Get details about a specific brain. Requires npub for credit billing.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | No | Required. Your Nostr public key (npub1...) for credit billing. | |
| brain_id | Yes | The ID of the brain | |
| dpop_token | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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?
With no annotations provided, the description carries the full burden. It adds one useful behavioral detail (npub required for credit billing) but fails to disclose aspects like whether the operation is read-only, what happens without npub, or any rate limits. The description is too sparse to give the agent confidence about side effects or requirements beyond the billing note.
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?
The description is only two sentences, with the core purpose first and the billing requirement second. Every word earns its place, and there is no redundancy or fluff.
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?
The tool is a simple get-by-ID operation with an output schema present, so return values are likely covered by the schema. The description adds the billing context, but lacks guidance on when to use it versus sibling tools, and the npub requirement is stated without explaining whether it is mandatory at the API level despite not being listed as a required schema property. This leaves some ambiguity for a low-complexity tool.
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 67% (npub and brain_id have descriptions; dpop_token does not). The description adds context that npub is required for credit billing, which supplements the schema's note on npub. However, brain_id is described only as 'The ID of the brain' with no additional semantic value, and dpop_token remains unexplained. This is adequate but not exceptional.
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 clearly states the action: 'Get details about a specific brain.' The verb 'get' and resource 'specific brain' distinguish it from sibling tools like brain_list_brains (which lists brains) and brain_get_brain_stats (which gets stats). However, it does not explicitly mention that it retrieves by brain_id, though the schema covers that.
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 provides a prerequisite ('Requires npub for credit billing') but does not state when to use this tool vs alternatives or any exclusions. It implies use when you need details of a single brain, but there is no explicit guidance about preferring this over brain_list_brains or other getters.
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.
Multiple tools have overlapping purposes. For example, `brain_request_credential_channel` and `brain_request_patron_credentials` serve similar roles, and `brain_receive_credentials`, `brain_receive_npub_proof`, and `brain_receive_patron_credentials` all handle receiving data from a courier flow. While descriptions help, the sheer number of tools (83) with similar-sounding purposes (check_ vs get_ vs request_ vs receive_ prefixes) makes it hard to quickly distinguish which tool to use.
The tools mostly follow a `brain_verb_noun` pattern (e.g., `brain_create_thought`, `brain_delete_link`), which provides some consistency. However, there are inconsistencies with prefixes like `brain_oracle_` (e.g., `brain_oracle_about`, `brain_oracle_how_to_join`) which are more like static pages than actions. Additionally, 'check' and 'get' seem interchangeable (e.g., `brain_check_balance` vs `brain_get_thought`), and 'list' is used alongside 'get' in a way that sometimes means the same thing (e.g., `brain_list_brains` vs `brain_get_brain`).
83 tools is an extremely large and unwieldy surface area. While the server aims to be a comprehensive 'operating system' for a specific ecosystem (DPYC/Nostr), this many tools will lead to agent confusion and high latency. Tools like `brain_oracle_about`, `brain_oracle_how_to_join`, and `brain_oracle_network_advisory` could easily be combined into a single tool or served as function parameters.
For its stated domain (managing a 'brain' with credits, payments, and Nostr integration), the tool set is remarkably complete. It covers CRUD operations, payment flows (purchase, check, restore), coupon management, credential handling, and even notarization. Minor gaps are hard to identify, though some flows feel overly complex (e.g., the multiple `request_`/`receive_` patterns could arguably be simplified). The high number of tools is a result of this extreme specialization.