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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
OF_MCP_DB_PATHNoPath to the SQLite database index (optional, defaults to ./data/of.db)./data/of.db
ATLASSIAN_EMAILNoAtlassian email (optional, currently not needed as Confluence space is public)
ATLASSIAN_API_TOKENNoAtlassian API token (optional, currently not needed as Confluence space is public)

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
search_docsA

Search the Open Finance Brasil docs (BM25). Returns compact snippets.

Args: query: Natural-language query in Portuguese or English. limit: Max number of hits (default 6, hard-capped at 20).

get_pageA

Return the full markdown of a page.

Args: page_ref: Confluence page id, exact title, or substring of the title. section: Optional heading text. If provided, only the matching section (and its sub-sections) is returned.

list_sectionsA

List pages in the documentation tree.

Args: parent_id: If omitted, returns root pages of the OF space. Otherwise returns immediate children of the given page id.

answer_questionA

Retrieve the most relevant chunks formatted as RAG context.

The MCP itself does NOT call an LLM — it returns the raw context plus citations so the calling assistant can answer using its own context window (saving tokens vs. running a second model here).

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A4.4/5.0

Scored across 4 tools

Disambiguation5/5

Each tool serves a distinct purpose: answer_question returns RAG context, get_page retrieves full page markdown, list_sections navigates the doc tree, and search_docs performs keyword search. No overlap in functionality.

Naming Consistency5/5

All tools follow a consistent verb_noun snake_case pattern (answer_question, get_page, list_sections, search_docs), making it easy to infer their actions.

Tool Count5/5

With 4 tools, the server is well-scoped for documentation retrieval and search. Each tool earns its place, covering essential operations without unnecessary bloat.

Completeness5/5

The tool set covers the full lifecycle of documentation access: search (search_docs), context retrieval (answer_question), page content (get_page), and navigation (list_sections). No obvious gaps.