Eduard van Valkenburg
c91b88f217
* feat(python): add agent-framework-hosting-mcp channel Add a hosting channel that exposes the host target (agent or workflow) as a single Model Context Protocol tool over Streamable HTTP. The tool invocation routes through the host pipeline (ChannelContext.run/ run_stream) so sessions, linking, and run/response hooks apply. Maps the MCP request context to a ChannelSession isolation key and ChannelIdentity, and forwards streaming output as MCP progress notifications. Includes tests, README, and workspace registration. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Address MCP hosting channel review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
agent-framework-hosting-mcp
Model Context Protocol (MCP) tool channel for agent-framework-hosting.
Exposes the hosted target (an Agent or a Workflow) as a single MCP tool over
the Streamable-HTTP transport, so MCP clients — other agents, IDE tooling — can
invoke it. Every call is routed through the host pipeline, so host sessions,
request metadata, and run/response hooks all apply.
from agent_framework.openai import OpenAIChatClient
from agent_framework_hosting import AgentFrameworkHost
from agent_framework_hosting_mcp import MCPChannel
agent = OpenAIChatClient().as_agent(name="Assistant")
host = AgentFrameworkHost(target=agent, channels=[MCPChannel()])
host.serve(port=8000)
The Streamable-HTTP endpoint is mounted at path (default /mcp). The advertised
tool accepts {"input": str, "session_id": str?} and returns the target's reply
as MCP content blocks, including structured output when the agent returns one.
Pass session_id to continue a prior conversation (it maps onto the host
session). When streaming=True (default) incremental text is forwarded as MCP
progress notifications while the full reply is returned as the tool result.
The base host plumbing lives in
agent-framework-hosting.