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personalbrain-mcp

by io.github.lonniev

brain_check_payment

Check the payment status of a Lightning invoice.

Call after paying the invoice from purchase_credits. Free — no credits required. Proof of npub ownership is required to prevent credit-grant front-running by an observer of the invoice ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
npubYesThe Nostr public key (npub1...) that purchased the invoice.
dpop_tokenYesRaw JSON of a kind-27235 Nostr event signed by npub — not base64, not NIP-98 'Authorization: Nostr <b64>' framing. Its `u` tag must hold THIS tool's exact name (from tools/list), not the endpoint URL; content:"", created_at within 60s of now, and a random `nonce` tag recommended. Or a cached dpop_token phrase.
invoice_idYesThe invoice ID returned by purchase_credits.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description discloses important behavioral traits: 'Free — no credits required' and the security rationale for npub ownership proof. It adds context beyond the basic check operation, though it doesn't describe potential error responses or specific statuses returned. This is valuable but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only three sentences, front-loaded with the main purpose, and includes critical caveats without any fluff. Every sentence earns its place, making it very concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, full schema coverage, and presence of an output schema, the description covers the essential workflow (when to call), prerequisites (npub proof), and cost (free). It is complete for an agent to correctly select and invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with detailed parameter descriptions, so baseline is 3. The description adds additional meaning by tying invoice_id to purchase_credits output and explaining why npub ownership proof is needed. This goes slightly beyond the schema, justifying a 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Check the payment status of a Lightning invoice.' It distinguishes itself from siblings by specifying the exact resource (Lightning invoice) and the workflow context (after purchase_credits). This is specific with a verb and resource, making it easily distinguishable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit usage context: 'Call after paying the invoice from purchase_credits.' It also mentions the requirement of npub ownership proof. However, it does not explicitly state when not to use this tool or mention alternatives, so it doesn't reach a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.3/5.0
Disambiguation2/5

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.

Naming Consistency3/5

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`).

Tool Count2/5

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.

Completeness4/5

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.

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