Cerebro de compañía
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| save_noteC | Save a business note, learning, investment insight, product note, client note, or decision to the company brain. |
| save_chat_summaryC | Save a useful business conversation summary to the company brain. |
| ingest_meetingC | Save a meeting record or transcript that is already available as text or Markdown. |
| ask_brainC | Ask a business question over local Markdown knowledge. Placeholder until GBrain retrieval is wired. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct action: querying the brain, saving meetings, saving chat summaries, and saving general notes. Some potential overlap between save_chat_summary and save_note, but descriptions clarify the intended use.
All tools follow a consistent verb_noun pattern (ask_brain, ingest_meeting, save_chat_summary, save_note) using snake_case, making the naming predictable and clear.
Four tools cover the core operations for a company knowledge brain: querying and saving different content types (meetings, chat summaries, notes). The count is well-scoped for this domain.
The set covers adding knowledge and querying (though ask_brain is a placeholder), but lacks update or delete operations. For a knowledge base, this leaves notable gaps in lifecycle management.