MCP Prompts

from definable.mcp import MCPClient, MCPConfig, MCPServerConfig

client = MCPClient(config)
await client.connect()

# List prompts from all servers
all_prompts = await client.list_all_prompts()
for server_name, prompts in all_prompts.items():
    print(f"\n{server_name}:")
    for prompt in prompts:
        print(f"  {prompt.name}: {prompt.description}")

result = await client.get_prompt(
    server_name="my-server",
    prompt_name="code_review",
    arguments={"language": "python", "code": "def hello(): print('hi')"},
)

for message in result.messages:
    print(f"[{message.role}] {message.content}")

from definable.mcp import MCPPromptProvider

provider = MCPPromptProvider(client)

# List all prompts
prompts = await provider.list_prompts()

# Get prompt as text
text = await provider.get_text(
    "my-server",
    "code_review",
    arguments={"language": "python", "code": "def hello(): ..."},
)
print(text)

# Get as message list
messages = await provider.get_messages(
    "my-server",
    "code_review",
    arguments={"language": "python", "code": "..."},
)

# Discover prompt arguments
arg_names = await provider.get_prompt_arguments("my-server", "code_review")
print(f"Required arguments: {arg_names}")

# Find which server has a prompt
server = await provider.find_prompt("code_review")

from definable.agents import Agent
from definable.models import OpenAIChat

# Get the prompt text
prompt_text = await provider.get_text(
    "templates",
    "analyze_code",
    arguments={"language": "python"},
)

# Use as agent instructions
agent = Agent(
    model=OpenAIChat(id="gpt-4o"),
    instructions=prompt_text,
)

output = await agent.arun("Review this function: def add(a, b): return a + b")
print(output.content)