Fetch a specific memory entry by id (from memory_search).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The memory entry id. |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | Whether noticed completed the operation. | |
| data | No | The operation result when ok is true. | |
| error | No | A human-readable error when ok is false. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "http://json-schema.org/draft-07/schema#",
+ "additionalProperties": true,
+ "properties": {
+ "data": {
+ "additionalProperties": true,
+ "description": "The operation result when ok is true.",
+ "properties": {
+ "content": {
+ "type": "string"
+ },
+ "createdAt": {
+ "type": "string"
+ },
+ "id": {
+ "type": "string"
+ },
+ "memoryType": {
+ "type": "string"
+ },
+ "similarity": {
+ "type": "number"
+ },
+ "sourceDate": {
+ "type": [
+ "string",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "id",
+ "content"
+ ],
+ "type": "object"
+ },
+ "error": {
+ "description": "A human-readable error when ok is false.",
+ "type": "string"
+ },
+ "ok": {
+ "description": "Whether noticed completed the operation.",
+ "type": "boolean"
+ }
+ },
+ "required": [
+ "ok"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint, idempotentHint, destructiveHint, and openWorldHint, covering the safety profile. The description agrees with these annotations and adds the slight behavioral note that ids originate from memory_search, but otherwise defers to the structured data, which is acceptable given the richness of the annotations.
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?
Eleven words communicate exactly what the tool does and where the id originates, with the most important action verb leading. Not a wasted word, and the provenance note earns its place.
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 tool with 100% schema coverage, a comprehensive annotations block, and an output schema, the description fully covers what an agent needs to invoke it correctly. The minimal description is complete for the tool's complexity.
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 coverage is 100% and the schema defines the id simply as 'The memory entry id.' The description adds value by signaling that a valid id comes from memory_search results, constraining the parameter's valid domain beyond the schema. This is a small but meaningful enhancement.
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?
The description uses a specific verb ('Fetch'), a precise resource ('specific memory entry'), and identifies the lookup key ('by id'). The parenthetical '(from memory_search)' further clarifies both the identity domain and the natural workflow, effectively distinguishing this from siblings like memory_search and memory_save.
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 parenthetical '(from memory_search)' implies the expected workflow—search results yield the id to fetch—but stops short of explicitly stating when to choose this tool over alternatives like memory_search or when not to use it. Usage is indicated rather than spelled out.
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.
The tool set is organized around distinct resources, and the descriptions work hard to separate them, but several close pairs remain easy to confuse: add_memory vs memory_save vs add_note, accept_identity_match vs suggest_identity_match, and dismiss_identity_match vs mark_different_people. An agent will often need to read very subtle signals (who originated the content, pending vs initiating a merge, soft vs durable rejection) to pick the right tool.
Most tools follow a clear verb_noun snake_case pattern like create_list, update_person, and delete_view, which is readable and mostly predictable. However, the memory tools break the pattern (memory_save, memory_get, memory_search instead of save_memory/get_memory/search_memory), and a few noun-style names (my_profile, network_summary, account_status) add inconsistency.
At 57 tools, this is an extremely large surface that exceeds the calibration threshold for an extreme mismatch. The scope is broad, but many tools are micro-specialized variations of the same concept, such as four memory-related tools and seven identity-match tools, which makes the count feel inflated rather than well-scoped.
The tool set provides thorough lifecycle coverage for the core domain: people can be added, updated, searched, and removed; lists, views, actions, and scheduled tasks have create/read/update/delete; and identity matching has accept, dismiss, differentiate, and suggest paths. Minor gaps exist, such as no direct memory/note deletion or intro deletion, but agents can generally complete workflows without hitting dead ends.