agent-context
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 |
|---|---|
| get_contextA | Read the project's persistent AI context: index, project description, constraints, decisions, plans, memory. Call with no arguments at session start to orient yourself. |
| record_decisionA | Record an architectural or otherwise important project decision as a permanent ADR. Call this whenever you make or the user confirms a significant technical choice. |
| record_noteA | Persist a short project note: a gotcha, convention, learning, or todo that future sessions should know. |
| update_planA | Create or fully overwrite a named project plan. Plans are mutable working documents, unlike decisions. |
| list_contextA | List all files in the project's ai_context folder with sizes and dates. |
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 5 tools
Each tool targets a distinct action: reading full context, listing files, recording a note, recording a decision, and updating a plan. The only potential overlap is between get_context and list_context, but their descriptions clearly differentiate content retrieval from file listing.
All tool names follow a consistent verb_noun pattern (get_context, record_note, record_decision, update_plan, list_context) using snake_case. The verbs are descriptive and the pattern is uniform across the set.
With 5 tools, the server is well-scoped for managing AI context. Each tool serves a clear purpose without redundancy, and the count is appropriate for the narrow domain.
The set covers the core workflow: reading the full context, listing stored files, and writing notes, decisions, and plans. Minor gaps exist (e.g., no direct note or decision deletion/editing), but these are acceptable given the 'permanent' nature of decisions and the mutable plan overwrite capability.