documented target frameworks include .NET Standard 2.0 and .NET 8, 9 and 10.
Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.
Add and search a local memory
Use the documented default service to save a user-scoped fact and retrieve it with a query.
Before you start
- A .NET project with the MagiCore package installed.
- C# code using the MagiCore namespace.
Steps
Install the package with
dotnet add package MagiCore.Create a
MemoryServiceinstance.Call
AddAsyncwith a memory and a user ID.Call
SearchAsyncwith a query and aMemoryFilterfor that user.
Expected outcome
The service returns matching memory results; the README example prints the retrieved memory text.
Guide limitations
- The default store, extractor and lexical embedding generator are local and deterministic; this recipe does not configure durable vector storage or an external model.
Sources & review
Source record details
- Source availability
- Active
- Sources checked
- 15 October 2026
- Original website title
- jihadkhawaja/magicore · Official homepage title · retained in its source language

