diff --git a/cognee-mcp/src/__init__.py b/cognee-mcp/src/__init__.py index 3081d5c2..1939efe9 100644 --- a/cognee-mcp/src/__init__.py +++ b/cognee-mcp/src/__init__.py @@ -1,6 +1,8 @@ -from .server import mcp +from .server import main as server_main def main(): """Main entry point for the package.""" - mcp.run(transport="stdio") + import asyncio + + asyncio.run(server_main()) diff --git a/cognee-mcp/src/client.py b/cognee-mcp/src/client.py old mode 100644 new mode 100755 index 202b109f..46218e1a --- a/cognee-mcp/src/client.py +++ b/cognee-mcp/src/client.py @@ -4,8 +4,8 @@ # Create server parameters for stdio connection server_params = StdioServerParameters( - command="mcp", # Executable - args=["run", "src/server.py"], # Optional command line arguments + command="uv", # Executable + args=["--directory", ".", "run", "cognee"], # Optional command line arguments env=None, # Optional environment variables ) @@ -33,10 +33,15 @@ async def run(): async with ClientSession(read, write, timedelta(minutes=3)) as session: await session.initialize() + toolResult = await session.list_tools() + + toolResult = await session.call_tool("prune", arguments={}) + toolResult = await session.call_tool("cognify", arguments={"text": text}) - # toolResult = await session.call_tool("search", arguments={"search_query": "AI"}) - print(f"Cognify result: {toolResult}") + toolResult = await session.call_tool("search", arguments={"search_query": "AI"}) + + print(f"Cognify result: {toolResult.content}") if __name__ == "__main__": diff --git a/cognee-mcp/src/server.py b/cognee-mcp/src/server.py old mode 100644 new mode 100755 index ed603feb..4cc7440f --- a/cognee-mcp/src/server.py +++ b/cognee-mcp/src/server.py @@ -1,16 +1,97 @@ import os import cognee +import logging import importlib.util +from contextlib import redirect_stderr, redirect_stdout # from PIL import Image as PILImage -from mcp.server.fastmcp import FastMCP +import mcp.types as types +from mcp.server import Server, NotificationOptions +from mcp.server.models import InitializationOptions from cognee.api.v1.search import SearchType from cognee.shared.data_models import KnowledgeGraph -mcp = FastMCP("cognee", timeout=120000) +mcp = Server("cognee") + +logger = logging.getLogger(__name__) + + +@mcp.list_tools() +async def list_tools() -> list[types.Tool]: + return [ + types.Tool( + name="cognify", + description="Cognifies text into knowledge graph", + inputSchema={ + "type": "object", + "properties": { + "text": { + "type": "string", + "description": "The text to cognify", + }, + "graph_model_file": { + "type": "string", + "description": "The path to the graph model file", + }, + "graph_model_name": { + "type": "string", + "description": "The name of the graph model", + }, + }, + "required": ["text"], + }, + ), + types.Tool( + name="search", + description="Searches for information in knowledge graph", + inputSchema={ + "type": "object", + "properties": { + "search_query": { + "type": "string", + "description": "The query to search for", + }, + }, + "required": ["search_query"], + }, + ), + types.Tool( + name="prune", + description="Prunes knowledge graph", + inputSchema={ + "type": "object", + "properties": {}, + }, + ), + ] + + +@mcp.call_tool() +async def call_tools(name: str, arguments: dict) -> list[types.TextContent]: + try: + with open(os.devnull, "w") as fnull: + with redirect_stdout(fnull), redirect_stderr(fnull): + if name == "cognify": + await cognify( + text=arguments["text"], + graph_model_file=arguments.get("graph_model_file", None), + graph_model_name=arguments.get("graph_model_name", None), + ) + + return [types.TextContent(type="text", text="Ingested")] + elif name == "search": + search_results = await search(arguments["search_query"]) + + return [types.TextContent(type="text", text=search_results)] + elif name == "prune": + await prune() + + return [types.TextContent(type="text", text="Pruned")] + except Exception as e: + logger.error(f"Error calling tool '{name}': {str(e)}") + return [types.TextContent(type="text", text=f"Error calling tool '{name}': {str(e)}")] -@mcp.tool() async def cognify(text: str, graph_model_file: str = None, graph_model_name: str = None) -> str: """Build knowledge graph from the input text""" if graph_model_file and graph_model_name: @@ -25,10 +106,7 @@ async def cognify(text: str, graph_model_file: str = None, graph_model_name: str except Exception as e: raise ValueError(f"Failed to cognify: {str(e)}") - return "Ingested" - -@mcp.tool() async def search(search_query: str) -> str: """Search the knowledge graph""" search_results = await cognee.search(SearchType.INSIGHTS, query_text=search_query) @@ -38,16 +116,36 @@ async def search(search_query: str) -> str: return results -@mcp.tool() async def prune() -> str: """Reset the knowledge graph""" await cognee.prune.prune_data() await cognee.prune.prune_system(metadata=True) - return "Pruned" + +async def main(): + try: + from mcp.server.stdio import stdio_server + + async with stdio_server() as (read_stream, write_stream): + await mcp.run( + read_stream=read_stream, + write_stream=write_stream, + initialization_options=InitializationOptions( + server_name="cognee", + server_version="0.1.0", + capabilities=mcp.get_capabilities( + notification_options=NotificationOptions(), + experimental_capabilities={}, + ), + ), + raise_exceptions=True, + ) + + except Exception as e: + logger.error(f"Server failed to start: {str(e)}", exc_info=True) + raise -# @mcp.tool() # async def visualize() -> Image: # """Visualize the knowledge graph""" # try: @@ -116,4 +214,6 @@ def load_class(model_file, model_name): if __name__ == "__main__": # Initialize and run the server - mcp.run(transport="stdio") + import asyncio + + asyncio.run(main()) diff --git a/cognee-mcp/uv.lock b/cognee-mcp/uv.lock index b79e6695..e467727f 100644 --- a/cognee-mcp/uv.lock +++ b/cognee-mcp/uv.lock @@ -1,7 +1,9 @@ version = 1 requires-python = ">=3.10" resolution-markers = [ - 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"sha256:18fb850d47b5a2a6ea45b2f7e0eda687f903a2f2e58909b1defd48e2b3126ff4"}, ] [package.dependencies] @@ -8148,19 +8148,19 @@ wrapt = "*" xlrd = {version = "*", optional = true, markers = "extra == \"xlsx\""} [package.extras] -all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (==0.8.1)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +all-docs = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] csv = ["pandas"] doc = ["python-docx (>=1.1.2)"] docx = ["python-docx (>=1.1.2)"] epub = ["pypandoc"] huggingface = ["langdetect", "sacremoses", "sentencepiece", "torch", "transformers"] -image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (==0.8.1)", "unstructured.pytesseract (>=0.3.12)"] -local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (==0.8.1)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] +image = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)"] +local-inference = ["effdet", "google-cloud-vision", "markdown", "networkx", "onnx", "openpyxl", "pandas", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypandoc", "pypdf", "python-docx (>=1.1.2)", "python-pptx (>=1.0.1)", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)", "xlrd"] md = ["markdown"] odt = ["pypandoc", "python-docx (>=1.1.2)"] org = ["pypandoc"] paddleocr = ["paddlepaddle (==3.0.0b1)", "unstructured.paddleocr (==2.8.1.0)"] -pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (==0.8.1)", "unstructured.pytesseract (>=0.3.12)"] +pdf = ["effdet", "google-cloud-vision", "onnx", "pdf2image", "pdfminer.six", "pi-heif", "pikepdf", "pypdf", "unstructured-inference (>=0.8.6)", "unstructured.pytesseract (>=0.3.12)"] ppt = ["python-pptx (>=1.0.1)"] pptx = ["python-pptx (>=1.0.1)"] rst = ["pypandoc"] @@ -8528,13 +8528,13 @@ test = ["pytest", "pytest-cov"] [[package]] name = "xlsxwriter" -version = "3.2.0" +version = "3.2.1" description = "A Python module for creating Excel XLSX files." optional = true python-versions = ">=3.6" files = [ - {file = "XlsxWriter-3.2.0-py3-none-any.whl", hash = "sha256:ecfd5405b3e0e228219bcaf24c2ca0915e012ca9464a14048021d21a995d490e"}, - {file = "XlsxWriter-3.2.0.tar.gz", hash = "sha256:9977d0c661a72866a61f9f7a809e25ebbb0fb7036baa3b9fe74afcfca6b3cb8c"}, + {file = "XlsxWriter-3.2.1-py3-none-any.whl", hash = "sha256:7e8f7c60b7a1660ef791d46ab5de78469cb978b991ca841af61f5832d2f9f4fe"}, + {file = "XlsxWriter-3.2.1.tar.gz", hash = "sha256:97618759cb264fb6a93397f660cca156ffa9561743b1823dafb60dc4474e1902"}, ] [[package]] @@ -8815,4 +8815,4 @@ weaviate = ["weaviate-client"] [metadata] lock-version = "2.0" python-versions = ">=3.10.0,<3.13" -content-hash = "9b5d0162e4fdaaded920a2c8b448e07ec794c55914c1d6e18c6ab9b48c42df2d" +content-hash = "1cc352109264d0e3add524cdc15c9b2e6153e1bab20d968b40e42a4d5138967f" diff --git a/pyproject.toml b/pyproject.toml index 731203c9..034b4889 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,7 +22,7 @@ python = ">=3.10.0,<3.13" openai = "1.59.4" pydantic = "2.10.5" python-dotenv = "1.0.1" -fastapi = ">=0.109.2,<0.116.0" +fastapi = "0.115.7" uvicorn = "0.34.0" requests = "2.32.3" aiohttp = "3.10.10"