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MCP-Based Agent Skills Sample
This sample demonstrates how to discover Agent Skills served over MCP with a ChatClientAgent.
What it demonstrates
- Hosting a small MCP server (in this same executable, launched with
--server) that exposes skill resources following the SEP-2640 convention. - Connecting an
McpClientto the embedded server via stdio transport. - Building an
AgentSkillsProviderviaUseMcpSkills(client), which readsskill://index.json(SEP-2640 canonical discovery) and constructs skills from the index entries. - The progressive disclosure pattern across MCP: advertise → load → read resources, exactly as for filesystem-backed skills.
Running the Sample
Prerequisites
- .NET 10.0 SDK
- Azure OpenAI endpoint with a deployed model
Setup
$env:AZURE_OPENAI_ENDPOINT="https://your-endpoint.openai.azure.com/"
$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-5.4-mini"
Run
dotnet run
Security Considerations
Discovering skills over MCP means an external MCP server controls what skill content (including
instructions and, for archive-type entries, extracted files) reaches the agent. A compromised or
untrustworthy server could return adversarial content designed to manipulate the agent (indirect
prompt injection) or to exfiltrate data through skill instructions/scripts. Only connect UseMcpSkills
to MCP servers you have vetted and trust, and keep the conservative archive size/file-count limits in
AgentMcpSkillsSourceOptions unless you have a specific reason to raise them.