Skip to main content
Glama

Add Thought

addThought

Add a thought to an existing chain in Brain-MCP's memory system to manage cognitive processes and reasoning workflows.

Instructions

Add a thought to an existing thought chain

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
chainIdYesThe thought chain ID
thoughtYesThe thought content
typeYesType of thought
parentThoughtIdNoParent thought ID for branching
confidenceNoConfidence level (0-1)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoThe new thought ID
errorNo
successYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It mentions 'Add a thought' which implies a write/mutation operation, but doesn't disclose behavioral traits like permissions needed, whether it's idempotent, rate limits, or what happens on failure. This leaves significant gaps for an agent to understand how to use it safely and effectively.

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 a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core purpose without unnecessary elaboration, making it easy for an agent to parse quickly.

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

Completeness3/5

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

Given the tool has an output schema (which covers return values), 5 parameters with full schema coverage, and no annotations, the description is minimally adequate. However, as a mutation tool with no behavioral disclosure, it should do more to explain usage context and potential side effects to be fully complete for an agent.

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 schema already documents all parameters thoroughly. The description adds no additional meaning beyond the schema, such as explaining relationships between parameters (e.g., how 'parentThoughtId' relates to 'chainId'). Baseline 3 is appropriate as the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('Add') and resource ('thought to an existing thought chain'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'branchThought' or 'evaluateThought', which also manipulate thoughts in some way, so it misses full sibling distinction.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'branchThought' (for branching) and 'evaluateThought' (for evaluation), there's no indication of when 'addThought' is appropriate, such as for appending to a linear chain versus other operations.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DDguan2010/brain-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server