MCP 服务器作为 CrewAI 中的工具

from crewai import Agent

agent = Agent(
    role="Research Analyst",
    goal="Research and analyze information",
    backstory="Expert researcher with access to external tools",
    mcps=[
        "https://mcp.exa.ai/mcp?api_key=your_key",           # External MCP server
        "https://api.weather.com/mcp#get_forecast",          # Specific tool from server
        "snowflake",                                         # Connected MCP from catalog
        "stripe#list_invoices"                               # Specific tool from connected MCP
    ]
)
# MCP tools are now automatically available to your agent!

from crewai import Agent
from crewai.mcp import MCPServerStdio, MCPServerHTTP, MCPServerSSE
from crewai.mcp.filters import create_static_tool_filter

agent = Agent(
    role="Advanced Research Analyst",
    goal="Research with full control over MCP connections",
    backstory="Expert researcher with advanced tool access",
    mcps=[
        # Stdio transport for local servers
        MCPServerStdio(
            command="npx",
            args=["-y", "@modelcontextprotocol/server-filesystem"],
            env={"API_KEY": "your_key"},
            tool_filter=create_static_tool_filter(
                allowed_tool_names=["read_file", "list_directory"]
            ),
            cache_tools_list=True,
        ),
        # HTTP/Streamable HTTP transport for remote servers
        MCPServerHTTP(
            url="https://api.example.com/mcp",
            headers={"Authorization": "Bearer your_token"},
            streamable=True,
            cache_tools_list=True,
        ),
        # SSE transport for real-time streaming
        MCPServerSSE(
            url="https://stream.example.com/mcp/sse",
            headers={"Authorization": "Bearer your_token"},
        ),
    ]
)

# For Simple DSL Integration (Recommended)
uv add mcp

# For Advanced MCPServerAdapter usage
uv pip install 'crewai-tools[mcp]'

from crewai import Agent, Task, Crew

# Create agent with MCP tools using string references
research_agent = Agent(
    role="Research Analyst",
    goal="Find and analyze information using advanced search tools",
    backstory="Expert researcher with access to multiple data sources",
    mcps=[
        "https://mcp.exa.ai/mcp?api_key=your_key&profile=your_profile",
        "snowflake#run_query"
    ]
)

# Create task
research_task = Task(
    description="Research the latest developments in AI agent frameworks",
    expected_output="Comprehensive research report with citations",
    agent=research_agent
)

# Create and run crew
crew = Crew(agents=[research_agent], tasks=[research_task])
result = crew.kickoff()

from crewai import Agent, Task, Crew
from crewai.mcp import MCPServerStdio, MCPServerHTTP, MCPServerSSE

# Create agent with structured MCP configurations
research_agent = Agent(
    role="Research Analyst",
    goal="Find and analyze information using advanced search tools",
    backstory="Expert researcher with access to multiple data sources",
    mcps=[
        # Local stdio server
        MCPServerStdio(
            command="python",
            args=["local_server.py"],
            env={"API_KEY": "your_key"},
        ),
        # Remote HTTP server
        MCPServerHTTP(
            url="https://api.research.com/mcp",
            headers={"Authorization": "Bearer your_token"},
        ),
    ]
)

# Create task
research_task = Task(
    description="Research the latest developments in AI agent frameworks",
    expected_output="Comprehensive research report with citations",
    agent=research_agent
)

# Create and run crew
crew = Crew(agents=[research_agent], tasks=[research_task])
result = crew.kickoff()

mcps=[
    # Full server - get all available tools
    "https://mcp.example.com/api",

    # Specific tool from server using # syntax
    "https://api.weather.com/mcp#get_current_weather",

    # Server with authentication parameters
    "https://mcp.exa.ai/mcp?api_key=your_key&profile=your_profile"
]

mcps=[
    # Connected MCP - get all available tools
    "snowflake",

    # Specific tool from a connected MCP using # syntax
    "stripe#list_invoices",

    # Multiple connected MCPs
    "snowflake",
    "stripe",
    "github"
]

from crewai.mcp import MCPServerStdio
from crewai.mcp.filters import create_static_tool_filter

mcps=[
    MCPServerStdio(
        command="npx",
        args=["-y", "@modelcontextprotocol/server-filesystem"],
        env={"API_KEY": "your_key"},
        tool_filter=create_static_tool_filter(
            allowed_tool_names=["read_file", "write_file"]
        ),
        cache_tools_list=True,
    ),
    # Python-based server
    MCPServerStdio(
        command="python",
        args=["path/to/server.py"],
        env={"UV_PYTHON": "3.12", "API_KEY": "your_key"},
    ),
]

from crewai.mcp import MCPServerHTTP

mcps=[
    # Streamable HTTP (default)
    MCPServerHTTP(
        url="https://api.example.com/mcp",
        headers={"Authorization": "Bearer your_token"},
        streamable=True,
        cache_tools_list=True,
    ),
    # Standard HTTP
    MCPServerHTTP(
        url="https://api.example.com/mcp",
        headers={"Authorization": "Bearer your_token"},
        streamable=False,
    ),
]

from crewai.mcp import MCPServerSSE

mcps=[
    MCPServerSSE(
        url="https://stream.example.com/mcp/sse",
        headers={"Authorization": "Bearer your_token"},
        cache_tools_list=True,
    ),
]

from crewai.mcp import MCPServerStdio, MCPServerHTTP

mcps=[
    # String references
    "https://external-api.com/mcp",              # External server
    "snowflake",                                 # Connected MCP from catalog

    # Structured configurations
    MCPServerStdio(
        command="npx",
        args=["-y", "@modelcontextprotocol/server-filesystem"],
    ),
    MCPServerHTTP(
        url="https://api.example.com/mcp",
        headers={"Authorization": "Bearer token"},
    ),
]

from crewai.mcp import MCPServerStdio
from crewai.mcp.filters import create_static_tool_filter, create_dynamic_tool_filter, ToolFilterContext

# Static filtering (allow/block lists)
static_filter = create_static_tool_filter(
    allowed_tool_names=["read_file", "write_file"],
    blocked_tool_names=["delete_file"],
)

# Dynamic filtering (context-aware)
def dynamic_filter(context: ToolFilterContext, tool: dict) -> bool:
    # Block dangerous tools for certain agent roles
    if context.agent.role == "Code Reviewer":
        if "delete" in tool.get("name", "").lower():
            return False
    return True

mcps=[
    MCPServerStdio(
        command="npx",
        args=["-y", "@modelcontextprotocol/server-filesystem"],
        tool_filter=static_filter,  # or dynamic_filter
    ),
]

from crewai import Agent
from crewai.mcp import MCPServerStdio, MCPServerHTTP

agent = Agent(
    role="Resilient Agent",
    goal="Continue working despite server issues",
    backstory="Agent that handles failures gracefully",
    mcps=[
        # String references
        "https://reliable-server.com/mcp",        # Will work
        "https://unreachable-server.com/mcp",     # Will be skipped gracefully
        "snowflake",                              # Connected MCP from catalog

        # Structured configs
        MCPServerStdio(
            command="python",
            args=["reliable_server.py"],          # Will work
        ),
        MCPServerHTTP(
            url="https://slow-server.com/mcp",     # Will timeout gracefully
        ),
    ]
)
# Agent will use tools from working servers and log warnings for failing ones

# Example with custom connection timeout
with MCPServerAdapter(server_params, connect_timeout=60) as tools:
    # Connection will timeout after 60 seconds if not established
    pass

from crewai import Agent
from crewai_tools import MCPServerAdapter
from mcp import StdioServerParameters # For Stdio Server

# Example server_params (choose one based on your server type):
# 1. Stdio Server:
server_params=StdioServerParameters(
    command="python3",
    args=["servers/your_server.py"],
    env={"UV_PYTHON": "3.12", **os.environ},
)

# 2. SSE Server:
server_params = {
    "url": "https://:8000/sse",
    "transport": "sse"
}

# 3. Streamable HTTP Server:
server_params = {
    "url": "https://:8001/mcp",
    "transport": "streamable-http"
}

# Example usage (uncomment and adapt once server_params is set):
with MCPServerAdapter(server_params, connect_timeout=60) as mcp_tools:
    print(f"Available tools: {[tool.name for tool in mcp_tools]}")

    my_agent = Agent(
        role="MCP Tool User",
        goal="Utilize tools from an MCP server.",
        backstory="I can connect to MCP servers and use their tools.",
        tools=mcp_tools, # Pass the loaded tools to your agent
        reasoning=True,
        verbose=True
    )
    # ... rest of your crew setup ...

with MCPServerAdapter(server_params, connect_timeout=60) as mcp_tools:
    print(f"Available tools: {[tool.name for tool in mcp_tools]}")

    my_agent = Agent(
        role="MCP Tool User",
        goal="Utilize tools from an MCP server.",
        backstory="I can connect to MCP servers and use their tools.",
        tools=[mcp_tools["tool_name"]], # Pass the loaded tools to your agent
        reasoning=True,
        verbose=True
    )
    # ... rest of your crew setup ...

with MCPServerAdapter(server_params, "tool_name", connect_timeout=60) as mcp_tools:
    print(f"Available tools: {[tool.name for tool in mcp_tools]}")

    my_agent = Agent(
        role="MCP Tool User",
        goal="Utilize tools from an MCP server.",
        backstory="I can connect to MCP servers and use their tools.",
        tools=mcp_tools, # Pass the loaded tools to your agent
        reasoning=True,
        verbose=True
    )
    # ... rest of your crew setup ...

@CrewBase
class CrewWithMCP:
  # ... define your agents and tasks config file ...

  mcp_server_params = [
    # Streamable HTTP Server
    {
        "url": "https://:8001/mcp",
        "transport": "streamable-http"
    },
    # SSE Server
    {
        "url": "https://:8000/sse",
        "transport": "sse"
    },
    # StdIO Server
    StdioServerParameters(
        command="python3",
        args=["servers/your_stdio_server.py"],
        env={"UV_PYTHON": "3.12", **os.environ},
    )
  ]

  @agent
  def your_agent(self):
      return Agent(config=self.agents_config["your_agent"], tools=self.get_mcp_tools()) # get all available tools

    # ... rest of your crew setup ...

@CrewBase
class CrewWithMCP:
  mcp_server_params = [...]
  mcp_connect_timeout = 60  # 60 seconds timeout for all MCP connections

  @agent
  def your_agent(self):
      return Agent(config=self.agents_config["your_agent"], tools=self.get_mcp_tools())

@CrewBase
class CrewWithDefaultTimeout:
  mcp_server_params = [...]
  # No mcp_connect_timeout specified - uses default 30 seconds

  @agent
  def your_agent(self):
      return Agent(config=self.agents_config["your_agent"], tools=self.get_mcp_tools())

@agent
def another_agent(self):
    return Agent(
      config=self.agents_config["your_agent"],
      tools=self.get_mcp_tools("tool_1", "tool_2") # get specific tools
    )

@CrewBase
class CrewWithCustomTimeout:
  mcp_server_params = [...]
  mcp_connect_timeout = 90  # 90 seconds timeout for all MCP connections

  @agent
  def filtered_agent(self):
      return Agent(
        config=self.agents_config["your_agent"],
        tools=self.get_mcp_tools("tool_1", "tool_2") # specific tools with custom timeout
      )