personalbrain-mcp

brain_update_thought

Update a thought's properties and/or its parent in one call. Requires npub for credit billing.

Sets any subset of {name, label, colors, kind, ac_type, type, parent} on a single thought. Reparenting via new_parent_id replaces the existing parent link (the old parent child-link is deleted and a new one created); it does not add an additional parent.

Input Schema

TableJSON Schema

Name	Required	Description
`kind`	No	New kind
`name`	No	New name
`npub`	No	Required. Your Nostr public key (npub1...) for credit billing.
`label`	No	New label
`ac_type`	No	New access type
`confirm`	No	If True, verify type/parent changes against the authoritative change-log (SET_TYPE / MOVED_LINK) instead of the cached graph, and attach a ``confirmation`` block. Costs one extra billed read.
`type_id`	No	New type ID
`brain_id`	No	The ID of the brain (uses active brain if not specified)
`dpop_token`	No
`thought_id`	Yes	The ID of the thought to update
`new_parent_id`	No	New parent thought ID (replaces all current parents)
`background_color`	No	New background color in hex
`foreground_color`	No	New foreground color in hex

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedJul 18, 2026

addedInput schema / properties / confirm

Added value: +{
+  "default": false,
+  "description": "If True, verify type/parent changes against the authoritative\nchange-log (SET_TYPE / MOVED_LINK) instead of the cached graph, and\nattach a ``confirmation`` block. Costs one extra billed read.",
+  "type": "boolean"
+}

First observedJul 16, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden of disclosing behavior. It explicitly states the billing requirement (npub) and the destructive reparenting behavior (old parent link deleted, new one created; not additive). This adds important context beyond the bare 'update' concept, though it does not cover all edge cases like error handling or confirmation semantics.

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 concise (about 60 words) and front-loaded with the main purpose. It includes the essential subset semantics and the reparenting caveat without unnecessary fluff. Every sentence contributes valuable 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?

For a mutation tool with 13 parameters and an output schema, the description covers the most critical non-obvious behaviors (partial update, billing, and destructive reparenting). It does not explain confirmation logic or error scenarios, but those are partially covered by the schema and output schema, preventing a lower score.

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 high (92%) and the description adds meaningful semantics by explaining that any subset of properties can be set and, critically, that new_parent_id replaces the existing parent rather than adding one. This goes beyond the schema descriptions for individual parameters.

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 updates a thought's properties and/or parent, using a specific verb and resource. It distinguishes itself from sibling tools like brain_create_thought and brain_delete_thought by focusing on updating existing thoughts.

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 clearly implies when to use the tool (when updating thought properties or reparenting) and notes the npub billing requirement. It does not explicitly mention alternatives or exclusions, but the context is clear enough for the agent to select this tool over create/delete siblings.

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

All personalbrain-mcp tools Inspect

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.

brain_update_thought

Input Schema

Output Schema

Schema Changelog

TDQS

Glama MCP Gateway

TDQS

Resources