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enable use of Azure OpenAI with mcp server (#368)

Browse source 
* add azure open ai dependency

* update readme

* Create support for azure open ai endpoints

* fix: formatting

---------

Co-authored-by: paulpaliychuk <pavlo.paliychuk.ca@gmail.com>
This commit is contained in:
Diego Colombo 2025-04-18 02:05:08 +01:00 • committed by GitHub
parent daaa0beab9
commit a193476abe
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6 changed files with 500 additions and 17 deletions
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9
mcp_server/.env.example
View file

@ -24,3 +24,12 @@ MODEL_NAME=gpt-4.1-mini
# NEO4J_server_memory_heap_initial__size=512m # NEO4J_server_memory_heap_initial__size=512m
# NEO4J_server_memory_heap_max__size=1G # NEO4J_server_memory_heap_max__size=1G
# NEO4J_server_memory_pagecache_size=512m # NEO4J_server_memory_pagecache_size=512m
# Azure OpenAI configuration
# Optional: Only needed for Azure OpenAI endpoints
# AZURE_OPENAI_ENDPOINT=your_azure_openai_endpoint_here
# AZURE_OPENAI_API_VERSION=2025-01-01-preview
# AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o-gpt-4o-mini-deployment
# AZURE_OPENAI_EMBEDDING_API_VERSION=2023-05-15
# AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=text-embedding-3-large-deployment
# AZURE_OPENAI_USE_MANAGED_IDENTITY=false

2
mcp_server/Dockerfile
View file

@ -17,6 +17,8 @@ RUN uv sync
# Copy application code # Copy application code
COPY graphiti_mcp_server.py . COPY graphiti_mcp_server.py .
EXPOSE 8000
# Set environment variables # Set environment variables
ENV PYTHONUNBUFFERED=1 ENV PYTHONUNBUFFERED=1

6
mcp_server/README.md
View file

@ -52,6 +52,12 @@ The server uses the following environment variables:
- `OPENAI_API_KEY`: OpenAI API key (required for LLM operations) - `OPENAI_API_KEY`: OpenAI API key (required for LLM operations)
- `OPENAI_BASE_URL`: Optional base URL for OpenAI API - `OPENAI_BASE_URL`: Optional base URL for OpenAI API
- `MODEL_NAME`: Optional model name to use for LLM inference - `MODEL_NAME`: Optional model name to use for LLM inference
- `AZURE_OPENAI_ENDPOINT`: Optional Azure OpenAI endpoint URL
- `AZURE_OPENAI_DEPLOYMENT_NAME`: Optional Azure OpenAI deployment name
- `AZURE_OPENAI_API_VERSION`: Optional Azure OpenAI API version
- `AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME`: Optional Azure OpenAI embedding deployment name
- `AZURE_OPENAI_EMBEDDING_API_VERSION`: Optional Azure OpenAI API version
- `AZURE_OPENAI_USE_MANAGED_IDENTITY`: Optional use Azure Managed Identities for authentication
You can set these variables in a `.env` file in the project directory. You can set these variables in a `.env` file in the project directory.

217
mcp_server/graphiti_mcp_server.py
View file

@ -9,15 +9,22 @@ import logging
import os import os
import sys import sys
import uuid import uuid
from collections.abc import Callable
from datetime import datetime, timezone from datetime import datetime, timezone
from typing import Any, TypedDict, cast from typing import Any, TypedDict, cast
from azure.identity import DefaultAzureCredential, get_bearer_token_provider
from dotenv import load_dotenv from dotenv import load_dotenv
from mcp.server.fastmcp import FastMCP from mcp.server.fastmcp import FastMCP
from openai import AsyncAzureOpenAI
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
from graphiti_core import Graphiti from graphiti_core import Graphiti
from graphiti_core.cross_encoder.client import CrossEncoderClient
from graphiti_core.cross_encoder.openai_reranker_client import OpenAIRerankerClient
from graphiti_core.edges import EntityEdge from graphiti_core.edges import EntityEdge
from graphiti_core.embedder.client import EmbedderClient
from graphiti_core.embedder.openai import OpenAIEmbedder, OpenAIEmbedderConfig
from graphiti_core.llm_client import LLMClient from graphiti_core.llm_client import LLMClient
from graphiti_core.llm_client.config import LLMConfig from graphiti_core.llm_client.config import LLMConfig
from graphiti_core.llm_client.openai_client import OpenAIClient from graphiti_core.llm_client.openai_client import OpenAIClient
@ -32,6 +39,7 @@ from graphiti_core.utils.maintenance.graph_data_operations import clear_data
load_dotenv() load_dotenv()
DEFAULT_LLM_MODEL = 'gpt-4.1-mini' DEFAULT_LLM_MODEL = 'gpt-4.1-mini'
DEFAULT_EMBEDDER_MODEL = 'text-embedding-3-small'
class Requirement(BaseModel): class Requirement(BaseModel):
@ -153,10 +161,19 @@ class StatusResponse(TypedDict):
message: str message: str
def create_azure_credential_token_provider() -> Callable[[], str]:
credential = DefaultAzureCredential()
token_provider = get_bearer_token_provider(
credential, 'https://cognitiveservices.azure.com/.default'
)
return token_provider
# Server configuration classes # Server configuration classes
# The configuration system has a hierarchy: # The configuration system has a hierarchy:
# - GraphitiConfig is the top-level configuration # - GraphitiConfig is the top-level configuration
# - LLMConfig handles all OpenAI/LLM related settings # - LLMConfig handles all OpenAI/LLM related settings
# - EmbedderConfig manages embedding settings
# - Neo4jConfig manages database connection details # - Neo4jConfig manages database connection details
# - Various other settings like group_id and feature flags # - Various other settings like group_id and feature flags
# Configuration values are loaded from: # Configuration values are loaded from:
@ -172,6 +189,10 @@ class GraphitiLLMConfig(BaseModel):
api_key: str | None = None api_key: str | None = None
model: str = DEFAULT_LLM_MODEL model: str = DEFAULT_LLM_MODEL
temperature: float = 0.0 temperature: float = 0.0
azure_openai_endpoint: str | None = None
azure_openai_deployment_name: str | None = None
azure_openai_api_version: str | None = None
azure_openai_use_managed_identity: bool = False
@classmethod @classmethod
def from_env(cls) -> 'GraphitiLLMConfig': def from_env(cls) -> 'GraphitiLLMConfig':
@ -180,22 +201,53 @@ class GraphitiLLMConfig(BaseModel):
model_env = os.environ.get('MODEL_NAME', '') model_env = os.environ.get('MODEL_NAME', '')
model = model_env if model_env.strip() else DEFAULT_LLM_MODEL model = model_env if model_env.strip() else DEFAULT_LLM_MODEL
# Log if empty model was provided azure_openai_endpoint = os.environ.get('AZURE_OPENAI_ENDPOINT', None)
if model_env == '': azure_openai_api_version = os.environ.get('AZURE_OPENAI_API_VERSION', None)
logger.debug( azure_openai_deployment_name = os.environ.get('AZURE_OPENAI_DEPLOYMENT_NAME', None)
f'MODEL_NAME environment variable not set, using default: {DEFAULT_LLM_MODEL}' azure_openai_use_managed_identity = (
) os.environ.get('AZURE_OPENAI_USE_MANAGED_IDENTITY', 'false').lower() == 'true'
elif not model_env.strip():
logger.warning(
f'Empty MODEL_NAME environment variable, using default: {DEFAULT_LLM_MODEL}'
)
return cls(
api_key=os.environ.get('OPENAI_API_KEY'),
model=model,
temperature=float(os.environ.get('LLM_TEMPERATURE', '0.0')),
) )
if azure_openai_endpoint is None:
# Setup for OpenAI API
# Log if empty model was provided
if model_env == '':
logger.debug(
f'MODEL_NAME environment variable not set, using default: {DEFAULT_LLM_MODEL}'
)
elif not model_env.strip():
logger.warning(
f'Empty MODEL_NAME environment variable, using default: {DEFAULT_LLM_MODEL}'
)
return cls(
api_key=os.environ.get('OPENAI_API_KEY'),
model=model,
temperature=float(os.environ.get('LLM_TEMPERATURE', '0.0')),
)
else:
# Setup for Azure OpenAI API
# Log if empty deployment name was provided
if azure_openai_deployment_name is None:
logger.error('AZURE_OPENAI_DEPLOYMENT_NAME environment variable not set')
raise ValueError('AZURE_OPENAI_DEPLOYMENT_NAME environment variable not set')
if not azure_openai_use_managed_identity:
# api key
api_key = os.environ.get('OPENAI_API_KEY', None)
else:
# Managed identity
api_key = None
return cls(
azure_openai_use_managed_identity=azure_openai_use_managed_identity,
azure_openai_endpoint=azure_openai_endpoint,
api_key=api_key,
azure_openai_api_version=azure_openai_api_version,
azure_openai_deployment_name=azure_openai_deployment_name,
temperature=float(os.environ.get('LLM_TEMPERATURE', '0.0')),
)
@classmethod @classmethod
def from_cli_and_env(cls, args: argparse.Namespace) -> 'GraphitiLLMConfig': def from_cli_and_env(cls, args: argparse.Namespace) -> 'GraphitiLLMConfig':
"""Create LLM configuration from CLI arguments, falling back to environment variables.""" """Create LLM configuration from CLI arguments, falling back to environment variables."""
@ -220,8 +272,32 @@ class GraphitiLLMConfig(BaseModel):
"""Create an LLM client based on this configuration. """Create an LLM client based on this configuration.
Returns: Returns:
LLMClient instance if API key is available, None otherwise LLMClient instance if able, None otherwise
""" """
if self.azure_openai_endpoint is not None:
# Azure OpenAI API setup
if self.azure_openai_use_managed_identity:
# Use managed identity for authentication
token_provider = create_azure_credential_token_provider()
return AsyncAzureOpenAI(
azure_endpoint=self.azure_openai_endpoint,
azure_deployment=self.azure_openai_deployment_name,
api_version=self.azure_openai_api_version,
azure_ad_token_provider=token_provider,
)
elif self.api_key:
# Use API key for authentication
return AsyncAzureOpenAI(
azure_endpoint=self.azure_openai_endpoint,
azure_deployment=self.azure_openai_deployment_name,
api_version=self.azure_openai_api_version,
api_key=self.api_key,
)
else:
logger.error('OPENAI_API_KEY must be set when using Azure OpenAI API')
return None
if not self.api_key: if not self.api_key:
return None return None
@ -232,6 +308,110 @@ class GraphitiLLMConfig(BaseModel):
return OpenAIClient(config=llm_client_config) return OpenAIClient(config=llm_client_config)
def create_cross_encoder_client(self) -> CrossEncoderClient | None:
"""Create a cross-encoder client based on this configuration."""
if self.azure_openai_endpoint is not None:
client = self.create_client()
return OpenAIRerankerClient(client=client)
else:
llm_client_config = LLMConfig(api_key=self.api_key, model=self.model)
return OpenAIRerankerClient(config=llm_client_config)
class GraphitiEmbedderConfig(BaseModel):
"""Configuration for the embedder client.
Centralizes all embedding-related configuration parameters.
"""
model: str = DEFAULT_EMBEDDER_MODEL
api_key: str | None = None
azure_openai_endpoint: str | None = None
azure_openai_deployment_name: str | None = None
azure_openai_api_version: str | None = None
azure_openai_use_managed_identity: bool = False
@classmethod
def from_env(cls) -> 'GraphitiEmbedderConfig':
"""Create embedder configuration from environment variables."""
# Get model from environment, or use default if not set or empty
model_env = os.environ.get('EMBEDDER_MODEL_NAME', '')
model = model_env if model_env.strip() else DEFAULT_EMBEDDER_MODEL
azure_openai_endpoint = os.environ.get('AZURE_OPENAI_ENDPOINT', None)
azure_openai_api_version = os.environ.get('AZURE_OPENAI_EMBEDDING_API_VERSION', None)
azure_openai_deployment_name = os.environ.get(
'AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME', None
)
azure_openai_use_managed_identity = (
os.environ.get('AZURE_OPENAI_USE_MANAGED_IDENTITY', 'false').lower() == 'true'
)
if azure_openai_endpoint is not None:
# Setup for Azure OpenAI API
# Log if empty deployment name was provided
azure_openai_deployment_name = os.environ.get(
'AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME', None
)
if azure_openai_deployment_name is None:
logger.error('AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME environment variable not set')
raise ValueError(
'AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME environment variable not set'
)
if not azure_openai_use_managed_identity:
# api key
api_key = os.environ.get('OPENAI_API_KEY', None)
else:
# Managed identity
api_key = None
return cls(
azure_openai_use_managed_identity=azure_openai_use_managed_identity,
azure_openai_endpoint=azure_openai_endpoint,
api_key=api_key,
azure_openai_api_version=azure_openai_api_version,
azure_openai_deployment_name=azure_openai_deployment_name,
)
else:
return cls(
model=model,
api_key=os.environ.get('OPENAI_API_KEY'),
)
def create_client(self) -> EmbedderClient | None:
if self.azure_openai_endpoint is not None:
# Azure OpenAI API setup
if self.azure_openai_use_managed_identity:
# Use managed identity for authentication
token_provider = create_azure_credential_token_provider()
return AsyncAzureOpenAI(
azure_endpoint=self.azure_openai_endpoint,
azure_deployment=self.azure_openai_deployment_name,
api_version=self.azure_openai_api_version,
azure_ad_token_provider=token_provider,
)
elif self.api_key:
# Use API key for authentication
return AsyncAzureOpenAI(
azure_endpoint=self.azure_openai_endpoint,
azure_deployment=self.azure_openai_deployment_name,
api_version=self.azure_openai_api_version,
api_key=self.api_key,
)
else:
logger.error('OPENAI_API_KEY must be set when using Azure OpenAI API')
return None
else:
# OpenAI API setup
if not self.api_key:
return None
embedder_config = OpenAIEmbedderConfig(api_key=self.api_key, model=self.model)
return OpenAIEmbedder(config=embedder_config)
class Neo4jConfig(BaseModel): class Neo4jConfig(BaseModel):
"""Configuration for Neo4j database connection.""" """Configuration for Neo4j database connection."""
@ -257,6 +437,7 @@ class GraphitiConfig(BaseModel):
""" """
llm: GraphitiLLMConfig = Field(default_factory=GraphitiLLMConfig) llm: GraphitiLLMConfig = Field(default_factory=GraphitiLLMConfig)
embedder: GraphitiEmbedderConfig = Field(default_factory=GraphitiEmbedderConfig)
neo4j: Neo4jConfig = Field(default_factory=Neo4jConfig) neo4j: Neo4jConfig = Field(default_factory=Neo4jConfig)
group_id: str | None = None group_id: str | None = None
use_custom_entities: bool = False use_custom_entities: bool = False
@ -267,6 +448,7 @@ class GraphitiConfig(BaseModel):
"""Create a configuration instance from environment variables.""" """Create a configuration instance from environment variables."""
return cls( return cls(
llm=GraphitiLLMConfig.from_env(), llm=GraphitiLLMConfig.from_env(),
embedder=GraphitiEmbedderConfig.from_env(),
neo4j=Neo4jConfig.from_env(), neo4j=Neo4jConfig.from_env(),
) )
@ -369,12 +551,17 @@ async def initialize_graphiti():
if not config.neo4j.uri or not config.neo4j.user or not config.neo4j.password: if not config.neo4j.uri or not config.neo4j.user or not config.neo4j.password:
raise ValueError('NEO4J_URI, NEO4J_USER, and NEO4J_PASSWORD must be set') raise ValueError('NEO4J_URI, NEO4J_USER, and NEO4J_PASSWORD must be set')
embedder_client = config.embedder.create_client()
cross_encoder_client = config.llm.create_cross_encoder_client()
# Initialize Graphiti client # Initialize Graphiti client
graphiti_client = Graphiti( graphiti_client = Graphiti(
uri=config.neo4j.uri, uri=config.neo4j.uri,
user=config.neo4j.user, user=config.neo4j.user,
password=config.neo4j.password, password=config.neo4j.password,
llm_client=llm_client, llm_client=llm_client,
embedder=embedder_client,
cross_encoder=cross_encoder_client,
) )
# Destroy graph if requested # Destroy graph if requested

1
mcp_server/pyproject.toml
View file

@ -8,4 +8,5 @@ dependencies = [
"mcp>=1.5.0", "mcp>=1.5.0",
"openai>=1.68.2", "openai>=1.68.2",
"graphiti-core>=0.8.2", "graphiti-core>=0.8.2",
"azure-identity>=1.21.0",
] ]

282
mcp_server/uv.lock generated
View file

@ -1,4 +1,5 @@
version = 1 version = 1
revision = 1
requires-python = ">=3.10" requires-python = ">=3.10"
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