Retrieve a memory by ID along with its connections. On failure, content[0].text is JSON: {"error_class": "not_found|retryable|forbidden|internal", "message": "..."}. Switch on error_class: retry on retryable, prompt user to check the ID on not_found.
| Name | Required | Description | Default |
|---|---|---|---|
| id | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, and the description does not contradict them. It adds significant behavioral detail beyond annotations: on failure, content[0].text is a JSON error envelope with a specific error_class discriminator and a suggested recovery action per error type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with the primary action front-loaded and error-handling instructions compactly integrated. No filler, redundancy, or repetition of annotation information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read tool with no output schema, the description covers the failure response format and recovery steps well. The successful return structure is only summarized as 'memory along with its connections', which is sufficient for high-level invocation but leaves parsing details implicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It clarifies that 'id' refers to the memory ID, which adds some meaning, but it does not describe ID format, validity, or optionality. Compensation is partial for a single-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb ('Retrieve'), a resource ('a memory by ID'), and an additional output ('along with its connections'). This clearly distinguishes it from siblings like remember, forget, and search, which create, delete, or query memories differently.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies clear usage context: call when you have a memory ID and need that memory plus its connections. It also gives explicit guidance on failure handling—retry on retryable errors and prompt the user to verify the ID on not_found—though it does not name alternative tools or exclusion cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct operation—lifecycle (remember/revise/forget), graph edges (connect/disconnect/why_connected), retrieval (recall/search/recent/history/orient/significance)—and the descriptions carefully disambiguate overlaps. However, the read/analysis cluster (recent, history, orient.recent, significance) could still cause initial misselection before reading the detailed descriptions.
Names are readable and consistently lowercase, but they do not follow a single convention: most are bare verbs (connect, remember, revise, search, visualise) while others are nouns (domains, history, recent, significance) and two are multiword phrases (suggest_connections, why_connected). This mix is still predictable enough to navigate, but less coherent than a uniform verb_noun surface.
16 tools is slightly above the typical 3–15 band, but the scope of a knowledge-graph memory server justifies the breadth: CRUD, connections, domain admin, and multiple query/analysis tools are all represented. No tool feels redundant enough to cut, though the set is at the heavy end.
Core lifecycle is well covered: create/read/update/archive/purge, connection creation/removal, domain admin, and multiple query/analysis modes. The main gap is that bulk domain merge (merge_domains) is referenced in tool descriptions but not exposed as an MCP tool, so agents must direct users to an external admin interface for that operation.
