roji · May 1, 2026 · Apr 28, 2026 · May 1, 2026
diff --git a/Directory.Build.props b/Directory.Build.props
@@ -16,9 +16,18 @@
     <DebugType>embedded</DebugType>
   </PropertyGroup>
 
-  <ItemGroup Condition="'$(IsPackable)' == 'true'">
-    <PackageReference Include="Microsoft.SourceLink.GitHub" PrivateAssets="all" IncludeAssets="runtime; build; native; contentfiles; analyzers" />
-  </ItemGroup>
+  <PropertyGroup>
+    <Authors>Microsoft.Toolkit,dotnetfoundation,Community Toolkit</Authors>
+    <Company>.NET Foundation</Company>
+    <Copyright>(c) .NET Foundation and Contributors. All rights reserved.</Copyright>
+    <PackageLicenseExpression>MIT</PackageLicenseExpression>
+    <PackageProjectUrl>https://github.com/CommunityToolkit/AI</PackageProjectUrl>
+    <RepositoryUrl>https://github.com/CommunityToolkit/AI</RepositoryUrl>
+    <PublishRepositoryUrl>true</PublishRepositoryUrl>
+    <PackageRequireLicenseAcceptance>true</PackageRequireLicenseAcceptance>
+    <PackageReadmeFile>README.md</PackageReadmeFile>
+  </PropertyGroup>
+
 
   <Import Project="$(MSBuildThisFileDirectory)eng/LegacySupport.props" />
 

diff --git a/Directory.Build.targets b/Directory.Build.targets
@@ -0,0 +1,8 @@
+<Project>
+
+  <ItemGroup Condition="'$(IsPackable)' == 'true'">
+    <PackageReference Include="Microsoft.SourceLink.GitHub" PrivateAssets="all" IncludeAssets="runtime; build; native; contentfiles; analyzers" />
+    <None Include="README.md" Pack="true" PackagePath="" />
+  </ItemGroup>
+
+</Project>
diff --git a/MEVD/src/AzureAISearch/AzureAISearch.csproj b/MEVD/src/AzureAISearch/AzureAISearch.csproj
@@ -1,12 +1,12 @@
 <Project Sdk="Microsoft.NET.Sdk">
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.AzureAISearch</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
 
     <Title>Azure AI Search provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Azure AI Search provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Azure AI Search provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/AzureAISearch/AzureAISearchCollection.cs b/MEVD/src/AzureAISearch/AzureAISearchCollection.cs
@@ -404,7 +404,7 @@ floatVector is null
         {
             // Azure AI Search threshold filtering is in preview:
             // https://learn.microsoft.com/azure/search/vector-search-how-to-query#set-thresholds-to-exclude-low-scoring-results-preview
-            // See https://github.com/microsoft/semantic-kernel/issues/13500.
+            // See https://github.com/CommunityToolkit/AI/issues/5.
             // For now, perform post-filtering on the client-side.
             if (options.ScoreThreshold.HasValue && record.Score < options.ScoreThreshold.Value)
             {

diff --git a/MEVD/src/AzureAISearch/AzureAISearchDynamicMapper.cs b/MEVD/src/AzureAISearch/AzureAISearchDynamicMapper.cs
@@ -12,7 +12,7 @@
 namespace CommunityToolkit.VectorData.AzureAISearch;
 
 /// <summary>
-/// A mapper that maps between the generic Semantic Kernel data model and the model that the data is stored under, within Azure AI Search.
+/// A mapper that maps between the generic data model and the model that the data is stored under, within Azure AI Search.
 /// </summary>
 internal sealed class AzureAISearchDynamicMapper(CollectionModel model, JsonSerializerOptions? jsonSerializerOptions) : IAzureAISearchMapper<Dictionary<string, object?>>
 {

diff --git a/MEVD/src/AzureAISearch/AzureAISearchModelBuilder.cs b/MEVD/src/AzureAISearch/AzureAISearchModelBuilder.cs
@@ -73,7 +73,7 @@ internal static bool IsVectorPropertyTypeValidCore(Type type, [NotNullWhen(false
     {
         // Azure AI Search is adding support for more types than just float32, but these are not available for use via the
         // SDK yet. We will update this list as the SDK is updated.
-        // <see href="https://learn.microsoft.com/en-us/rest/api/searchservice/supported-data-types#edm-data-types-for-vector-fields"/>
+        // <see href="https://learn.microsoft.com/rest/api/searchservice/supported-data-types#edm-data-types-for-vector-fields"/>
         supportedTypes = SupportedVectorTypes;
 
         return type == typeof(ReadOnlyMemory<float>)

diff --git a/MEVD/src/AzureAISearch/README.md b/MEVD/src/AzureAISearch/README.md
@@ -0,0 +1,17 @@
+# CommunityToolkit.VectorData.AzureAISearch
+
+Azure AI Search provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+[Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) is a cloud search service that provides vector similarity search, full-text search, and hybrid search capabilities.
+
+## Quick start
+
+1. Create an Azure AI Search instance via the [Azure portal](https://learn.microsoft.com/azure/search/search-create-service-portal) or [Azure CLI](https://learn.microsoft.com/azure/search/search-manage-azure-cli).
+
+2. Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.AzureAISearch
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/CosmosMongoDB/CosmosMongoCollectionCreateMapping.cs b/MEVD/src/CosmosMongoDB/CosmosMongoCollectionCreateMapping.cs
@@ -104,7 +104,7 @@ public static BsonArray GetFilterableDataIndexes(
     }
 
     /// <summary>
-    /// More information about Azure CosmosDB for MongoDB index kinds here: <see href="https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/vector-search" />.
+    /// More information about Azure CosmosDB for MongoDB index kinds here: <see href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/vector-search" />.
     /// </summary>
     private static string GetIndexKind(string? indexKind, string vectorPropertyName)
         => CosmosMongoCollectionSearchMapping.GetVectorPropertyIndexKind(indexKind) switch
@@ -115,7 +115,7 @@ private static string GetIndexKind(string? indexKind, string vectorPropertyName)
         };
 
     /// <summary>
-    /// More information about Azure CosmosDB for MongoDB distance functions here: <see href="https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/vector-search" />.
+    /// More information about Azure CosmosDB for MongoDB distance functions here: <see href="https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/vector-search" />.
     /// </summary>
     private static string GetDistanceFunction(string? distanceFunction, string vectorPropertyName)
         => CosmosMongoCollectionSearchMapping.GetVectorPropertyDistanceFunction(distanceFunction) switch

diff --git a/MEVD/src/CosmosMongoDB/CosmosMongoDB.csproj b/MEVD/src/CosmosMongoDB/CosmosMongoDB.csproj
@@ -1,14 +1,14 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.CosmosMongoDB</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.1;net472</TargetFrameworks>
     <IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net8.0'))">true</IsAotCompatible>
 
     <Title>Azure CosmosDB MongoDB vCore provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Azure CosmosDB MongoDB vCore provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Azure CosmosDB MongoDB vCore provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/CosmosMongoDB/MongoShared/README.md b/MEVD/src/CosmosMongoDB/MongoShared/README.md
@@ -1,5 +1,5 @@
 # MongoShared
 
-These files are shared utilities that are identical across the Cosmos MongoDB and the regular MongoDB vector store providers. They were originally shared via linked compilation in the Semantic Kernel repository.
+These files are shared utilities that are identical across the Cosmos MongoDB and the regular MongoDB vector store providers.
 
 If a regular MongoDB provider is added in the future, these files should be extracted to a shared location and linked into both projects.
diff --git a/MEVD/src/CosmosMongoDB/README.md b/MEVD/src/CosmosMongoDB/README.md
@@ -0,0 +1,17 @@
+# CommunityToolkit.VectorData.CosmosMongoDB
+
+Azure Cosmos DB for MongoDB (vCore) provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+[Azure Cosmos DB for MongoDB vCore](https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/) supports native vector search, enabling AI-powered applications with vector similarity search capabilities.
+
+## Quick start
+
+1. Create an Azure Cosmos DB for MongoDB vCore instance via the [Azure portal](https://learn.microsoft.com/azure/cosmos-db/mongodb/vcore/quickstart-portal).
+
+2. Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.CosmosMongoDB
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/InMemory/InMemory.csproj b/MEVD/src/InMemory/InMemory.csproj
@@ -1,12 +1,12 @@
 <Project Sdk="Microsoft.NET.Sdk">
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.InMemory</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
 
     <Title>In-Memory provider for Microsoft.Extensions.VectorData</Title>
-    <Description>In-Memory provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>In-Memory provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/InMemory/InMemoryServiceCollectionExtensions.cs b/MEVD/src/InMemory/InMemoryServiceCollectionExtensions.cs
@@ -7,7 +7,7 @@
 using Microsoft.Extensions.VectorData;
 using CommunityToolkit.VectorData.InMemory;
 
-namespace Microsoft.SemanticKernel;
+namespace Microsoft.Extensions.DependencyInjection;
 
 /// <summary>
 /// Extension methods to register Data services on an <see cref="IServiceCollection"/>.

diff --git a/MEVD/src/InMemory/README.md b/MEVD/src/InMemory/README.md
@@ -0,0 +1,15 @@
+# CommunityToolkit.VectorData.InMemory
+
+In-memory provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+This provider stores vector data in memory and is useful for testing, prototyping, and scenarios where persistence is not required.
+
+## Quick start
+
+Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.InMemory
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/PgVector/PgVector.csproj b/MEVD/src/PgVector/PgVector.csproj
@@ -1,15 +1,15 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.PgVector</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
     <IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net8.0'))">true</IsAotCompatible>
     <NoWarn>$(NoWarn);CS0436</NoWarn>
 
     <Title>Postgres provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Postgres (with pgvector extension) provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Postgres (with pgvector extension) provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/PgVector/README.md b/MEVD/src/PgVector/README.md
@@ -1,4 +1,4 @@
-# Microsoft.SemanticKernel.Connectors.Postgres
+# CommunityToolkit.VectorData.PgVector
 
 This connector uses Postgres to implement Semantic Memory. It requires the [pgvector](https://github.com/pgvector/pgvector) extension to be installed on Postgres to implement vector similarity search.
 
@@ -10,8 +10,8 @@ How to install the pgvector extension, please refer to its [documentation](https
 
 This extension is also available for **Azure Database for PostgreSQL - Flexible Server** and **Azure Cosmos DB for PostgreSQL**.
 
-- [Azure Database for Postgres](https://learn.microsoft.com/en-us/azure/postgresql/flexible-server/how-to-use-pgvector)
-- [Azure Cosmos DB for PostgreSQL](https://learn.microsoft.com/en-us/azure/cosmos-db/postgresql/howto-use-pgvector)
+- [Azure Database for Postgres](https://learn.microsoft.com/azure/postgresql/flexible-server/how-to-use-pgvector)
+- [Azure Cosmos DB for PostgreSQL](https://learn.microsoft.com/azure/cosmos-db/postgresql/howto-use-pgvector)
 
 ## Quick start
 
@@ -33,10 +33,6 @@ sk_demo=# CREATE EXTENSION vector;
 
 > Note, "Azure Cosmos DB for PostgreSQL" uses `SELECT CREATE_EXTENSION('vector');` to enable the extension.
 
-### Using PostgresVectorStore
 
-See [this sample](../../../samples/Concepts/Memory/VectorStore_VectorSearch_MultiStore_Postgres.cs) for an example of using the vector store.
 
-For more information on using Postgres as a vector store, see the [PostgresVectorStore](https://learn.microsoft.com/semantic-kernel/concepts/vector-store-connectors/out-of-the-box-connectors/postgres-connector) documentation.
-
-Use the [getting started instructions](https://learn.microsoft.com/semantic-kernel/concepts/vector-store-connectors/?pivots=programming-language-csharp#getting-started-with-vector-store-connectors) on the Microsoft Leearn site to learn more about using the vector store.
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/Pinecone/Pinecone.csproj b/MEVD/src/Pinecone/Pinecone.csproj
@@ -1,14 +1,14 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.Pinecone</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
     <IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net8.0'))">true</IsAotCompatible>
 
     <Title>Pinecone provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Pinecone provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Pinecone provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/Pinecone/README.md b/MEVD/src/Pinecone/README.md
@@ -0,0 +1,17 @@
+# CommunityToolkit.VectorData.Pinecone
+
+Pinecone provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+[Pinecone](https://www.pinecone.io/) is a managed vector database designed for high-performance vector similarity search at scale.
+
+## Quick start
+
+1. Create a Pinecone account and index at [pinecone.io](https://www.pinecone.io/).
+
+2. Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.Pinecone
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/Qdrant/Qdrant.csproj b/MEVD/src/Qdrant/Qdrant.csproj
@@ -1,14 +1,14 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.Qdrant</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
     <IsAotCompatible Condition="$([MSBuild]::IsTargetFrameworkCompatible('$(TargetFramework)', 'net8.0'))">true</IsAotCompatible>
 
     <Title>Qdrant provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Qdrant provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Qdrant provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/Qdrant/README.md b/MEVD/src/Qdrant/README.md
@@ -0,0 +1,21 @@
+# CommunityToolkit.VectorData.Qdrant
+
+Qdrant provider for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+[Qdrant](https://qdrant.tech/) is an open-source vector similarity search engine that provides fast and scalable vector search with filtering support.
+
+## Quick start
+
+1. Run Qdrant with Docker:
+
+```bash
+docker run -d --name qdrant -p 6333:6333 -p 6334:6334 qdrant/qdrant
+```
+
+2. Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.Qdrant
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/Redis/README.md b/MEVD/src/Redis/README.md
@@ -1,4 +1,4 @@
-# Microsoft.SemanticKernel.Connectors.Redis
+# CommunityToolkit.VectorData.Redis
 
 This connector uses Redis to implement Semantic Memory. It requires the [RediSearch](https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/) module to be enabled on Redis to implement vector similarity search.
 
@@ -12,7 +12,7 @@ Ways to get RediSearch:
 
 1. Set up the RediSearch on your self-managed Redis, please refer to its [documentation](https://redis.io/docs/latest/develop/interact/search-and-query/advanced-concepts/vectors/).
 
-1. Use the [Redis Enterprise](https://redis.io/docs/latest/operate/rs/), see [Azure Marketplace](https://azuremarketplace.microsoft.com/en-us/marketplace/apps/garantiadata.redis_enterprise_1sp_public_preview?tab=Overview), [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-e6y7ork67pjwg?sr=0-2&ref_=beagle&applicationId=AWSMPContessa), or [Google Marketplace](https://console.cloud.google.com/marketplace/details/redislabs-public/redis-enterprise?pli=1).
+1. Use the [Redis Enterprise](https://redis.io/docs/latest/operate/rs/), see [Azure Marketplace](https://azuremarketplace.microsoft.com/marketplace/apps/garantiadata.redis_enterprise_1sp_public_preview?tab=Overview), [AWS Marketplace](https://aws.amazon.com/marketplace/pp/prodview-e6y7ork67pjwg?sr=0-2&ref_=beagle&applicationId=AWSMPContessa), or [Google Marketplace](https://console.cloud.google.com/marketplace/details/redislabs-public/redis-enterprise?pli=1).
 
 ## Quick start
 
@@ -22,6 +22,10 @@ Ways to get RediSearch:
 docker run -d --name redis-stack-server -p 6379:6379 redis/redis-stack-server:latest
 ```
 
-2. Create a Redis Vector Store using instructions on the [Microsoft Learn site](https://learn.microsoft.com/semantic-kernel/concepts/vector-store-connectors/out-of-the-box-connectors/redis-connector).
+2. Install the NuGet package:
 
-3. Use the [getting started instructions](https://learn.microsoft.com/semantic-kernel/concepts/vector-store-connectors/?pivots=programming-language-csharp#getting-started-with-vector-store-connectors) on the Microsoft Leearn site to learn more about using the vector store.
+```bash
+dotnet add package CommunityToolkit.VectorData.Redis
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).
diff --git a/MEVD/src/Redis/Redis.csproj b/MEVD/src/Redis/Redis.csproj
@@ -1,13 +1,13 @@
 <Project Sdk="Microsoft.NET.Sdk">
 
   <PropertyGroup>
-    <Version>1.0.0-preview.1</Version>
+    <Version>1.0.0-preview.2</Version>
     <AssemblyName>CommunityToolkit.VectorData.Redis</AssemblyName>
     <RootNamespace>$(AssemblyName)</RootNamespace>
     <TargetFrameworks>net10.0;net8.0;netstandard2.0;net462</TargetFrameworks>
 
     <Title>Redis provider for Microsoft.Extensions.VectorData</Title>
-    <Description>Redis provider for Microsoft.Extensions.VectorData by Semantic Kernel</Description>
+    <Description>Redis provider for Microsoft.Extensions.VectorData by the .NET Community Toolkit</Description>
   </PropertyGroup>
 
   <ItemGroup>

diff --git a/MEVD/src/Redis/RedisJsonDynamicMapper.cs b/MEVD/src/Redis/RedisJsonDynamicMapper.cs
@@ -10,7 +10,7 @@
 namespace CommunityToolkit.VectorData.Redis;
 
 /// <summary>
-/// A mapper that maps between the generic Semantic Kernel data model and the model that the data is stored under, within Redis when using JSON.
+/// A mapper that maps between the generic data model and the model that the data is stored under, within Redis when using JSON.
 /// </summary>
 internal class RedisJsonDynamicMapper(CollectionModel model, JsonSerializerOptions jsonSerializerOptions) : IRedisJsonMapper<Dictionary<string, object?>>
 {

diff --git a/MEVD/src/SqliteVec/README.md b/MEVD/src/SqliteVec/README.md
@@ -0,0 +1,15 @@
+# CommunityToolkit.VectorData.SqliteVec
+
+SQLite provider (with [sqlite-vec](https://github.com/asg017/sqlite-vec) extension) for [Microsoft.Extensions.VectorData](https://learn.microsoft.com/dotnet/ai/vector-stores/overview), by the .NET Community Toolkit.
+
+[sqlite-vec](https://github.com/asg017/sqlite-vec) is a SQLite extension for vector search, providing efficient similarity search capabilities in a lightweight, embedded database.
+
+## Quick start
+
+Install the NuGet package:
+
+```bash
+dotnet add package CommunityToolkit.VectorData.SqliteVec
+```
+
+For more information, see the [Microsoft.Extensions.VectorData documentation](https://learn.microsoft.com/dotnet/ai/vector-stores/overview).