JD.SemanticKernel.Extensions.Mcp 0.1.106

JD.SemanticKernel.Extensions

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An extensible toolkit for Microsoft Semantic Kernel that bridges Claude Code skills, plugins, and hooks into SK applications, and adds context management primitives (compaction, semantic memory) for building production-grade AI agents.

Features

• 📝 Skills — Parse SKILL.md files (YAML frontmatter + markdown) into KernelFunction or PromptTemplate
• 🔗 Hooks — Map Claude Code lifecycle events (PreToolUse, PostToolUse, etc.) to SK's IFunctionInvocationFilter and IPromptRenderFilter
• 📦 Plugins — Load .claude-plugin/ directories with skills, hooks, and MCP configs
• 🔌 MCP — Discover MCP servers from Claude Code, Claude Desktop, VS Code, Codex, Copilot, and JD canonical config with a PatternKit-backed provider chain
• 🗜️ Compaction — Transparent context window management with configurable triggers and hierarchical summarization
• 🧠 Memory — Semantic memory with MMR reranking, temporal decay scoring, and query expansion
• 💾 Memory.Sqlite — SQLite-backed persistent memory storage
• 🎯 Fluent API — UseSkills(), UseHooks(), UsePlugins(), AddCompaction(), AddSemanticMemory() extension methods

Packages

Quick Start

dotnet add package JD.SemanticKernel.Extensions

Load Skills

using JD.SemanticKernel.Extensions.Skills;

var kernel = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion("gpt-4o", apiKey)
 .UseSkills("./skills/") // Scans for SKILL.md files
 .Build();

A SKILL.md file follows the Claude Code / AgentSkills.io format:

---
name: code-reviewer
description: Reviews code for quality issues
allowed-tools: [Read, Grep, Glob]
---
# Code Reviewer

Review the provided code for:
1. Bug risks
2. Security vulnerabilities
3. Performance issues

Input: $ARGUMENTS

Configure Hooks

using JD.SemanticKernel.Extensions.Hooks;

var kernel = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion("gpt-4o", apiKey)
 .UseHooks(hooks =>
 {
 hooks.OnFunctionInvoking("Bash|Execute", async ctx =>
 {
 Console.WriteLine($"Validating: {ctx.Function.Name}");
 });
 hooks.OnFunctionInvoked("Write|Edit", async ctx =>
 {
 Console.WriteLine($"Post-edit hook: {ctx.Function.Name}");
 });
 hooks.OnPromptRendering(async ctx =>
 {
 Console.WriteLine("Prompt is about to render...");
 });
 })
 .Build();

Load Plugins

using JD.SemanticKernel.Extensions.Plugins;

var kernel = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion("gpt-4o", apiKey)
 .UsePlugins("./my-plugin/") // Single plugin directory
 .UseAllPlugins("./plugins/") // All plugins in directory
 .Build();

Plugin directories follow the .claude-plugin/ convention:

my-plugin/
├── .claude-plugin/
│ └── plugin.json # Manifest
├── skills/
│ └── reviewer/SKILL.md # Skills
├── hooks/
│ └── hooks.json # Hooks
└── .mcp.json # MCP servers (future)

Meta-Package (All-in-One)

using JD.SemanticKernel.Extensions;

var kernel = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion("gpt-4o", apiKey)
 .AddClaudeCodeSkills("./skills/")
 .AddClaudeCodePlugin("./my-plugin/")
 .AddClaudeCodeHooks(hooks => hooks.OnFunctionInvoking(".*", _ => Task.CompletedTask))
 .Build();

Context Compaction

Automatically compress chat history when it grows too large, preserving key context while staying within token limits.

using JD.SemanticKernel.Extensions.Compaction;

var kernel = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion("gpt-4o", apiKey)
 .Build();

// Register compaction as transparent middleware
kernel.Services.AddCompaction(options =>
{
 options.TriggerMode = CompactionTriggerMode.ContextPercentage;
 options.Threshold = 0.70; // Compact at 70% of context window
 options.MaxContextWindowTokens = 128_000; // Model's context limit
 options.PreserveLastMessages = 10; // Always keep recent messages
 options.MinMessagesBeforeCompaction = 5; // Don't compact short conversations
});

Trigger modes:

• TokenThreshold — Compact when estimated tokens exceed an absolute count
• ContextPercentage — Compact when usage exceeds a percentage of the context window

Token estimation:

var tokens = TokenEstimator.EstimateTokens("Hello world"); // ~2 tokens
var historyTokens = TokenEstimator.EstimateTokens(chatHistory); // Includes overhead

Semantic Memory

Store, search, and retrieve context-relevant information with embedding-based similarity, MMR diversity reranking, and temporal decay scoring.

using JD.SemanticKernel.Extensions.Memory;

// Register with in-memory backend
kernel.Services.AddSemanticMemory(options =>
{
 options.DefaultSearchOptions = new MemorySearchOptions
 {
 TopK = 10,
 MinRelevanceScore = 0.7,
 UseMmrReranking = true,
 MmrLambda = 0.7, // Balance relevance vs diversity
 UseTemporalDecay = true,
 TemporalDecayRate = 0.01,
 };
});

SQLite persistence:

using JD.SemanticKernel.Extensions.Memory.Sqlite;

kernel.Services.AddSqliteMemoryBackend("Data Source=memory.db");

Key capabilities:

• MMR reranking — Maximal Marginal Relevance for diverse search results
• Temporal decay — Recent memories rank higher with configurable decay rate
• Query expansion — Automatically generate alternative queries for broader recall
• Pluggable backends — InMemoryBackend (default), SqliteMemoryBackend, or implement IMemoryBackend

Hook Event Mapping

Related Projects

Building

dotnet restore
dotnet build
dotnet test

License

© JD