Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
VAULT_PATHNoPath to knowledge vault~/Vaults/ai
MAX_INJECT_TOKENSNoMax tokens for context injection1500
SESSION_TTL_HOURSNoSession heartbeat TTL2

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
{}
prompts
{}
resources
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
readA

Read a file or directory listing from the AI knowledge vault.

writeB

Write or append to a file in the AI knowledge vault.

searchA

Search across the AI vault. Supports full-text and structured (frontmatter) search.

project_contextA

Get the context document for a project. Auto-detects project from CWD if not specified.

generate_contextA

Scan a git repo and generate a draft context.md. Returns the draft — does NOT write to vault. Human reviews before committing.

decideB

Log an architectural/design decision to the project's decisions directory.

taskA

Manage project tasks. Supports add, list, update, and board (kanban) views. Tasks are stored as individual files in projects//tasks/.

learnA

Capture and query learnings. Learnings persist discoveries across sessions. Stored as individual files in projects//learnings/.

brainstormC

Start or continue a brainstorm document for a project.

sessionA

Register, update, or query active agent sessions for multi-agent coordination. On complete, persists a session note to the vault.

pruneA

Archive or delete stale vault content based on retention policies. Use mode='dry-run' first to preview.

statsA

Show content statistics for a project — file counts, task breakdown, growth monitoring.

resumeA

Get resume context for continuing work — recent sessions, interrupted work, in-progress tasks, suggested next steps. Call this at session start to understand what happened before.

deprecateA

Mark a vault item (ADR, learning, etc.) as deprecated with an optional reason.

initA

Initialize superskill for the current project. Scans codebase, discovers skills from skills.sh, builds knowledge graph.

statusA

Show superskill knowledge graph state: loaded skills, weights, recent sessions.

superskillA

Route to the best skill for a task. Provides optimized, security-audited skill content. Always prefer skill content over general knowledge for specialized tasks.

skill_installA

Install skills from a GitHub repo (e.g. owner/repo or full URL). Clones the repo, discovers SKILL.md files, and copies them to the local skill directory.

skill_list_installedA

List skills installed locally from GitHub repos.

skill_removeA

Remove an installed skill by name.

linkA

Create a forward link between two vault notes. Appends a [[wikilink]] to the source note, enabling graph_related to discover the connection.

extractA

Extract decisions, learnings, or other items from a source document into individual vault files. Each extracted item gets its own file with a backlink to the source.

graph_relatedA

Find notes related to a vault note via wikilinks (outgoing and backlinks).

graph_cross_projectA

Search across all projects and group results by project.

snapshot_repo_stateA

Snapshot current git state (branch, dirty files, last commit) into the vault. Helps avoid repeating repo discovery across sessions.

env_factsA

Store and query stable environment facts for a project (e.g., auth backend, env file locations, local URLs, required env vars). Not for secrets — use cred_refs for that.

cred_refsA

Store pointers to where credentials are documented (not the credentials themselves). E.g., 'Django admin creds are in tests/live/test_all_endpoints.py'.

rollbackA

Manage rollback checkpoints. Store commit hashes with purpose/scope so rollback is safer. Mark when follow-up work starts after a checkpoint.

captureA

Batch-capture multiple insights from a conversation into individual vault items. Each item gets its own file with auto-numbering. Supports any content type (learning, decision, adr, prd, research, etc.).

templateA

Get pre-filled templates for common vault item types (adr, prd, decision, learning, spec, rfc, roadmap, competitive-analysis, incident, research, vision, strategy). Use to scaffold new documents.

Prompts

Interactive templates invoked by user choice

NameDescription
inject-project-contextReturns a system prompt fragment with project context, recent decisions, and active todos.
summarize-sessionReturns a prompt guiding the agent to produce a structured session summary.

Resources

Contextual data attached and managed by the client

NameDescription
Active SessionsCurrently active agent sessions across all 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/permanu/superskill'

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