PYPI Agents

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-level agent orchestration framework Integrations — Chat & embedding models, tools & toolkits, and more LangSmith — Agent evals, observability, and debugging for LLM apps LangSmith Deployment — Deploy and scale agents...

ditorconfig .gitattributes .gitattributes .gitignore .gitignore .markdownlint.json .markdownlint.json .mcp.json .mcp.json .pre-commit-config.yaml .pre-commit-config.yaml AGENTS.md AGENTS.md CITATION.cff CITATION.cff C...

ate with the latest AI developments through an active open-source community Flexible abstraction layers — Work at the level of abstraction that suits your needs — from high-level chains for quick starts to low-level c...

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d langchain from langchain . chat_models import init_chat_model model = init_chat_model ( "openai:gpt-5.4" ) result = model . invoke ( "Hello, world!" ) If you're looking for more advanced customization or agent orche...

your application's needs. As the industry frontier evolves, adapt quickly — LangChain's abstractions keep you moving without losing momentum Rapid prototyping — Quickly build and iterate on LLM applications with LangC...

it process_with_context ( x , ctx ) Context Properties and Methods The Context object provides the following capabilities: ctx.request_id - Unique ID for the current request ctx.client_id - Client ID if available ctx....

custom level await ctx.report_progress(progress, total=None, message=None) - Report operation progress await ctx.read_resource(uri) - Read a resource by URI await ctx.elicit(message, schema) - Request additional infor...

tuple, Union, Optional, etc.) - wrapped in {"result": value} Classes without type hints cannot be serialized for structured output. Only classes with properly annotated attributes will be converted to Pydantic models...

0 )) return Image ( data = img . tobytes (), format = "png" ) Full example: examples/snippets/servers/images.py Context The Context object is automatically injected into tool and resource functions that request it via...

nt ] @ mcp . tool () def advanced_tool () -> CallToolResult : """Return CallToolResult directly for full control including _meta field.""" return CallToolResult ( content = [ TextContent ( type = "text" , text = "Resp...

th empty content.""" return CallToolResult ( content = []) Full example: examples/snippets/servers/direct_call_tool_result.py Important: CallToolResult must always be returned (no Optional or Union ). For empty result...

" , ) await ctx . debug ( f"Completed step { i + 1 } " ) return f"Task ' { task_name } ' completed" Full example: examples/snippets/servers/tool_progress.py Completions MCP supports providing completion suggestions fo...

he server args = [ "run" , "server" , "completion" , "stdio" ], # Server with completion support env = { "UV_INDEX" : os . environ . get ( "UV_INDEX" , "" )}, ) async def run (): """Run the completion client example."...

name } " ) # Complete resource template arguments if templates . resourceTemplates : template = templates . resourceTemplates [ 0 ] print ( f" \n Completing arguments for resource template: { template . uriTemplate }...

ner" : "modelcontextprotocol" }, ) print ( f"Completions for 'repo' with owner='modelcontextprotocol': { result . completion . values } " ) # Complete prompt arguments if prompts . prompts : prompt_name = prompts . pr...

n" : 40.0 , "std_dev" : 5.2 } # Ordinary classes with type hints work for structured output class UserProfile : name : str age : int email : str | None = None def __init__ ( self , name : str , age : int , email : str...

" ) condition : str wind_speed : float @ mcp . tool () def get_weather ( city : str ) -> WeatherData : """Get weather for a city - returns structured data.""" # Simulated weather data return WeatherData ( temperature...

ns unstructured output - no schema generated""" return UntypedConfig ( "value1" , "value2" ) # Lists and other types are wrapped automatically @ mcp . tool () def list_cities () -> list [ str ]: """Get a list of citie...

ew" ) def review_code ( code : str ) -> str : return f"Please review this code: \n \n { code } " @ mcp . prompt ( title = "Debug Assistant" ) def debug_error ( error : str ) -> list [ base . Message ]: return [ base ....

website_url = "https://example.com" , icons = [ icon ] ) # Add icons to tools, resources, and prompts @ mcp . tool ( icons = [ icon ]) def my_tool (): """Tool with an icon.""" return "result" @ mcp . resource ( "demo:...

annotation causes the tool to be classified as structured and this is undesirable , the classification can be suppressed by passing structured_output=False to the @tool decorator. Advanced: Direct CallToolResult For f...

ments/{name}" ) def read_document ( name : str ) -> str : """Read a document by name.""" # This would normally read from disk return f"Content of { name } " @ mcp . resource ( "config://settings" ) def get_settings ()...

str : """Get weather for a city.""" # This would normally call a weather API return f"Weather in { city } : 22degrees { unit [ 0 ]. upper () } " Full example: examples/snippets/servers/basic_tool.py Tools can optional...

or i in range ( steps ): progress = ( i + 1 ) / steps await ctx . report_progress ( progress = progress , total = 1.0 , message = f"Step { i + 1 } / { steps } " , ) await ctx . debug ( f"Completed step { i + 1 } " ) r...

: yield AppContext ( db = db ) finally : # Cleanup on shutdown await db . disconnect () # Pass lifespan to server mcp = FastMCP ( "My App" , lifespan = app_lifespan ) # Access type-safe lifespan context in tools @ mcp...

, and Streamable HTTP Handle all MCP protocol messages and lifecycle events Installation Adding MCP to your python project We recommend using uv to manage your Python projects. If you haven't created a uv-managed proj...

CP server mcp = FastMCP ( "Demo" , json_response = True ) # Add an addition tool @ mcp . tool () def add ( a : int , b : int ) -> int : """Add two numbers""" return a + b # Add a dynamic greeting resource @ mcp . reso...

P transport if __name__ == "__main__" : mcp . run ( transport = "streamable-http" ) Full example: examples/snippets/servers/fastmcp_quickstart.py You can install this server in Claude Code and interact with it right a...

it like a web API, but specifically designed for LLM interactions. MCP servers can: Expose data through Resources (think of these sort of like GET endpoints; they are used to load information into the LLM's context) P...

aclasses import dataclass from mcp . server . fastmcp import Context , FastMCP from mcp . server . session import ServerSession # Mock database class for example class Database : """Mock database class for example."""...

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