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personalbrain-mcp

by io.github.lonniev

brain_request_adoption

Ask a chosen Authority to adopt this operator (deferred courtship).

RESTRICTED to the operator — requires proof the caller controls this operator's npub. Resolves the Authority's MCP endpoint from the community registry, mints an inline ownership proof with this operator's nsec, and delivers the request MCP-to-MCP. The Authority records it as pending; its owner approves on their own time. Poll adoption_status for progress; the operator flips to ready once the Authority provisions it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNooptional message for the Authority owner.
dpop_tokenNooperator-npub ownership proof (inline kind-27235 or cached token).
service_urlNothis operator's MCP endpoint (advertised to the Authority).
authority_npubYesnpub of the Authority to request adoption from.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations provided, the description fully carries the burden and exceeds it. It discloses the process (resolving endpoint, minting proof, delivering MCP-to-MCP), the security restriction, and the outcome (pending until owner approves), giving a complete picture of the tool's behavior.

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 three dense sentences that front-load the purpose, state the restriction, and outline the process and follow-up. Every sentence earns its place; no wasted words or redundant information.

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?

Given the tool's complexity and the existence of an output schema, the description covers purpose, prerequisites, process, and follow-up. It doesn't explain return values (handled by output schema) or error conditions, which is a minor gap for a request tool.

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 adds little param-specific detail beyond what the schema already provides, only contextualizing the flow by mentioning the proof and endpoint, but not adding new semantics.

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 action: 'Ask a chosen Authority to adopt this operator.' It uses a specific verb and resource, and distinguishes from sibling tools like brain_adoption_status by describing the initiation of the request rather than checking its status.

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?

It provides clear context: RESTRICTED to the operator, requires proof of npub control, and directs the user to poll adoption_status for progress. This implies the appropriate use case and follow-up, though it doesn't explicitly enumerate exclusions or alternatives beyond adoption_status.

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.

Resources