Get the binary content of an attachment. Requires npub for credit billing.
| Name | Required | Description | Default |
|---|---|---|---|
| npub | No | Required. Your Nostr public key (npub1...) for credit billing. | |
| brain_id | No | The ID of the brain (uses active brain if not specified) | |
| dpop_token | No | ||
| save_to_path | No | Optional path to save the file locally | |
| attachment_id | Yes | The ID of the attachment |
| 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, the description carries the full burden of behavioral disclosure. It mentions the npub requirement for credit billing, which is a useful behavioral trait, but omits other important aspects such as side effects (e.g., whether save_to_path writes to disk), return format, or potential size limitations. This is insufficient for a tool that retrieves binary data.
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 extremely concise: two sentences, first states the core purpose, second adds the billing requirement. There is zero waste, and the key action is front-loaded.
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 relatively simple, and the schema covers most parameters. However, the description lacks important context about how the binary content is returned (e.g., base64, file download) and does not clarify the relationship to the sibling tool brain_get_attachment. It also doesn't explain the behavior of the optional save_to_path parameter, despite that being a notable feature.
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?
The input schema covers 80% of parameters with descriptions, so the baseline is 3. The description's mention of 'Requires npub' adds no new information because the schema already describes npub as required for billing. It does not clarify the purpose of dpop_token or elaborate on save_to_path behavior beyond the schema.
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 tool retrieves the binary content of an attachment, which is a specific verb+resource action. While it implicitly distinguishes from the sibling tool 'brain_get_attachment' via the modifier 'binary', it does not explicitly differentiate them, leaving a small ambiguity.
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?
No guidance is provided on when to use this tool versus alternatives like brain_get_attachment or brain_list_attachments. The only additional information is the npub requirement for billing, which is a prerequisite rather than usage context, so the agent gets no direction on selecting this tool.
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.