chore: import upstream snapshot with attribution
dotnet-build-and-test / dotnet-test-functions (push) Has been cancelled
dotnet-build-and-test / paths-filter (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Debug, windows-latest, net9.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, ubuntu-latest, net10.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, ubuntu-latest, net8.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-build (Release, windows-latest, net472) (push) Has been cancelled
dotnet-build-and-test / dotnet-test (Release, integration, true, ubuntu-latest, net10.0) (push) Has been cancelled
dotnet-build-and-test / dotnet-test (Release, integration, true, windows-latest, net472) (push) Has been cancelled
dotnet-build-and-test / dotnet-foundry-hosted-it (push) Has been cancelled
dotnet-build-and-test / dotnet-build-and-test-check (push) Has been cancelled
dotnet-build-and-test / Integration Test Report (push) Has been cancelled
CodeQL / Analyze (csharp) (push) Has been cancelled
CodeQL / Analyze (python) (push) Has been cancelled

This commit is contained in:
wehub-resource-sync
2026-07-13 13:39:25 +08:00
commit db620d33df
5151 changed files with 925932 additions and 0 deletions
@@ -0,0 +1,61 @@
# MCP-Based Agent Skills Sample
This sample demonstrates how to discover **Agent Skills served over MCP** with an `Agent`.
## What it demonstrates
- Connecting to a remote MCP server (over streamable HTTP) that exposes skill
resources following the SEP-2640 convention.
- Building a `SkillsProvider` from an `MCPSkillsSource`, which reads
`skill://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
- Python 3.10+
- An [Azure AI Foundry](https://ai.azure.com/) project with a deployed model
- Azure CLI authentication (`az login`)
- A running MCP server that hosts SEP-2640 skill resources (see "Providing
an MCP server" below)
### Setup
Set the following environment variables (in a `.env` file or your shell):
```powershell
$env:FOUNDRY_PROJECT_ENDPOINT="https://your-endpoint.services.ai.azure.com/api/projects/your-project"
$env:FOUNDRY_MODEL="gpt-4o-mini"
$env:MCP_SKILLS_SERVER_URL="https://your-mcp-server.example.com/mcp"
```
### Run
```powershell
python mcp_based_skill.py
```
## Providing an MCP server
This sample is a **consumer**: it does not host an MCP server itself. To try
it end-to-end you need an MCP server that exposes the SEP-2640 skill
resources (`skill://index.json` plus per-skill `SKILL.md`).
- See [`samples/02-agents/mcp/agent_as_mcp_server.py`](../../mcp/agent_as_mcp_server.py)
for an example of hosting an MCP server via the Agent Framework.
- The Model Context Protocol working group maintains reference MCP-skills
servers at
[`modelcontextprotocol/experimental-ext-skills`](https://github.com/modelcontextprotocol/experimental-ext-skills).
## Security Considerations
Discovering skills over MCP means an *external* MCP server controls what skill content
(including instructions and, for script-capable skills, the scripts the agent may run)
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. This source is never enabled by default — connecting
`MCPSkillsSource` to a server is an explicit opt-in. Only connect to MCP servers you have
vetted and trust, and treat their responses as untrusted input.