Skip to main content
Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
HF_ENDPOINTNoHuggingFace mirror endpoint, used when downloading local rerank models (e.g., https://hf-mirror.com).
BRAIN_LLM_API_KEYNoAPI key for the LLM provider. Overrides the [llm] section in config.toml.
BRAIN_EMBED_API_KEYNoAPI key for the embedding provider. Overrides the [embed] section in config.toml.

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
brain_searchA

Search the personal knowledge base with hybrid retrieval (vector similarity fused with BM25 keyword matching). Behavior: returns up to k ranked excerpts, each with file path, heading breadcrumb and similarity score; no LLM call is made. Usage: reach for this when you need source material to quote, verify a claim, or see what exists on a topic; use brain_ask when you want a synthesized answer instead. Results are limited to the indexed sources — run brain_ingest first if recent files are missing.

brain_askA

Ask the knowledge base a question. Behavior: retrieves the most relevant excerpts, then an LLM synthesizes an answer grounded ONLY in them, ending with [source: path > section] citations. Usage: prefer this over brain_search whenever a question needs synthesis or an explanation; set verify=true to get a claim-by-claim audit (supported / partial / unsupported) when accuracy matters more than speed.

brain_linksA

Show the Obsidian-style [[wikilink]] graph around a note. Behavior: lists every note the given note links to (outbound) and every note that links back to it (inbound), based on the current index. Usage: use to explore how a topic connects to others before asking questions, or to find related notes when search keywords fail.

brain_statsA

Report what the index currently contains. Behavior: returns the store path, total chunk count, chunk count per source file, the embedding and chat models in use, and retrieval settings (hybrid, rrf_k, top_k). Reads local metadata only — no LLM or embedding calls. Usage: call before searching to see what is indexed, after brain_ingest to confirm what changed, or whenever answers seem to be missing a file you expected to be there. Takes no parameters.

brain_rememberA

Store a durable memory (decision, fact, preference, lesson learned) into the shared knowledge base. Behavior: writes a markdown note with frontmatter tags into the memories directory and indexes it immediately, so it is searchable within the same call. Memories persist across sessions and are shared by every MCP host that mounts loci — write from one IDE, recall from any other with brain_search or brain_ask. Usage: use for decisions, facts, preferences and lessons worth recording; do not use for ephemeral chit-chat.

brain_forgetA

Retract memories that are wrong or outdated. Behavior: memory notes matching the query move to a .trash folder (recoverable by hand) and their chunks leave the index immediately; nothing is permanently destroyed. Usage: use when a remembered fact was superseded or was a mistake; check with brain_search first if you are unsure what matches.

brain_ingestA

Incrementally (re)index the configured source directories. Safe to call repeatedly; only changed files are re-embedded.

Prompts

Interactive templates invoked by user choice

NameDescription
brain-briefingA structured briefing on a topic from your own notes.
study-planTurn scattered notes on a topic into a learning plan.
contradiction-checkFind contradictions and stale claims across your notes.

Resources

Contextual data attached and managed by the client

NameDescription
index-statsWhat is in the index: chunks per source, models, settings.

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/IvenKooLab/loci'

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