Improve error handling in GeminiEmbedder by raising ValueError for empty embedding values. This change enhances robustness by ensuring that all returned embeddings contain valid data.

Enhance error handling in GeminiEmbedder and GeminiClient
- Added checks to raise exceptions when no embeddings or response text are returned, improving robustness. - Included type ignore comments for mypy compatibility in embed_content calls.
2025-05-21 19:37:05 -07:00 · 2025-05-21 19:31:12 -07:00 · 2025-05-21 18:55:13 -07:00 · 2025-05-21 18:44:40 -07:00 · 2025-05-21 18:14:37 -07:00
5 changed files with 437 additions and 362 deletions
--- a/graphiti_core/embedder/gemini.py
+++ b/graphiti_core/embedder/gemini.py
@ -61,18 +61,29 @@ class GeminiEmbedder(EmbedderClient):
        # Generate embeddings
        result = await self.client.aio.models.embed_content(
            model=self.config.embedding_model or DEFAULT_EMBEDDING_MODEL,
-            contents=[input_data],
+            contents=[input_data],  # type: ignore[arg-type]  # mypy fails on broad union type
            config=types.EmbedContentConfig(output_dimensionality=self.config.embedding_dim),
        )

+        if not result.embeddings or len(result.embeddings) == 0 or not result.embeddings[0].values:
+            raise Exception('No embeddings returned')
+
        return result.embeddings[0].values

    async def create_batch(self, input_data_list: list[str]) -> list[list[float]]:
        # Generate embeddings
        result = await self.client.aio.models.embed_content(
            model=self.config.embedding_model or DEFAULT_EMBEDDING_MODEL,
-            contents=input_data_list,
+            contents=input_data_list,  # type: ignore[arg-type]  # mypy fails on broad union type
            config=types.EmbedContentConfig(output_dimensionality=self.config.embedding_dim),
        )

-        return [embedding.values for embedding in result.embeddings]
+        if not result.embeddings or len(result.embeddings) == 0:
+            raise Exception('No embeddings returned')
+
+        embeddings = []
+        for embedding in result.embeddings:
+            if not embedding.values:
+                raise ValueError('Empty embedding values returned')
+            embeddings.append(embedding.values)
+        return embeddings
--- a/graphiti_core/llm_client/gemini_client.py
+++ b/graphiti_core/llm_client/gemini_client.py
@ -139,13 +139,16 @@ class GeminiClient(LLMClient):
            # Generate content using the simple string approach
            response = await self.client.aio.models.generate_content(
                model=self.model or DEFAULT_MODEL,
-                contents=gemini_messages,
+                contents=gemini_messages,  # type: ignore[arg-type]  # mypy fails on broad union type
                config=generation_config,
            )

            # If this was a structured output request, parse the response into the Pydantic model
            if response_model is not None:
                try:
+                    if not response.text:
+                        raise Exception('No response text')
+
                    validated_model = response_model.model_validate(json.loads(response.text))

                    # Return as a dictionary for API consistency
--- a/mcp_server/README.md
+++ b/mcp_server/README.md
@ -103,7 +103,7 @@ Available arguments:

 - `--model`: Specify the model name to use with the LLM client
 - `--transport`: Choose the transport method (sse or stdio, default: sse)
- `--group-id`: Set a namespace for the graph (optional)
+- `--group-id`: Set a namespace for the graph (optional). If not provided, defaults to "default".
 - `--destroy-graph`: Destroy all Graphiti graphs (use with caution)
 - `--use-custom-entities`: Enable entity extraction using the predefined ENTITY_TYPES

@ -183,7 +183,7 @@ To use the Graphiti MCP server with an MCP-compatible client, configure it to co
 ```json
 {
  "mcpServers": {
-    "graphiti": {
+    "graphiti-memory": {
      "transport": "stdio",
      "command": "/Users/<user>/.local/bin/uv",
      "args": [
@ -214,7 +214,7 @@ For SSE transport (HTTP-based), you can use this configuration:
 ```json
 {
  "mcpServers": {
-    "graphiti": {
+    "graphiti-memory": {
      "transport": "sse",
      "url": "http://localhost:8000/sse"
    }
@ -262,15 +262,20 @@ To integrate the Graphiti MCP Server with the Cursor IDE, follow these steps:
 python graphiti_mcp_server.py --transport sse --use-custom-entities --group-id <your_group_id>
 ```

-Hint: specify a `group_id` to retain prior graph data. If you do not specify a `group_id`, the server will create a new
-graph
+Hint: specify a `group_id` to namespace graph data. If you do not specify a `group_id`, the server will use "default" as the group_id.
+
+or
+
+```bash
+docker compose up
+```

 2. Configure Cursor to connect to the Graphiti MCP server.

 ```json
 {
  "mcpServers": {
-    "Graphiti": {
+    "graphiti-memory": {
      "url": "http://localhost:8000/sse"
    }
  }
@ -284,6 +289,45 @@ graph
 The integration enables AI assistants in Cursor to maintain persistent memory through Graphiti's knowledge graph
 capabilities.

+## Integrating with Claude Desktop (Docker MCP Server)
+
+The Graphiti MCP Server container uses the SSE MCP transport. Claude Desktop does not natively support SSE, so you'll need to use a gateway like `mcp-remote`.
+
+1.  **Run the Graphiti MCP server using SSE transport**:
+
+    ```bash
+    docker compose up
+    ```
+
+2.  **(Optional) Install `mcp-remote` globally**:
+    If you prefer to have `mcp-remote` installed globally, or if you encounter issues with `npx` fetching the package, you can install it globally. Otherwise, `npx` (used in the next step) will handle it for you.
+
+    ```bash
+    npm install -g mcp-remote
+    ```
+
+3.  **Configure Claude Desktop**:
+    Open your Claude Desktop configuration file (usually `claude_desktop_config.json`) and add or modify the `mcpServers` section as follows:
+
+    ```json
+    {
+      "mcpServers": {
+        "graphiti-memory": {
+          // You can choose a different name if you prefer
+          "command": "npx", // Or the full path to mcp-remote if npx is not in your PATH
+          "args": [
+            "mcp-remote",
+            "http://localhost:8000/sse" // Ensure this matches your Graphiti server's SSE endpoint
+          ]
+        }
+      }
+    }
+    ```
+
+    If you already have an `mcpServers` entry, add `graphiti-memory` (or your chosen name) as a new key within it.
+
+4.  **Restart Claude Desktop** for the changes to take effect.
+
 ## Requirements

 - Python 3.10 or higher
@ -293,4 +337,4 @@ capabilities.

 ## License

-This project is licensed under the same license as the Graphiti project.
+This project is licensed under the same license as the parent Graphiti project.
--- a/mcp_server/graphiti_mcp_server.py
+++ b/mcp_server/graphiti_mcp_server.py
@ -8,7 +8,6 @@ import asyncio
 import logging
 import os
 import sys
-import uuid
 from collections.abc import Callable
 from datetime import datetime, timezone
 from typing import Any, TypedDict, cast
@ -301,7 +300,9 @@ class GraphitiLLMConfig(BaseModel):
        if not self.api_key:
            return None

-        llm_client_config = LLMConfig(api_key=self.api_key, model=self.model, small_model=self.model)
+        llm_client_config = LLMConfig(
+            api_key=self.api_key, model=self.model, small_model=self.model
+        )

        # Set temperature
        llm_client_config.temperature = self.temperature
@ -462,7 +463,7 @@ class GraphitiConfig(BaseModel):
        if args.group_id:
            config.group_id = args.group_id
        else:
-            config.group_id = f'graph_{uuid.uuid4().hex[:8]}'
+            config.group_id = 'default'

        config.use_custom_entities = args.use_custom_entities
        config.destroy_graph = args.destroy_graph
@ -497,7 +498,7 @@ config = GraphitiConfig()

 # MCP server instructions
 GRAPHITI_MCP_INSTRUCTIONS = """
-Welcome to Graphiti MCP - a memory service for AI agents built on a knowledge graph. Graphiti performs well
+Graphiti is a memory service for AI agents built on a knowledge graph. Graphiti performs well
 with dynamic data such as user interactions, changing enterprise data, and external information.

 Graphiti transforms information into a richly connected knowledge network, allowing you to 
@ -528,7 +529,7 @@ API keys are provided for any language model operations.

 # MCP server instance
 mcp = FastMCP(
-    'graphiti',
+    'Graphiti Agent Memory',
    instructions=GRAPHITI_MCP_INSTRUCTIONS,
 )

@ -651,7 +652,7 @@ async def process_episode_queue(group_id: str):


@mcp.tool()
-async def add_episode(
+async def add_memory(
    name: str,
    episode_body: str,
    group_id: str | None = None,
@ -659,16 +660,16 @@ async def add_episode(
    source_description: str = '',
    uuid: str | None = None,
 ) -> SuccessResponse | ErrorResponse:
-    """Add an episode to the Graphiti knowledge graph. This is the primary way to add information to the graph.
+    """Add an episode to memory. This is the primary way to add information to the graph.

    This function returns immediately and processes the episode addition in the background.
    Episodes for the same group_id are processed sequentially to avoid race conditions.

    Args:
        name (str): Name of the episode
-        episode_body (str): The content of the episode. When source='json', this must be a properly escaped JSON string,
-                           not a raw Python dictionary. The JSON data will be automatically processed
-                           to extract entities and relationships.
+        episode_body (str): The content of the episode to persist to memory. When source='json', this must be a
+                           properly escaped JSON string, not a raw Python dictionary. The JSON data will be
+                           automatically processed to extract entities and relationships.
        group_id (str, optional): A unique ID for this graph. If not provided, uses the default group_id from CLI
                                 or a generated one.
        source (str, optional): Source type, must be one of:
@ -760,9 +761,6 @@ async def add_episode(
                )
                logger.info(f"Episode '{name}' added successfully")

-                logger.info(f"Building communities after episode '{name}'")
-                await client.build_communities()
-
                logger.info(f"Episode '{name}' processed successfully")
            except Exception as e:
                error_msg = str(e)
@ -792,14 +790,14 @@ async def add_episode(


@mcp.tool()
-async def search_nodes(
+async def search_memory_nodes(
    query: str,
    group_ids: list[str] | None = None,
    max_nodes: int = 10,
    center_node_uuid: str | None = None,
    entity: str = '',  # cursor seems to break with None
 ) -> NodeSearchResponse | ErrorResponse:
-    """Search the Graphiti knowledge graph for relevant node summaries.
+    """Search the graph memory for relevant node summaries.
    These contain a summary of all of a node's relationships with other nodes.

    Note: entity is a single entity type to filter results (permitted: "Preference", "Procedure").
@ -873,13 +871,13 @@ async def search_nodes(


@mcp.tool()
-async def search_facts(
+async def search_memory_facts(
    query: str,
    group_ids: list[str] | None = None,
    max_facts: int = 10,
    center_node_uuid: str | None = None,
 ) -> FactSearchResponse | ErrorResponse:
-    """Search the Graphiti knowledge graph for relevant facts.
+    """Search the graph memory for relevant facts.

    Args:
        query: The search query
@ -924,7 +922,7 @@ async def search_facts(

@mcp.tool()
 async def delete_entity_edge(uuid: str) -> SuccessResponse | ErrorResponse:
-    """Delete an entity edge from the Graphiti knowledge graph.
+    """Delete an entity edge from the graph memory.

    Args:
        uuid: UUID of the entity edge to delete
@ -954,7 +952,7 @@ async def delete_entity_edge(uuid: str) -> SuccessResponse | ErrorResponse:

@mcp.tool()
 async def delete_episode(uuid: str) -> SuccessResponse | ErrorResponse:
-    """Delete an episode from the Graphiti knowledge graph.
+    """Delete an episode from the graph memory.

    Args:
        uuid: UUID of the episode to delete
@ -984,7 +982,7 @@ async def delete_episode(uuid: str) -> SuccessResponse | ErrorResponse:

@mcp.tool()
 async def get_entity_edge(uuid: str) -> dict[str, Any] | ErrorResponse:
-    """Get an entity edge from the Graphiti knowledge graph by its UUID.
+    """Get an entity edge from the graph memory by its UUID.

    Args:
        uuid: UUID of the entity edge to retrieve
@ -1017,7 +1015,7 @@ async def get_entity_edge(uuid: str) -> dict[str, Any] | ErrorResponse:
 async def get_episodes(
    group_id: str | None = None, last_n: int = 10
 ) -> list[dict[str, Any]] | EpisodeSearchResponse | ErrorResponse:
-    """Get the most recent episodes for a specific group.
+    """Get the most recent memory episodes for a specific group.

    Args:
        group_id: ID of the group to retrieve episodes from. If not provided, uses the default group_id.
@ -1065,7 +1063,7 @@ async def get_episodes(

@mcp.tool()
 async def clear_graph() -> SuccessResponse | ErrorResponse:
-    """Clear all data from the Graphiti knowledge graph and rebuild indices."""
+    """Clear all data from the graph memory and rebuild indices."""
    global graphiti_client

    if graphiti_client is None:
--- a/mcp_server/uv.lock
+++ b/mcp_server/uv.lock
@ -27,21 +27,21 @@ wheels = [

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+version = "1.34.0"
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+version = "1.23.0"
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Author	SHA1	Message	Date
Daniel Chalef	7a2111b809	Improve error handling in GeminiEmbedder by raising ValueError for empty embedding values. This change enhances robustness by ensuring that all returned embeddings contain valid data.	2025-05-21 19:37:05 -07:00
Daniel Chalef	b6c0bb9c54	Enhance error handling in GeminiEmbedder and GeminiClient - Added checks to raise exceptions when no embeddings or response text are returned, improving robustness. - Included type ignore comments for mypy compatibility in embed_content calls.	2025-05-21 19:31:12 -07:00
Daniel Chalef	e311dab617	Update README for Graphiti MCP server configuration and integration with Claude Desktop - Changed server name from "graphiti" to "graphiti-memory" in configuration examples for clarity. - Added instructions for running the Graphiti MCP server using Docker. - Included detailed steps for integrating Claude Desktop with the Graphiti MCP server, including optional installation of `mcp-remote`. - Enhanced overall documentation to improve user experience and understanding of the setup process.	2025-05-21 18:55:13 -07:00
Daniel Chalef	8959478170	Update Graphiti MCP server instructions and refactor method names for clarity - Revised the welcome message to enhance clarity about Graphiti's functionality. - Renamed methods for better understanding: `add_episode` to `add_memory`, `search_nodes` to `search_memory_nodes`, `search_facts` to `search_memory_facts`, and updated related docstrings to reflect these changes. - Updated references to "knowledge graph" to "graph memory" for consistency throughout the codebase.	2025-05-21 18:44:40 -07:00
Daniel Chalef	64e312f600	Refactor group_id handling and update dependencies - Changed default behavior for `group_id` to 'default' instead of generating a UUID. - Updated README to reflect the new default behavior for `--group-id`. - Reformatted LLMConfig initialization for better readability. - Bumped versions of several dependencies including `azure-core`, `azure-identity`, `certifi`, `charset-normalizer`, `sse-starlette`, and `typing-inspection`. - Added `python-multipart` as a new dependency. This update improves usability and ensures compatibility with the latest library versions.	2025-05-21 18:14:37 -07:00