A local-first temporal knowledge graph with a read-only MCP server and CLI
Graphiti Local provides 6 read-only tools with complete JSON schemas and reasonable descriptions. All tools have input schemas with typed parameters and descriptions. However, descriptions are generic and lack LLM-optimized guidance on when/why to use each tool. Parameter descriptions are minimal (e.g., 'Search query string' without format hints). No output schemas documented. Error handling and recovery guidance absent. Tool naming is clear (verb_noun pattern) but composition could be tighter, search_nodes and search_memory_facts overlap conceptually.
Retrieve a specific entity edge by UUID.
Retrieve entities associated with specific episodes.
Retrieve episodes from the knowledge graph, optionally filtered by group IDs.
Get the status of the Graphiti Local server and its connection to the knowledge graph backend.
Search memory facts in the knowledge graph with optional filtering by edge types and temporal validity.
Search graph entities. Requests are restricted to configured groups.
No output schemas documented. LLMs cannot predict response structure or plan downstream tool calls. Example: search_nodes returns nodes but fields are not specified.
Descriptions lack LLM-optimized guidance. Generic descriptions like 'Search graph entities' (22 chars) do not explain WHEN to use this tool vs search_memory_facts, or what the response contains. Baseline: 194 chars average.
Parameter descriptions are minimal. 'Search query string' does not specify format, length limits, or example patterns. 'Graph group IDs to search within' lacks guidance on how to obtain group IDs or whether they are required.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 56 | 2025-06-18+ | v2 |
No error handling or recovery guidance. If a search returns no results or a UUID is invalid, the tool provides no actionable next steps for the LLM.
Conceptual overlap: search_nodes and search_memory_facts both search the graph but return different entity types. Descriptions do not clarify the distinction or guide LLM selection.