Skip to main content
Glama

personalbrain-mcp

by io.github.lonniev

brain_publish_nostr_profile

Publish a CLIENT-SIGNED kind-0 profile to relays for an npub.

The wheel never holds a patron nsec. The frontend signs the kind-0 metadata event with the patron's session key or a NIP-07 extension and passes the signed event (JSON) here; the wheel verifies the signature matches the npub, then relays it to public relays. The signature is the authorization — no proof token, no key custody. Free.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
npubNoThe patron's Nostr public key the event must be signed by.
signed_eventNoA JSON-encoded, client-signed kind-0 event.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses that the wheel never holds the nsec, signature is the authorization, and the event is relayed to public relays. It also notes it's free. This is solid behavioral disclosure, though it doesn't mention failure modes or rate limits.

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

Conciseness4/5

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

The description is front-loaded with the main purpose and then provides essential security context. It is longer than a single sentence but each part adds value, making it appropriately concise without redundancy.

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

Completeness4/5

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

The description addresses key contextual aspects: security model (no nsec custody), authorization (signature), cost (free), and effect (relay to public relays). An output schema exists, so return values don't need to be explained. It could mention failure conditions (e.g., signature mismatch), but overall it's well-rounded.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description mentions the two parameters in the flow but does not add significant semantic detail beyond what the schema already provides (e.g., format of signed_event is already stated as 'JSON-encoded, client-signed kind-0 event').

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 'Publish a CLIENT-SIGNED kind-0 profile to relays for an npub', specifying the exact action, resource (kind-0 profile), and target (relays). It distinguishes this from siblings like get_nostr_profile by focusing on the publish operation and client-signed input.

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 explains the intended usage context: the frontend signs the event and passes it here, and the wheel verifies and relays. This clearly implies when to use it, but it does not explicitly mention alternatives or when-not-to-use cases, so it falls short of a 5.

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

All personalbrain-mcp toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.

Resources