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Glama
asd-noor

ProjectContext

by asd-noor
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

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

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
save_memoryA

Save a memory to the long-term storage.

Args:
    category: The category of the memory (e.g., "architecture", "preference", "fix")
    topic: A short descriptive title for the memory
    content: The detailed memory/decision text

Returns:
    A dictionary with status, doc_id, topic, and category
delete_memoryA

Delete a memory by ID.

Args:
    doc_id: The ID of the memory to delete

Returns:
    A dictionary with status and message
update_memoryA

Update a memory by ID.

Args:
    doc_id: The ID of the memory to update
    category: New category (optional)
    topic: New topic (optional)
    content: New content (optional)

Returns:
    A dictionary with status and updated details
query_memoryA

Query memories using semantic and keyword search.

Args:
    query: Natural language search string
    top_k: Number of results to return (default: 3)

Returns:
    A list of matching memories with similarity scores
create_agendaA

Create a new agenda (plan/todo list).

Args:
    tasks: List of task dicts. Each task should have:
        - details: str (required)
        - is_optional: bool (optional, default False)
        - acceptance_guard: str (optional)
    title: Optional title for the agenda
    description: Optional description for the agenda

Returns:
    A dictionary with status and agenda_id
list_agendasC

List all agendas.

Args:
    active_only: If True, only show active agendas (default: True)

Returns:
    A list of agendas
get_agendaA

Get detailed information about an agenda, including its tasks.

Args:
    agenda_id: The ID of the agenda to retrieve

Returns:
    A dictionary with agenda details and tasks
search_agendasA

Search agendas by title or description.

Args:
    query: The search query string
    limit: Maximum number of results to return (default: 10)

Returns:
    A list of matching agendas
update_taskA

Update a task's completion status.

If all non-optional tasks are completed, the agenda will be marked as inactive.

Args:
    task_id: The ID of the task to update
    is_completed: True if the task is finished, False otherwise

Returns:
    A dictionary with status and message
update_agendaA

Update an agenda's status, details, or add new tasks.

Args:
    agenda_id: The ID of the agenda to update
    is_active: Set to False to deactivate the agenda (irreversible).
    new_tasks: Optional list of new task dicts to add (only if agenda is active).
    title: New title (optional)
    description: New description (optional)

Returns:
    A dictionary with status and message
delete_agendaB

Delete an agenda and its associated tasks.

Args:
    agenda_id: The ID of the agenda to delete

Returns:
    A dictionary with status and message

Prompts

Interactive templates invoked by user choice

NameDescription
setup_project_contextTemplate for initializing a new project with technical stack, goals, and conventions. Args: query: Optional user request or project description.
plan_feature_implementationGuides the model to break down a feature into a structured agenda with acceptance criteria.
summarize_and_rememberSummarize a conversation or technical discussion and save it to memory. Args: context: The text or conversation history to summarize.
debug_with_historyWorkflow for debugging issues using past bug fix memories and system context. Args: bug_description: Description of the current issue.
maintain_memory_healthWorkflow for identifying and updating outdated or redundant memories.

Resources

Contextual data attached and managed by the client

NameDescription
get_usage_guidelinesMemory Engine usage guidelines for AI agents. Provides comprehensive documentation on: - When to save memories (DO's and DON'Ts) - How to structure memories (category, topic, content) - How to query effectively - Best practices and common patterns - Search features and capabilities Returns: The complete usage guidelines as markdown text
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A3.9/5.0

Scored across 11 tools

Disambiguation5/5

Each tool clearly targets either the memory resource (save/delete/update/query) or the agenda resource (create/list/get/search/update/delete). Even update_task is distinct from update_agenda as it operates on a sub-resource, eliminating any real ambiguity.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern with snake_case, using clear verbs like save, delete, update, query, create, list, get, search. The pluralization of list_agendas vs get_agenda is a minor stylistic variation but consistent throughout.

Tool Count5/5

11 tools is well within the ideal 3-15 range, covering two distinct domains (memory and agenda) without bloat or thinness. Each tool earns its place in the set.

Completeness4/5

Memory has full CRUD plus semantic search, and agenda has create/read/update/delete plus task management. The only noticeable gap is the lack of a list_memories tool, but query_memory serves as a search-based alternative. Task deletion is also not available, but tasks can be added and marked complete, so the core lifecycle is covered.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources