QdrantSkillsMCP 1.4.0

dotnet tool install --global QdrantSkillsMCP --version 1.4.0
                    
This package contains a .NET tool you can call from the shell/command line.
dotnet new tool-manifest
                    
if you are setting up this repo
dotnet tool install --local QdrantSkillsMCP --version 1.4.0
                    
This package contains a .NET tool you can call from the shell/command line.
#tool dotnet:?package=QdrantSkillsMCP&version=1.4.0
                    
nuke :add-package QdrantSkillsMCP --version 1.4.0
                    

QdrantSkillsMCP

A .NET 10 MCP server for vector-based skill storage and retrieval using Qdrant. Enables AI agents (Claude Code, Copilot, Codex, etc.) to semantically search, load, and manage skills via MCP tools.

Prerequisites

Get Started

No install neededdnx runs the tool directly from NuGet, always using the latest version:

# Initialize config (creates ~/.qdrant-skills/config.json with local defaults)
dnx QdrantSkillsMCP -- --config init

# Auto-configure your AI agent (Claude, Copilot, Codex, etc.)
dnx QdrantSkillsMCP -- --setup

# Verify your Qdrant connection
dnx QdrantSkillsMCP -- --config validate

What is dnx? It's .NET 10's equivalent of npx — runs NuGet tools without installing them. Always gets the latest version automatically.

Alternative: Global Install

If you prefer a permanent installation (no dnx prefix needed):

dotnet tool install -g QdrantSkillsMCP
qdrant-skills-mcp --config init
qdrant-skills-mcp --setup

Update later with: dotnet tool update -g QdrantSkillsMCP

Configuration

# Show all config with source annotations ([default], [user], [project], [env])
dnx QdrantSkillsMCP -- --config show

# Connect to a remote Qdrant instance
dnx QdrantSkillsMCP -- --config set QdrantHost=my-qdrant.example.com
dnx QdrantSkillsMCP -- --config set QdrantGrpcPort=6334
dnx QdrantSkillsMCP -- --config set UseTls=true
dnx QdrantSkillsMCP -- --config set QdrantApiKey=your-api-key

# Named profiles for switching between environments
dnx QdrantSkillsMCP -- --config use cloud

# Validate connection works
dnx QdrantSkillsMCP -- --config validate

# Generate env var template for your shell (auto-detects bash/PowerShell/cmd)
dnx QdrantSkillsMCP -- --config env

# Interactive config wizard
dnx QdrantSkillsMCP -- --config

Config files:

  • User-level: ~/.qdrant-skills/config.json (API keys, personal settings)
  • Project-level: ./qdrant-skills.json (shared team settings)
  • Precedence: Environment variables > Project > User > Defaults

CLI Usage

# Search skills by meaning
dnx QdrantSkillsMCP -- --console search "authentication patterns"

# List all skills
dnx QdrantSkillsMCP -- --console list

# JSON output for scripting
dnx QdrantSkillsMCP -- --console --json search "error handling"

# Interactive REPL with tab completion and history
dnx QdrantSkillsMCP -- --console

# Show help
dnx QdrantSkillsMCP -- --console help

MCP Server Mode

By default (no flags), QdrantSkillsMCP runs as an MCP server over stdio. This is how AI agents connect to it. The --setup wizard configures this automatically for your agent.

Available MCP Tools

Tool Description
search-skills Semantic vector search with configurable temperature and max results
load-skill Fetch specific skill(s) by name
add-skill Persist a skill with YAML frontmatter to Qdrant
update-skill Update existing skill content and re-embed
delete-skill Permanently remove a skill
archive-skill Soft-hide a skill without deletion
list-skills List all skills (supports --names and --summaries modes)
reset-session Clear session tracking for loaded skills
get-skill-guide Returns the bundled guide teaching agents how to use QdrantSkillsMCP

ONNX Model Packages

For local embedding without API keys, three pre-built model packages are available:

Package Model Size Quality Dims
QdrantSkillsMCP.Models.MiniLM all-MiniLM-L6-v2 ~23 MB Fastest 384
QdrantSkillsMCP.Models.BgeSmall BGE-small-en-v1.5 ~34 MB Best value 384
QdrantSkillsMCP.Models.BgeBase BGE-base-en-v1.5 ~105 MB Highest quality 768

Without a companion package, the tool auto-downloads all-MiniLM-L6-v2 from HuggingFace on first use (~23 MB, requires internet). This works with no setup.

To pre-install a model, add it to your NuGet global cache (works without a project):

# Create a temp project, restore, then discard — populates the NuGet cache
dotnet new console -o /tmp/model-install --no-restore
dotnet add /tmp/model-install package QdrantSkillsMCP.Models.BgeSmall
dotnet restore /tmp/model-install

The tool auto-detects the model in ~/.nuget/packages/qdrantskillsmcp.models.bgesmall/ on startup.

Then select it:

dnx QdrantSkillsMCP -- --config set OnnxModelName=bge-small-en-v1.5

Embedding Providers

Configure via dnx QdrantSkillsMCP -- --config set EmbeddingProvider=<provider>:

Provider Model Notes
LocalONNX (default) all-MiniLM-L6-v2 Runs locally, no API key needed, 384 dimensions
OpenAI text-embedding-3-small/large Requires OpenAiApiKey or OPENAI_API_KEY env var
Ollama Any Ollama embedding model Set EmbeddingUrl (default: http://localhost:11434)
AzureOpenAI Azure-hosted embeddings Requires endpoint, key, and deployment name

Development

Requires .NET 10 SDK and Docker (for Qdrant via Aspire).

# Run with Aspire (starts Qdrant automatically)
dotnet run --project src/QdrantSkillsMCP.AppHost

# Run unit tests
dotnet test tests/QdrantSkillsMCP.UnitTests

# Run all tests (requires Qdrant running)
dotnet test

License

MIT

Product Compatible and additional computed target framework versions.
.NET net10.0 is compatible.  net10.0-android was computed.  net10.0-browser was computed.  net10.0-ios was computed.  net10.0-maccatalyst was computed.  net10.0-macos was computed.  net10.0-tvos was computed.  net10.0-windows was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

This package has no dependencies.

Version Downloads Last Updated
1.4.0 35 3/30/2026
1.3.1 29 3/30/2026
1.3.0 95 3/28/2026
1.2.0 37 3/28/2026
1.1.0 36 3/28/2026
1.0.1 47 3/28/2026
1.0.0 36 3/28/2026
0.0.0-alpha.0.86 32 3/28/2026