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MCP API

Model Context Protocol (MCP) client support. Build MCP server toolsets and attach them to an agent via the mcp_servers parameter of [create_deep_agent][pydantic_deep.agent.create_deep_agent]. See MCP servers for the conceptual overview.

build_mcp_server

::: pydantic_deep.mcp.build_mcp_server options: show_source: false

HttpClientFactory

::: pydantic_deep.mcp.registry.HttpClientFactory options: show_source: false

probe_mcp_server

::: pydantic_deep.mcp.probe_mcp_server options: show_source: false

create_mcp_resources_toolset

Most MCP servers are used for their tools, but a server can also publish resources — docs, templates, or FastMCP skill://.../SKILL.md skills. pydantic-ai surfaces only the tools to the model, so set include_resources=True (or include_skills=True for skills specifically) on an [MCPServerConfig][pydantic_deep.mcp.MCPServerConfig] and build with [MCPRegistry.build_active][pydantic_deep.mcp.MCPRegistry] to attach a second toolset that lets the model discover and read them:

from pydantic_deep.mcp import MCPRegistry, MCPServerConfig

registry = MCPRegistry([
    MCPServerConfig(
        name="service",
        transport="http",
        url="https://example.com/mcp/",
        include_skills=True,  # exposes list_mcp_skills / load_mcp_skill
    ),
])
mcp_servers = registry.build_active()  # tools toolset + resources toolset

The resources toolset adds list_mcp_resources / read_mcp_resource, plus list_mcp_skills / load_mcp_skill when include_skills is set. It binds to the same underlying MCPToolset, so tools and resources share one connection.

Every server's tools carry a prefix, so the example above registers service_list_mcp_skills, service_load_mcp_skill and so on. The prefix is the server's tool_prefix when set, otherwise its name — without it, two servers exposing their resources would register identical tool names and pydantic-ai would reject the collision and fail the run.

With include_skills the toolset also lists the server's skills in the system prompt, so the model knows the guidance exists before it reaches for the server's operational tools rather than having to go looking for it.

A server that is unreachable degrades the same way its tools do: these tools return the error as text instead of raising out of agent.run().

Use create_mcp_resources_toolset directly to wrap a server you built yourself — pass tool_prefix if more than one server will expose its resources.

::: pydantic_deep.mcp.create_mcp_resources_toolset options: show_source: false

builtin_mcp_servers

::: pydantic_deep.mcp.builtin_mcp_servers options: show_source: false

auth_satisfied

::: pydantic_deep.mcp.auth_satisfied options: show_source: false

parse_mcp_servers

::: pydantic_deep.mcp.parse_mcp_servers options: show_source: false

MCPServerConfig

::: pydantic_deep.mcp.MCPServerConfig options: show_source: false

MCPAuth

::: pydantic_deep.mcp.MCPAuth options: show_source: false

MCPRegistry

::: pydantic_deep.mcp.MCPRegistry options: show_source: false

MCPProbeResult

::: pydantic_deep.mcp.MCPProbeResult options: show_source: false

MCPNotInstalledError

::: pydantic_deep.mcp.MCPNotInstalledError options: show_source: false